id	sid	tid	token	lemma	pos
ajst-24888	1	1	academic	academic	ADJ
ajst-24888	1	2	journal	journal	NOUN
ajst-24888	1	3	of	of	ADP
ajst-24888	1	4	science	science	NOUN
ajst-24888	1	5	and	and	CCONJ
ajst-24888	1	6	technology	technology	NOUN
ajst-24888	1	7	issn	issn	NOUN
ajst-24888	1	8	:	:	PUNCT
ajst-24888	1	9	2771	2771	NUM
ajst-24888	1	10	-	-	SYM
ajst-24888	1	11	3032	3032	NUM
ajst-24888	1	12	|	|	NOUN
ajst-24888	1	13	vol	vol	NOUN
ajst-24888	1	14	.	.	PROPN
ajst-24888	2	1	12	12	NUM
ajst-24888	2	2	,	,	PUNCT
ajst-24888	2	3	no	no	INTJ
ajst-24888	2	4	.	.	NOUN
ajst-24888	2	5	1	1	NUM
ajst-24888	2	6	,	,	PUNCT
ajst-24888	2	7	2024	2024	NUM
ajst-24888	2	8	121	121	NUM
ajst-24888	2	9	research	research	NOUN
ajst-24888	2	10	on	on	ADP
ajst-24888	2	11	lithology	lithology	NOUN
ajst-24888	2	12	identification	identification	NOUN
ajst-24888	2	13	based	base	VERB
ajst-24888	2	14	on	on	ADP
ajst-24888	2	15	machine	machine	NOUN
ajst-24888	2	16	learning	learn	VERB
ajst-24888	2	17	kunkun	kunkun	PROPN
ajst-24888	2	18	li	li	PROPN
ajst-24888	2	19	school	school	PROPN
ajst-24888	2	20	of	of	ADP
ajst-24888	2	21	xi'an	xi'an	PROPN
ajst-24888	2	22	shiyou	shiyou	PROPN
ajst-24888	2	23	university	university	PROPN
ajst-24888	2	24	,	,	PUNCT
ajst-24888	2	25	xi'an	xi'an	PROPN
ajst-24888	2	26	710065	710065	NUM
ajst-24888	2	27	,	,	PUNCT
ajst-24888	2	28	china	china	PROPN
ajst-24888	2	29	abstract	abstract	NOUN
ajst-24888	2	30	:	:	PUNCT
ajst-24888	2	31	machine	machine	NOUN
ajst-24888	2	32	learning	learning	NOUN
ajst-24888	2	33	has	have	VERB
ajst-24888	2	34	great	great	ADJ
ajst-24888	2	35	potential	potential	NOUN
ajst-24888	2	36	in	in	ADP
ajst-24888	2	37	lithology	lithology	NOUN
ajst-24888	2	38	identification	identification	NOUN
ajst-24888	2	39	.	.	PUNCT
ajst-24888	3	1	through	through	ADP
ajst-24888	3	2	supervised	supervised	ADJ
ajst-24888	3	3	learning	learning	NOUN
ajst-24888	3	4	,	,	PUNCT
ajst-24888	3	5	unsupervised	unsupervised	ADJ
ajst-24888	3	6	learning	learning	NOUN
ajst-24888	3	7	,	,	PUNCT
ajst-24888	3	8	semi	semi	ADJ
ajst-24888	3	9	-	-	ADJ
ajst-24888	3	10	supervised	supervised	ADJ
ajst-24888	3	11	learning	learning	NOUN
ajst-24888	3	12	,	,	PUNCT
ajst-24888	3	13	deep	deep	ADJ
ajst-24888	3	14	learning	learning	NOUN
ajst-24888	3	15	and	and	CCONJ
ajst-24888	3	16	other	other	ADJ
ajst-24888	3	17	methods	method	NOUN
ajst-24888	3	18	,	,	PUNCT
ajst-24888	3	19	features	feature	NOUN
ajst-24888	3	20	can	can	AUX
ajst-24888	3	21	be	be	AUX
ajst-24888	3	22	automatically	automatically	ADV
ajst-24888	3	23	extracted	extract	VERB
ajst-24888	3	24	from	from	ADP
ajst-24888	3	25	complex	complex	ADJ
ajst-24888	3	26	seismic	seismic	ADJ
ajst-24888	3	27	data	datum	NOUN
ajst-24888	3	28	and	and	CCONJ
ajst-24888	3	29	logging	log	VERB
ajst-24888	3	30	data	datum	NOUN
ajst-24888	3	31	to	to	PART
ajst-24888	3	32	achieve	achieve	VERB
ajst-24888	3	33	efficient	efficient	ADJ
ajst-24888	3	34	and	and	CCONJ
ajst-24888	3	35	accurate	accurate	ADJ
ajst-24888	3	36	lithology	lithology	NOUN
ajst-24888	3	37	classification	classification	NOUN
ajst-24888	3	38	.	.	PUNCT
ajst-24888	4	1	these	these	DET
ajst-24888	4	2	methods	method	NOUN
ajst-24888	4	3	not	not	PART
ajst-24888	4	4	only	only	ADV
ajst-24888	4	5	improve	improve	VERB
ajst-24888	4	6	the	the	DET
ajst-24888	4	7	accuracy	accuracy	NOUN
ajst-24888	4	8	and	and	CCONJ
ajst-24888	4	9	efficiency	efficiency	NOUN
ajst-24888	4	10	of	of	ADP
ajst-24888	4	11	lithology	lithology	NOUN
ajst-24888	4	12	identification	identification	NOUN
ajst-24888	4	13	,	,	PUNCT
ajst-24888	4	14	but	but	CCONJ
ajst-24888	4	15	also	also	ADV
ajst-24888	4	16	reduce	reduce	VERB
ajst-24888	4	17	the	the	DET
ajst-24888	4	18	workload	workload	NOUN
ajst-24888	4	19	of	of	ADP
ajst-24888	4	20	geologists	geologist	NOUN
ajst-24888	4	21	,	,	PUNCT
ajst-24888	4	22	allowing	allow	VERB
ajst-24888	4	23	them	they	PRON
ajst-24888	4	24	to	to	PART
ajst-24888	4	25	focus	focus	VERB
ajst-24888	4	26	on	on	ADP
ajst-24888	4	27	higher	high	ADJ
ajst-24888	4	28	-	-	PUNCT
ajst-24888	4	29	level	level	NOUN
ajst-24888	4	30	analysis	analysis	NOUN
ajst-24888	4	31	and	and	CCONJ
ajst-24888	4	32	decision	decision	NOUN
ajst-24888	4	33	making	making	NOUN
ajst-24888	4	34	.	.	PUNCT
ajst-24888	5	1	despite	despite	SCONJ
ajst-24888	5	2	significant	significant	ADJ
ajst-24888	5	3	progress	progress	NOUN
ajst-24888	5	4	,	,	PUNCT
ajst-24888	5	5	machine	machine	NOUN
ajst-24888	5	6	learning	learning	NOUN
ajst-24888	5	7	still	still	ADV
ajst-24888	5	8	faces	face	VERB
ajst-24888	5	9	many	many	ADJ
ajst-24888	5	10	challenges	challenge	NOUN
ajst-24888	5	11	in	in	ADP
ajst-24888	5	12	lithology	lithology	NOUN
ajst-24888	5	13	identification	identification	NOUN
ajst-24888	5	14	.	.	PUNCT
ajst-24888	6	1	first	first	ADV
ajst-24888	6	2	,	,	PUNCT
ajst-24888	6	3	data	datum	NOUN
ajst-24888	6	4	quality	quality	NOUN
ajst-24888	6	5	and	and	CCONJ
ajst-24888	6	6	quantity	quantity	NOUN
ajst-24888	6	7	limitations	limitation	NOUN
ajst-24888	6	8	remain	remain	VERB
ajst-24888	6	9	a	a	DET
ajst-24888	6	10	major	major	ADJ
ajst-24888	6	11	problem	problem	NOUN
ajst-24888	6	12	,	,	PUNCT
ajst-24888	6	13	especially	especially	ADV
ajst-24888	6	14	in	in	ADP
ajst-24888	6	15	certain	certain	ADJ
ajst-24888	6	16	areas	area	NOUN
ajst-24888	6	17	where	where	SCONJ
ajst-24888	6	18	obtaining	obtain	VERB
ajst-24888	6	19	high	high	ADJ
ajst-24888	6	20	-	-	PUNCT
ajst-24888	6	21	quality	quality	NOUN
ajst-24888	6	22	seismic	seismic	ADJ
ajst-24888	6	23	and	and	CCONJ
ajst-24888	6	24	logging	log	VERB
ajst-24888	6	25	data	datum	NOUN
ajst-24888	6	26	is	be	AUX
ajst-24888	6	27	difficult	difficult	ADJ
ajst-24888	6	28	.	.	PUNCT
ajst-24888	7	1	second	second	ADJ
ajst-24888	7	2	,	,	PUNCT
ajst-24888	7	3	the	the	DET
ajst-24888	7	4	training	training	NOUN
ajst-24888	7	5	and	and	CCONJ
ajst-24888	7	6	interpretability	interpretability	NOUN
ajst-24888	7	7	of	of	ADP
ajst-24888	7	8	complex	complex	ADJ
ajst-24888	7	9	models	model	NOUN
ajst-24888	7	10	also	also	ADV
ajst-24888	7	11	need	need	VERB
ajst-24888	7	12	to	to	PART
ajst-24888	7	13	be	be	AUX
ajst-24888	7	14	addressed	address	VERB
ajst-24888	7	15	,	,	PUNCT
ajst-24888	7	16	especially	especially	ADV
ajst-24888	7	17	because	because	SCONJ
ajst-24888	7	18	the	the	DET
ajst-24888	7	19	"	"	PUNCT
ajst-24888	7	20	black	black	ADJ
ajst-24888	7	21	box	box	NOUN
ajst-24888	7	22	"	"	PUNCT
ajst-24888	7	23	nature	nature	NOUN
ajst-24888	7	24	of	of	ADP
ajst-24888	7	25	deep	deep	ADJ
ajst-24888	7	26	learning	learning	NOUN
ajst-24888	7	27	models	model	NOUN
ajst-24888	7	28	makes	make	VERB
ajst-24888	7	29	it	it	PRON
ajst-24888	7	30	difficult	difficult	ADJ
ajst-24888	7	31	for	for	SCONJ
ajst-24888	7	32	geologists	geologist	NOUN
ajst-24888	7	33	to	to	PART
ajst-24888	7	34	understand	understand	VERB
ajst-24888	7	35	their	their	PRON
ajst-24888	7	36	internal	internal	ADJ
ajst-24888	7	37	mechanisms	mechanism	NOUN
ajst-24888	7	38	and	and	CCONJ
ajst-24888	7	39	predictions	prediction	NOUN
ajst-24888	7	40	.	.	PUNCT
ajst-24888	8	1	in	in	ADP
ajst-24888	8	2	addition	addition	NOUN
ajst-24888	8	3	,	,	PUNCT
ajst-24888	8	4	the	the	DET
ajst-24888	8	5	generalization	generalization	NOUN
ajst-24888	8	6	ability	ability	NOUN
ajst-24888	8	7	and	and	CCONJ
ajst-24888	8	8	overfitting	overfitting	NOUN
ajst-24888	8	9	of	of	ADP
ajst-24888	8	10	models	model	NOUN
ajst-24888	8	11	,	,	PUNCT
ajst-24888	8	12	as	as	ADV
ajst-24888	8	13	well	well	ADV
ajst-24888	8	14	as	as	ADP
ajst-24888	8	15	the	the	DET
ajst-24888	8	16	need	need	NOUN
ajst-24888	8	17	for	for	ADP
ajst-24888	8	18	real	real	ADJ
ajst-24888	8	19	-	-	PUNCT
ajst-24888	8	20	time	time	NOUN
ajst-24888	8	21	data	datum	NOUN
ajst-24888	8	22	processing	processing	NOUN
ajst-24888	8	23	in	in	ADP
ajst-24888	8	24	practical	practical	ADJ
ajst-24888	8	25	applications	application	NOUN
ajst-24888	8	26	,	,	PUNCT
ajst-24888	8	27	are	be	AUX
ajst-24888	8	28	also	also	ADV
ajst-24888	8	29	urgent	urgent	ADJ
ajst-24888	8	30	challenges	challenge	NOUN
ajst-24888	8	31	to	to	PART
ajst-24888	8	32	be	be	AUX
ajst-24888	8	33	solved	solve	VERB
ajst-24888	8	34	.	.	PUNCT
ajst-24888	9	1	to	to	PART
ajst-24888	9	2	address	address	VERB
ajst-24888	9	3	these	these	DET
ajst-24888	9	4	challenges	challenge	NOUN
ajst-24888	9	5	,	,	PUNCT
ajst-24888	9	6	this	this	DET
ajst-24888	9	7	paper	paper	NOUN
ajst-24888	9	8	proposes	propose	VERB
ajst-24888	9	9	several	several	ADJ
ajst-24888	9	10	solutions	solution	NOUN
ajst-24888	9	11	and	and	CCONJ
ajst-24888	9	12	future	future	ADJ
ajst-24888	9	13	directions	direction	NOUN
ajst-24888	9	14	.	.	PUNCT
ajst-24888	10	1	data	datum	NOUN
ajst-24888	10	2	enhancement	enhancement	NOUN
ajst-24888	10	3	and	and	CCONJ
ajst-24888	10	4	synthesis	synthesis	NOUN
ajst-24888	10	5	techniques	technique	NOUN
ajst-24888	10	6	can	can	AUX
ajst-24888	10	7	extend	extend	VERB
ajst-24888	10	8	existing	exist	VERB
ajst-24888	10	9	data	datum	NOUN
ajst-24888	10	10	sets	set	NOUN
ajst-24888	10	11	and	and	CCONJ
ajst-24888	10	12	improve	improve	VERB
ajst-24888	10	13	the	the	DET
ajst-24888	10	14	robustness	robustness	NOUN
ajst-24888	10	15	and	and	CCONJ
ajst-24888	10	16	accuracy	accuracy	NOUN
ajst-24888	10	17	of	of	ADP
ajst-24888	10	18	models	model	NOUN
ajst-24888	10	19	.	.	PUNCT
ajst-24888	11	1	the	the	DET
ajst-24888	11	2	development	development	NOUN
ajst-24888	11	3	of	of	ADP
ajst-24888	11	4	interpretative	interpretative	ADJ
ajst-24888	11	5	models	model	NOUN
ajst-24888	11	6	and	and	CCONJ
ajst-24888	11	7	visualization	visualization	NOUN
ajst-24888	11	8	tools	tool	NOUN
ajst-24888	11	9	helps	help	VERB
ajst-24888	11	10	geologists	geologist	NOUN
ajst-24888	11	11	understand	understand	VERB
ajst-24888	11	12	and	and	CCONJ
ajst-24888	11	13	trust	trust	VERB
ajst-24888	11	14	the	the	DET
ajst-24888	11	15	decision	decision	NOUN
ajst-24888	11	16	-	-	PUNCT
ajst-24888	11	17	making	make	VERB
ajst-24888	11	18	process	process	NOUN
ajst-24888	11	19	of	of	ADP
ajst-24888	11	20	models	model	NOUN
ajst-24888	11	21	.	.	PUNCT
ajst-24888	12	1	multi	multi	ADJ
ajst-24888	12	2	-	-	ADJ
ajst-24888	12	3	source	source	NOUN
ajst-24888	12	4	data	data	NOUN
ajst-24888	12	5	fusion	fusion	NOUN
ajst-24888	12	6	technology	technology	NOUN
ajst-24888	12	7	can	can	AUX
ajst-24888	12	8	effectively	effectively	ADV
ajst-24888	12	9	use	use	VERB
ajst-24888	12	10	multi	multi	ADJ
ajst-24888	12	11	-	-	ADJ
ajst-24888	12	12	source	source	ADJ
ajst-24888	12	13	heterogeneous	heterogeneous	ADJ
ajst-24888	12	14	data	datum	NOUN
ajst-24888	12	15	such	such	ADJ
ajst-24888	12	16	as	as	ADP
ajst-24888	12	17	seismic	seismic	ADJ
ajst-24888	12	18	data	datum	NOUN
ajst-24888	12	19	,	,	PUNCT
ajst-24888	12	20	well	well	ADV
ajst-24888	12	21	logging	log	VERB
ajst-24888	12	22	data	datum	NOUN
ajst-24888	12	23	and	and	CCONJ
ajst-24888	12	24	geological	geological	ADJ
ajst-24888	12	25	map	map	NOUN
ajst-24888	12	26	to	to	PART
ajst-24888	12	27	improve	improve	VERB
ajst-24888	12	28	model	model	NOUN
ajst-24888	12	29	performance	performance	NOUN
ajst-24888	12	30	.	.	PUNCT
ajst-24888	13	1	online	online	ADJ
ajst-24888	13	2	learning	learning	NOUN
ajst-24888	13	3	and	and	CCONJ
ajst-24888	13	4	transfer	transfer	VERB
ajst-24888	13	5	learning	learning	NOUN
ajst-24888	13	6	technologies	technology	NOUN
ajst-24888	13	7	can	can	AUX
ajst-24888	13	8	update	update	VERB
ajst-24888	13	9	models	model	NOUN
ajst-24888	13	10	in	in	ADP
ajst-24888	13	11	real	real	ADJ
ajst-24888	13	12	time	time	NOUN
ajst-24888	13	13	,	,	PUNCT
ajst-24888	13	14	improve	improve	VERB
ajst-24888	13	15	the	the	DET
ajst-24888	13	16	adaptability	adaptability	NOUN
ajst-24888	13	17	and	and	CCONJ
ajst-24888	13	18	generalization	generalization	NOUN
ajst-24888	13	19	ability	ability	NOUN
ajst-24888	13	20	of	of	ADP
ajst-24888	13	21	models	model	NOUN
ajst-24888	13	22	,	,	PUNCT
ajst-24888	13	23	and	and	CCONJ
ajst-24888	13	24	develop	develop	VERB
ajst-24888	13	25	more	more	ADV
ajst-24888	13	26	accurate	accurate	ADJ
ajst-24888	13	27	and	and	CCONJ
ajst-24888	13	28	interpretable	interpretable	ADJ
ajst-24888	13	29	models	model	NOUN
ajst-24888	13	30	.	.	PUNCT
ajst-24888	14	1	keywords	keyword	NOUN
ajst-24888	14	2	:	:	PUNCT
ajst-24888	14	3	machine	machine	NOUN
ajst-24888	14	4	learning	learning	NOUN
ajst-24888	14	5	;	;	PUNCT
ajst-24888	14	6	lithology	lithology	NOUN
ajst-24888	14	7	identification	identification	NOUN
ajst-24888	14	8	;	;	PUNCT
ajst-24888	14	9	deep	deep	ADJ
ajst-24888	14	10	learning	learning	NOUN
ajst-24888	14	11	.	.	PUNCT
ajst-24888	15	1	1	1	X
ajst-24888	15	2	.	.	X
ajst-24888	15	3	introduction	introduction	NOUN
ajst-24888	15	4	lithology	lithology	NOUN
ajst-24888	15	5	identification	identification	NOUN
ajst-24888	15	6	is	be	AUX
ajst-24888	15	7	an	an	DET
ajst-24888	15	8	important	important	ADJ
ajst-24888	15	9	task	task	NOUN
ajst-24888	15	10	in	in	ADP
ajst-24888	15	11	geology	geology	NOUN
ajst-24888	15	12	and	and	CCONJ
ajst-24888	15	13	petroleum	petroleum	NOUN
ajst-24888	15	14	exploration	exploration	NOUN
ajst-24888	15	15	,	,	PUNCT
ajst-24888	15	16	which	which	PRON
ajst-24888	15	17	determines	determine	VERB
ajst-24888	15	18	the	the	DET
ajst-24888	15	19	types	type	NOUN
ajst-24888	15	20	of	of	ADP
ajst-24888	15	21	underground	underground	ADJ
ajst-24888	15	22	rocks	rock	NOUN
ajst-24888	15	23	by	by	ADP
ajst-24888	15	24	analyzing	analyze	VERB
ajst-24888	15	25	geological	geological	ADJ
ajst-24888	15	26	data	datum	NOUN
ajst-24888	15	27	[	[	X
ajst-24888	15	28	1	1	NUM
ajst-24888	15	29	]	]	PUNCT
ajst-24888	15	30	.	.	PUNCT
ajst-24888	16	1	traditional	traditional	ADJ
ajst-24888	16	2	lithology	lithology	NOUN
ajst-24888	16	3	identification	identification	NOUN
ajst-24888	16	4	methods	method	NOUN
ajst-24888	16	5	rely	rely	VERB
ajst-24888	16	6	on	on	ADP
ajst-24888	16	7	the	the	DET
ajst-24888	16	8	expertise	expertise	NOUN
ajst-24888	16	9	and	and	CCONJ
ajst-24888	16	10	experience	experience	NOUN
ajst-24888	16	11	of	of	ADP
ajst-24888	16	12	geologists	geologist	NOUN
ajst-24888	16	13	,	,	PUNCT
ajst-24888	16	14	combining	combine	VERB
ajst-24888	16	15	geological	geological	ADJ
ajst-24888	16	16	maps	map	NOUN
ajst-24888	16	17	,	,	PUNCT
ajst-24888	16	18	rock	rock	NOUN
ajst-24888	16	19	samples	sample	NOUN
ajst-24888	16	20	,	,	PUNCT
ajst-24888	16	21	seismic	seismic	ADJ
ajst-24888	16	22	data	datum	NOUN
ajst-24888	16	23	and	and	CCONJ
ajst-24888	16	24	well	well	ADV
ajst-24888	16	25	logging	log	VERB
ajst-24888	16	26	data	datum	NOUN
ajst-24888	16	27	.	.	PUNCT
ajst-24888	17	1	although	although	SCONJ
ajst-24888	17	2	these	these	DET
ajst-24888	17	3	methods	method	NOUN
ajst-24888	17	4	are	be	AUX
ajst-24888	17	5	effective	effective	ADJ
ajst-24888	17	6	in	in	ADP
ajst-24888	17	7	some	some	DET
ajst-24888	17	8	cases	case	NOUN
ajst-24888	17	9	,	,	PUNCT
ajst-24888	17	10	they	they	PRON
ajst-24888	17	11	often	often	ADV
ajst-24888	17	12	have	have	VERB
ajst-24888	17	13	problems	problem	NOUN
ajst-24888	17	14	such	such	ADJ
ajst-24888	17	15	as	as	ADP
ajst-24888	17	16	strong	strong	ADJ
ajst-24888	17	17	subjectivity	subjectivity	NOUN
ajst-24888	17	18	and	and	CCONJ
ajst-24888	17	19	low	low	ADJ
ajst-24888	17	20	efficiency	efficiency	NOUN
ajst-24888	17	21	because	because	SCONJ
ajst-24888	17	22	they	they	PRON
ajst-24888	17	23	rely	rely	VERB
ajst-24888	17	24	on	on	ADP
ajst-24888	17	25	human	human	ADJ
ajst-24888	17	26	judgment	judgment	NOUN
ajst-24888	18	1	[	[	X
ajst-24888	18	2	2	2	NUM
ajst-24888	18	3	]	]	PUNCT
ajst-24888	18	4	.	.	PUNCT
ajst-24888	19	1	with	with	ADP
ajst-24888	19	2	the	the	DET
ajst-24888	19	3	development	development	NOUN
ajst-24888	19	4	of	of	ADP
ajst-24888	19	5	information	information	NOUN
ajst-24888	19	6	technology	technology	NOUN
ajst-24888	19	7	,	,	PUNCT
ajst-24888	19	8	data	data	NOUN
ajst-24888	19	9	-	-	PUNCT
ajst-24888	19	10	driven	drive	VERB
ajst-24888	19	11	machine	machine	NOUN
ajst-24888	19	12	learning	learning	NOUN
ajst-24888	19	13	has	have	AUX
ajst-24888	19	14	shown	show	VERB
ajst-24888	19	15	great	great	ADJ
ajst-24888	19	16	potential	potential	NOUN
ajst-24888	19	17	in	in	ADP
ajst-24888	19	18	lithology	lithology	NOUN
ajst-24888	19	19	identification	identification	NOUN
ajst-24888	19	20	.	.	PUNCT
ajst-24888	20	1	machine	machine	NOUN
ajst-24888	20	2	learning	learning	NOUN
ajst-24888	20	3	is	be	AUX
ajst-24888	20	4	a	a	DET
ajst-24888	20	5	technology	technology	NOUN
ajst-24888	20	6	that	that	PRON
ajst-24888	20	7	uses	use	VERB
ajst-24888	20	8	computers	computer	NOUN
ajst-24888	20	9	to	to	PART
ajst-24888	20	10	automatically	automatically	ADV
ajst-24888	20	11	learn	learn	VERB
ajst-24888	20	12	from	from	ADP
ajst-24888	20	13	data	datum	NOUN
ajst-24888	20	14	and	and	CCONJ
ajst-24888	20	15	make	make	VERB
ajst-24888	20	16	predictions	prediction	NOUN
ajst-24888	20	17	.	.	PUNCT
ajst-24888	21	1	its	its	PRON
ajst-24888	21	2	powerful	powerful	ADJ
ajst-24888	21	3	data	data	NOUN
ajst-24888	21	4	processing	processing	NOUN
ajst-24888	21	5	and	and	CCONJ
ajst-24888	21	6	pattern	pattern	NOUN
ajst-24888	21	7	recognition	recognition	NOUN
ajst-24888	21	8	capabilities	capability	NOUN
ajst-24888	21	9	make	make	VERB
ajst-24888	21	10	it	it	PRON
ajst-24888	21	11	widely	widely	ADV
ajst-24888	21	12	used	use	VERB
ajst-24888	21	13	in	in	ADP
ajst-24888	21	14	various	various	ADJ
ajst-24888	21	15	fields	field	NOUN
ajst-24888	21	16	[	[	X
ajst-24888	21	17	3	3	NUM
ajst-24888	21	18	]	]	PUNCT
ajst-24888	21	19	.	.	PUNCT
ajst-24888	22	1	especially	especially	ADV
ajst-24888	22	2	in	in	ADP
ajst-24888	22	3	the	the	DET
ajst-24888	22	4	field	field	NOUN
ajst-24888	22	5	of	of	ADP
ajst-24888	22	6	lithology	lithology	NOUN
ajst-24888	22	7	identification	identification	NOUN
ajst-24888	22	8	,	,	PUNCT
ajst-24888	22	9	machine	machine	NOUN
ajst-24888	22	10	learning	learning	NOUN
ajst-24888	22	11	methods	method	NOUN
ajst-24888	22	12	can	can	AUX
ajst-24888	22	13	process	process	VERB
ajst-24888	22	14	a	a	DET
ajst-24888	22	15	large	large	ADJ
ajst-24888	22	16	amount	amount	NOUN
ajst-24888	22	17	of	of	ADP
ajst-24888	22	18	geological	geological	ADJ
ajst-24888	22	19	data	datum	NOUN
ajst-24888	22	20	,	,	PUNCT
ajst-24888	22	21	automatically	automatically	ADV
ajst-24888	22	22	extract	extract	VERB
ajst-24888	22	23	features	feature	NOUN
ajst-24888	22	24	and	and	CCONJ
ajst-24888	22	25	classify	classify	VERB
ajst-24888	22	26	them	they	PRON
ajst-24888	22	27	,	,	PUNCT
ajst-24888	22	28	and	and	CCONJ
ajst-24888	22	29	significantly	significantly	ADV
ajst-24888	22	30	improve	improve	VERB
ajst-24888	22	31	the	the	DET
ajst-24888	22	32	accuracy	accuracy	NOUN
ajst-24888	22	33	and	and	CCONJ
ajst-24888	22	34	efficiency	efficiency	NOUN
ajst-24888	22	35	of	of	ADP
ajst-24888	22	36	lithology	lithology	NOUN
ajst-24888	22	37	identification	identification	NOUN
ajst-24888	22	38	[	[	X
ajst-24888	22	39	4	4	NUM
ajst-24888	22	40	]	]	PUNCT
ajst-24888	22	41	.	.	PUNCT
ajst-24888	23	1	in	in	ADP
ajst-24888	23	2	recent	recent	ADJ
ajst-24888	23	3	years	year	NOUN
ajst-24888	23	4	,	,	PUNCT
ajst-24888	23	5	with	with	ADP
ajst-24888	23	6	the	the	DET
ajst-24888	23	7	rise	rise	NOUN
ajst-24888	23	8	of	of	ADP
ajst-24888	23	9	deep	deep	ADJ
ajst-24888	23	10	learning	learning	NOUN
ajst-24888	23	11	technology	technology	NOUN
ajst-24888	23	12	,	,	PUNCT
ajst-24888	23	13	convolutional	convolutional	ADJ
ajst-24888	23	14	neural	neural	ADJ
ajst-24888	23	15	network	network	NOUN
ajst-24888	23	16	(	(	PUNCT
ajst-24888	23	17	cnn	cnn	PROPN
ajst-24888	23	18	)	)	PUNCT
ajst-24888	24	1	[	[	X
ajst-24888	24	2	5	5	NUM
ajst-24888	24	3	]	]	PUNCT
ajst-24888	24	4	and	and	CCONJ
ajst-24888	24	5	other	other	ADJ
ajst-24888	24	6	models	model	NOUN
ajst-24888	24	7	have	have	AUX
ajst-24888	24	8	achieved	achieve	VERB
ajst-24888	24	9	remarkable	remarkable	ADJ
ajst-24888	24	10	results	result	NOUN
ajst-24888	24	11	in	in	ADP
ajst-24888	24	12	lithology	lithology	NOUN
ajst-24888	24	13	identification	identification	NOUN
ajst-24888	24	14	.	.	PUNCT
ajst-24888	25	1	these	these	DET
ajst-24888	25	2	methods	method	NOUN
ajst-24888	25	3	can	can	AUX
ajst-24888	25	4	not	not	PART
ajst-24888	25	5	only	only	ADV
ajst-24888	25	6	process	process	VERB
ajst-24888	25	7	structured	structure	VERB
ajst-24888	25	8	data	datum	NOUN
ajst-24888	25	9	,	,	PUNCT
ajst-24888	25	10	but	but	CCONJ
ajst-24888	25	11	also	also	ADV
ajst-24888	25	12	unstructured	unstructured	ADJ
ajst-24888	25	13	data	datum	NOUN
ajst-24888	25	14	such	such	ADJ
ajst-24888	25	15	as	as	ADP
ajst-24888	25	16	seismic	seismic	ADJ
ajst-24888	25	17	images	image	NOUN
ajst-24888	25	18	,	,	PUNCT
ajst-24888	25	19	which	which	PRON
ajst-24888	25	20	further	far	ADV
ajst-24888	25	21	expands	expand	VERB
ajst-24888	25	22	the	the	DET
ajst-24888	25	23	application	application	NOUN
ajst-24888	25	24	range	range	NOUN
ajst-24888	25	25	of	of	ADP
ajst-24888	25	26	lithology	lithology	NOUN
ajst-24888	25	27	identification	identification	NOUN
ajst-24888	25	28	.	.	PUNCT
ajst-24888	26	1	in	in	ADP
ajst-24888	26	2	summary	summary	NOUN
ajst-24888	26	3	,	,	PUNCT
ajst-24888	26	4	through	through	ADP
ajst-24888	26	5	systematic	systematic	ADJ
ajst-24888	26	6	review	review	NOUN
ajst-24888	26	7	and	and	CCONJ
ajst-24888	26	8	analysis	analysis	NOUN
ajst-24888	26	9	of	of	ADP
ajst-24888	26	10	existing	exist	VERB
ajst-24888	26	11	literature	literature	NOUN
ajst-24888	26	12	,	,	PUNCT
ajst-24888	26	13	this	this	DET
ajst-24888	26	14	paper	paper	NOUN
ajst-24888	26	15	aims	aim	VERB
ajst-24888	26	16	to	to	PART
ajst-24888	26	17	provide	provide	VERB
ajst-24888	26	18	a	a	DET
ajst-24888	26	19	comprehensive	comprehensive	ADJ
ajst-24888	26	20	reference	reference	NOUN
ajst-24888	26	21	for	for	ADP
ajst-24888	26	22	researchers	researcher	NOUN
ajst-24888	26	23	and	and	CCONJ
ajst-24888	26	24	engineers	engineer	NOUN
ajst-24888	26	25	,	,	PUNCT
ajst-24888	26	26	help	help	VERB
ajst-24888	26	27	them	they	PRON
ajst-24888	26	28	understand	understand	VERB
ajst-24888	26	29	the	the	DET
ajst-24888	26	30	current	current	ADJ
ajst-24888	26	31	research	research	NOUN
ajst-24888	26	32	progress	progress	NOUN
ajst-24888	26	33	of	of	ADP
ajst-24888	26	34	lithology	lithology	NOUN
ajst-24888	26	35	identification	identification	NOUN
ajst-24888	26	36	based	base	VERB
ajst-24888	26	37	on	on	ADP
ajst-24888	26	38	machine	machine	NOUN
ajst-24888	26	39	learning	learning	NOUN
ajst-24888	26	40	,	,	PUNCT
ajst-24888	26	41	and	and	CCONJ
ajst-24888	26	42	provide	provide	VERB
ajst-24888	26	43	guidance	guidance	NOUN
ajst-24888	26	44	for	for	ADP
ajst-24888	26	45	future	future	ADJ
ajst-24888	26	46	research	research	NOUN
ajst-24888	26	47	and	and	CCONJ
ajst-24888	26	48	application	application	NOUN
ajst-24888	26	49	.	.	PUNCT
ajst-24888	27	1	it	it	PRON
ajst-24888	27	2	is	be	AUX
ajst-24888	27	3	hoped	hope	VERB
ajst-24888	27	4	that	that	SCONJ
ajst-24888	27	5	this	this	DET
ajst-24888	27	6	paper	paper	NOUN
ajst-24888	27	7	can	can	AUX
ajst-24888	27	8	promote	promote	VERB
ajst-24888	27	9	the	the	DET
ajst-24888	27	10	further	further	ADJ
ajst-24888	27	11	application	application	NOUN
ajst-24888	27	12	and	and	CCONJ
ajst-24888	27	13	development	development	NOUN
ajst-24888	27	14	of	of	ADP
ajst-24888	27	15	machine	machine	NOUN
ajst-24888	27	16	learning	learn	VERB
ajst-24888	27	17	technology	technology	NOUN
ajst-24888	27	18	in	in	ADP
ajst-24888	27	19	lithology	lithology	NOUN
ajst-24888	27	20	identification	identification	NOUN
ajst-24888	27	21	,	,	PUNCT
ajst-24888	27	22	and	and	CCONJ
ajst-24888	27	23	make	make	VERB
ajst-24888	27	24	contributions	contribution	NOUN
ajst-24888	27	25	to	to	ADP
ajst-24888	27	26	geology	geology	NOUN
ajst-24888	27	27	,	,	PUNCT
ajst-24888	27	28	petroleum	petroleum	NOUN
ajst-24888	27	29	exploration	exploration	NOUN
ajst-24888	27	30	and	and	CCONJ
ajst-24888	27	31	other	other	ADJ
ajst-24888	27	32	related	related	ADJ
ajst-24888	27	33	fields	field	NOUN
ajst-24888	27	34	.	.	PUNCT
ajst-24888	28	1	2	2	X
ajst-24888	28	2	.	.	X
ajst-24888	28	3	summary	summary	NOUN
ajst-24888	28	4	of	of	ADP
ajst-24888	28	5	existing	exist	VERB
ajst-24888	28	6	research	research	NOUN
ajst-24888	28	7	results	result	NOUN
ajst-24888	28	8	fang	fang	PROPN
ajst-24888	28	9	dazhi[6]et	dazhi[6]et	PROPN
ajst-24888	28	10	al	al	PROPN
ajst-24888	28	11	.	.	PROPN
ajst-24888	28	12	used	use	VERB
ajst-24888	28	13	svm	svm	PROPN
ajst-24888	28	14	to	to	PART
ajst-24888	28	15	classify	classify	VERB
ajst-24888	28	16	logging	log	VERB
ajst-24888	28	17	data	datum	NOUN
ajst-24888	28	18	in	in	ADP
ajst-24888	28	19	the	the	DET
ajst-24888	28	20	lithology	lithology	NOUN
ajst-24888	28	21	identification	identification	NOUN
ajst-24888	28	22	study	study	NOUN
ajst-24888	28	23	of	of	ADP
ajst-24888	28	24	an	an	DET
ajst-24888	28	25	oilfield	oilfield	NOUN
ajst-24888	28	26	.	.	PUNCT
ajst-24888	29	1	their	their	PRON
ajst-24888	29	2	research	research	NOUN
ajst-24888	29	3	shows	show	VERB
ajst-24888	29	4	that	that	SCONJ
ajst-24888	29	5	svm	svm	PROPN
ajst-24888	29	6	is	be	AUX
ajst-24888	29	7	excellent	excellent	ADJ
ajst-24888	29	8	at	at	ADP
ajst-24888	29	9	distinguishing	distinguish	VERB
ajst-24888	29	10	between	between	ADP
ajst-24888	29	11	different	different	ADJ
ajst-24888	29	12	types	type	NOUN
ajst-24888	29	13	of	of	ADP
ajst-24888	29	14	rocks	rock	NOUN
ajst-24888	29	15	,	,	PUNCT
ajst-24888	29	16	especially	especially	ADV
ajst-24888	29	17	when	when	SCONJ
ajst-24888	29	18	dealing	deal	VERB
ajst-24888	29	19	with	with	ADP
ajst-24888	29	20	highdimensional	highdimensional	ADJ
ajst-24888	29	21	data	datum	NOUN
ajst-24888	29	22	.	.	PUNCT
ajst-24888	30	1	by	by	ADP
ajst-24888	30	2	optimizing	optimize	VERB
ajst-24888	30	3	kernel	kernel	PROPN
ajst-24888	30	4	function	function	NOUN
ajst-24888	30	5	and	and	CCONJ
ajst-24888	30	6	parameters	parameter	NOUN
ajst-24888	30	7	,	,	PUNCT
ajst-24888	30	8	svm	svm	ADJ
ajst-24888	30	9	model	model	NOUN
ajst-24888	30	10	realizes	realize	VERB
ajst-24888	30	11	high	high	ADJ
ajst-24888	30	12	precision	precision	NOUN
ajst-24888	30	13	lithology	lithology	NOUN
ajst-24888	30	14	classification	classification	NOUN
ajst-24888	30	15	,	,	PUNCT
ajst-24888	30	16	and	and	CCONJ
ajst-24888	30	17	the	the	DET
ajst-24888	30	18	identification	identification	NOUN
ajst-24888	30	19	accuracy	accuracy	NOUN
ajst-24888	30	20	reaches	reach	VERB
ajst-24888	30	21	more	more	ADJ
ajst-24888	30	22	than	than	ADP
ajst-24888	30	23	95	95	NUM
ajst-24888	30	24	%	%	NOUN
ajst-24888	30	25	.	.	PUNCT
ajst-24888	31	1	wang	wang	PROPN
ajst-24888	31	2	qi	qi	PROPN
ajst-24888	32	1	[	[	X
ajst-24888	32	2	7	7	NUM
ajst-24888	32	3	]	]	PUNCT
ajst-24888	32	4	et	et	PROPN
ajst-24888	32	5	al	al	PROPN
ajst-24888	32	6	.	.	PROPN
ajst-24888	32	7	used	use	VERB
ajst-24888	32	8	random	random	ADJ
ajst-24888	32	9	forest	forest	NOUN
ajst-24888	32	10	model	model	NOUN
ajst-24888	32	11	to	to	PART
ajst-24888	32	12	conduct	conduct	VERB
ajst-24888	32	13	integrated	integrated	ADJ
ajst-24888	32	14	learning	learning	NOUN
ajst-24888	32	15	of	of	ADP
ajst-24888	32	16	multiple	multiple	ADJ
ajst-24888	32	17	groups	group	NOUN
ajst-24888	32	18	of	of	ADP
ajst-24888	32	19	logging	log	VERB
ajst-24888	32	20	data	datum	NOUN
ajst-24888	32	21	in	in	ADP
ajst-24888	32	22	the	the	DET
ajst-24888	32	23	study	study	NOUN
ajst-24888	32	24	of	of	ADP
ajst-24888	32	25	lithology	lithology	NOUN
ajst-24888	32	26	identification	identification	NOUN
ajst-24888	32	27	of	of	ADP
ajst-24888	32	28	complex	complex	ADJ
ajst-24888	32	29	carbonate	carbonate	NOUN
ajst-24888	32	30	rocks	rock	NOUN
ajst-24888	32	31	.	.	PUNCT
ajst-24888	33	1	studies	study	NOUN
ajst-24888	33	2	have	have	AUX
ajst-24888	33	3	shown	show	VERB
ajst-24888	33	4	that	that	SCONJ
ajst-24888	33	5	random	random	ADJ
ajst-24888	33	6	forests	forest	NOUN
ajst-24888	33	7	are	be	AUX
ajst-24888	33	8	excellent	excellent	ADJ
ajst-24888	33	9	at	at	ADP
ajst-24888	33	10	handling	handle	VERB
ajst-24888	33	11	noise	noise	NOUN
ajst-24888	33	12	and	and	CCONJ
ajst-24888	33	13	outliers	outlier	NOUN
ajst-24888	33	14	in	in	ADP
ajst-24888	33	15	data	datum	NOUN
ajst-24888	33	16	and	and	CCONJ
ajst-24888	33	17	have	have	VERB
ajst-24888	33	18	high	high	ADJ
ajst-24888	33	19	robustness	robustness	NOUN
ajst-24888	33	20	.	.	PUNCT
ajst-24888	34	1	finally	finally	ADV
ajst-24888	34	2	,	,	PUNCT
ajst-24888	34	3	the	the	DET
ajst-24888	34	4	identification	identification	NOUN
ajst-24888	34	5	accuracy	accuracy	NOUN
ajst-24888	34	6	of	of	ADP
ajst-24888	34	7	the	the	DET
ajst-24888	34	8	model	model	NOUN
ajst-24888	34	9	reaches	reach	VERB
ajst-24888	34	10	more	more	ADJ
ajst-24888	34	11	than	than	ADP
ajst-24888	34	12	90	90	NUM
ajst-24888	34	13	%	%	NOUN
ajst-24888	34	14	,	,	PUNCT
ajst-24888	34	15	which	which	PRON
ajst-24888	34	16	significantly	significantly	ADV
ajst-24888	34	17	improves	improve	VERB
ajst-24888	34	18	the	the	DET
ajst-24888	34	19	reliability	reliability	NOUN
ajst-24888	34	20	of	of	ADP
ajst-24888	34	21	lithology	lithology	NOUN
ajst-24888	34	22	identification	identification	NOUN
ajst-24888	34	23	.	.	PUNCT
ajst-24888	35	1	chen	chen	PROPN
ajst-24888	35	2	weicheng	weicheng	PROPN
ajst-24888	36	1	[	[	X
ajst-24888	36	2	8	8	NUM
ajst-24888	36	3	]	]	PUNCT
ajst-24888	36	4	uses	use	VERB
ajst-24888	36	5	artificial	artificial	ADJ
ajst-24888	36	6	neural	neural	ADJ
ajst-24888	36	7	network	network	NOUN
ajst-24888	36	8	to	to	PART
ajst-24888	36	9	identify	identify	VERB
ajst-24888	36	10	lithology	lithology	NOUN
ajst-24888	36	11	of	of	ADP
ajst-24888	36	12	logging	log	VERB
ajst-24888	36	13	data	datum	NOUN
ajst-24888	36	14	of	of	ADP
ajst-24888	36	15	sandstone	sandstone	NOUN
ajst-24888	36	16	type	type	NOUN
ajst-24888	36	17	uranium	uranium	NOUN
ajst-24888	36	18	mine	mine	NOUN
ajst-24888	36	19	,	,	PUNCT
ajst-24888	36	20	and	and	CCONJ
ajst-24888	36	21	computates	computate	VERB
ajst-24888	36	22	the	the	DET
ajst-24888	36	23	number	number	NOUN
ajst-24888	36	24	of	of	ADP
ajst-24888	36	25	hidden	hide	VERB
ajst-24888	36	26	layer	layer	NOUN
ajst-24888	36	27	neurons	neuron	NOUN
ajst-24888	36	28	through	through	ADP
ajst-24888	36	29	two	two	NUM
ajst-24888	36	30	ways	way	NOUN
ajst-24888	36	31	.	.	PUNCT
ajst-24888	37	1	gridsearchcv	gridsearchcv	NOUN
ajst-24888	37	2	is	be	AUX
ajst-24888	37	3	used	use	VERB
ajst-24888	37	4	to	to	PART
ajst-24888	37	5	optimize	optimize	VERB
ajst-24888	37	6	the	the	DET
ajst-24888	37	7	number	number	NOUN
ajst-24888	37	8	of	of	ADP
ajst-24888	37	9	hidden	hide	VERB
ajst-24888	37	10	layer	layer	NOUN
ajst-24888	37	11	neurons	neuron	NOUN
ajst-24888	37	12	and	and	CCONJ
ajst-24888	37	13	the	the	DET
ajst-24888	37	14	learning	learning	NOUN
ajst-24888	37	15	rate	rate	NOUN
ajst-24888	37	16	.	.	PUNCT
ajst-24888	38	1	by	by	ADP
ajst-24888	38	2	identifying	identify	VERB
ajst-24888	38	3	the	the	DET
ajst-24888	38	4	actual	actual	ADJ
ajst-24888	38	5	data	datum	NOUN
ajst-24888	38	6	,	,	PUNCT
ajst-24888	38	7	the	the	DET
ajst-24888	38	8	model	model	NOUN
ajst-24888	38	9	can	can	AUX
ajst-24888	38	10	reach	reach	VERB
ajst-24888	38	11	convergence	convergence	NOUN
ajst-24888	38	12	within	within	ADP
ajst-24888	38	13	200	200	NUM
ajst-24888	38	14	iterations	iteration	NOUN
ajst-24888	38	15	.	.	PUNCT
ajst-24888	39	1	the	the	DET
ajst-24888	39	2	results	result	NOUN
ajst-24888	39	3	of	of	ADP
ajst-24888	39	4	confusion	confusion	NOUN
ajst-24888	39	5	matrix	matrix	NOUN
ajst-24888	39	6	show	show	VERB
ajst-24888	39	7	that	that	SCONJ
ajst-24888	39	8	the	the	DET
ajst-24888	39	9	recognition	recognition	NOUN
ajst-24888	39	10	accuracy	accuracy	NOUN
ajst-24888	39	11	of	of	ADP
ajst-24888	39	12	permeable	permeable	ADJ
ajst-24888	39	13	sandstone	sandstone	NOUN
ajst-24888	39	14	is	be	AUX
ajst-24888	39	15	80	80	NUM
ajst-24888	39	16	%	%	NOUN
ajst-24888	39	17	,	,	PUNCT
ajst-24888	39	18	and	and	CCONJ
ajst-24888	39	19	the	the	DET
ajst-24888	39	20	recognition	recognition	NOUN
ajst-24888	39	21	accuracy	accuracy	NOUN
ajst-24888	39	22	of	of	ADP
ajst-24888	39	23	impermeable	impermeable	ADJ
ajst-24888	39	24	siltstone	siltstone	NOUN
ajst-24888	39	25	and	and	CCONJ
ajst-24888	39	26	muddy	muddy	ADJ
ajst-24888	39	27	siltstone	siltstone	NOUN
ajst-24888	39	28	is	be	AUX
ajst-24888	39	29	60	60	NUM
ajst-24888	39	30	%	%	NOUN
ajst-24888	39	31	.	.	PUNCT
ajst-24888	40	1	zhou	zhou	PROPN
ajst-24888	40	2	yuankai	yuankai	PROPN
ajst-24888	41	1	[	[	X
ajst-24888	41	2	9	9	NUM
ajst-24888	41	3	]	]	PUNCT
ajst-24888	41	4	et	et	PROPN
ajst-24888	41	5	al	al	PROPN
ajst-24888	41	6	.	.	PROPN
ajst-24888	41	7	discussed	discuss	VERB
ajst-24888	41	8	the	the	DET
ajst-24888	41	9	application	application	NOUN
ajst-24888	41	10	of	of	ADP
ajst-24888	41	11	deep	deep	ADJ
ajst-24888	41	12	neural	neural	ADJ
ajst-24888	41	13	network	network	NOUN
ajst-24888	41	14	model	model	NOUN
ajst-24888	41	15	in	in	ADP
ajst-24888	41	16	lithology	lithology	NOUN
ajst-24888	41	17	classification	classification	NOUN
ajst-24888	41	18	of	of	ADP
ajst-24888	41	19	uranium	uranium	NOUN
ajst-24888	41	20	logging	log	VERB
ajst-24888	41	21	122	122	NUM
ajst-24888	41	22	interpretation	interpretation	NOUN
ajst-24888	41	23	in	in	ADP
ajst-24888	41	24	the	the	DET
ajst-24888	41	25	nalinggou	nalinggou	NOUN
ajst-24888	41	26	area	area	NOUN
ajst-24888	41	27	,	,	PUNCT
ajst-24888	41	28	alleviated	alleviate	VERB
ajst-24888	41	29	the	the	DET
ajst-24888	41	30	impact	impact	NOUN
ajst-24888	41	31	of	of	ADP
ajst-24888	41	32	class	class	NOUN
ajst-24888	41	33	imbalance	imbalance	NOUN
ajst-24888	41	34	on	on	ADP
ajst-24888	41	35	classification	classification	NOUN
ajst-24888	41	36	results	result	NOUN
ajst-24888	41	37	by	by	ADP
ajst-24888	41	38	using	use	VERB
ajst-24888	41	39	models	model	NOUN
ajst-24888	41	40	with	with	ADP
ajst-24888	41	41	different	different	ADJ
ajst-24888	41	42	structures	structure	NOUN
ajst-24888	41	43	,	,	PUNCT
ajst-24888	41	44	analyzed	analyze	VERB
ajst-24888	41	45	the	the	DET
ajst-24888	41	46	hierarchical	hierarchical	ADJ
ajst-24888	41	47	structure	structure	NOUN
ajst-24888	41	48	and	and	CCONJ
ajst-24888	41	49	training	training	NOUN
ajst-24888	41	50	process	process	NOUN
ajst-24888	41	51	of	of	ADP
ajst-24888	41	52	the	the	DET
ajst-24888	41	53	model	model	NOUN
ajst-24888	41	54	,	,	PUNCT
ajst-24888	41	55	and	and	CCONJ
ajst-24888	41	56	explained	explain	VERB
ajst-24888	41	57	the	the	DET
ajst-24888	41	58	internal	internal	ADJ
ajst-24888	41	59	mechanism	mechanism	NOUN
ajst-24888	41	60	and	and	CCONJ
ajst-24888	41	61	decision	decision	NOUN
ajst-24888	41	62	logic	logic	NOUN
ajst-24888	41	63	of	of	ADP
ajst-24888	41	64	the	the	DET
ajst-24888	41	65	model	model	NOUN
ajst-24888	41	66	in	in	ADP
ajst-24888	41	67	a	a	DET
ajst-24888	41	68	more	more	ADV
ajst-24888	41	69	comprehensive	comprehensive	ADJ
ajst-24888	41	70	way	way	NOUN
ajst-24888	41	71	.	.	PUNCT
ajst-24888	42	1	the	the	DET
ajst-24888	42	2	results	result	NOUN
ajst-24888	42	3	show	show	VERB
ajst-24888	42	4	that	that	SCONJ
ajst-24888	42	5	the	the	DET
ajst-24888	42	6	recognition	recognition	NOUN
ajst-24888	42	7	accuracy	accuracy	NOUN
ajst-24888	42	8	of	of	ADP
ajst-24888	42	9	long	long	ADJ
ajst-24888	42	10	and	and	CCONJ
ajst-24888	42	11	short	short	ADJ
ajst-24888	42	12	time	time	NOUN
ajst-24888	42	13	memory	memory	NOUN
ajst-24888	42	14	network	network	NOUN
ajst-24888	42	15	is	be	AUX
ajst-24888	42	16	higher	high	ADJ
ajst-24888	42	17	than	than	ADP
ajst-24888	42	18	80	80	NUM
ajst-24888	42	19	%	%	NOUN
ajst-24888	42	20	while	while	SCONJ
ajst-24888	42	21	maintaining	maintain	VERB
ajst-24888	42	22	high	high	ADJ
ajst-24888	42	23	training	training	NOUN
ajst-24888	42	24	efficiency	efficiency	NOUN
ajst-24888	42	25	,	,	PUNCT
ajst-24888	42	26	and	and	CCONJ
ajst-24888	42	27	the	the	DET
ajst-24888	42	28	accuracy	accuracy	NOUN
ajst-24888	42	29	of	of	ADP
ajst-24888	42	30	8	8	NUM
ajst-24888	42	31	-	-	PUNCT
ajst-24888	42	32	layer	layer	NOUN
ajst-24888	42	33	fully	fully	ADV
ajst-24888	42	34	connected	connect	VERB
ajst-24888	42	35	network	network	NOUN
ajst-24888	42	36	is	be	AUX
ajst-24888	42	37	higher	high	ADJ
ajst-24888	42	38	than	than	ADP
ajst-24888	42	39	90	90	NUM
ajst-24888	42	40	%	%	NOUN
ajst-24888	42	41	.	.	PUNCT
ajst-24888	43	1	gao	gao	PROPN
ajst-24888	43	2	jiatian	jiatian	PROPN
ajst-24888	44	1	[	[	X
ajst-24888	44	2	10	10	NUM
ajst-24888	44	3	]	]	PUNCT
ajst-24888	44	4	et	et	PROPN
ajst-24888	44	5	al	al	PROPN
ajst-24888	44	6	.	.	PROPN
ajst-24888	44	7	,	,	PUNCT
ajst-24888	44	8	using	use	VERB
ajst-24888	44	9	the	the	DET
ajst-24888	44	10	well	well	ADV
ajst-24888	44	11	logging	log	VERB
ajst-24888	44	12	data	datum	NOUN
ajst-24888	44	13	of	of	ADP
ajst-24888	44	14	several	several	ADJ
ajst-24888	44	15	wells	well	NOUN
ajst-24888	44	16	in	in	ADP
ajst-24888	44	17	the	the	DET
ajst-24888	44	18	songliao	songliao	NOUN
ajst-24888	44	19	basin	basin	NOUN
ajst-24888	44	20	to	to	PART
ajst-24888	44	21	conduct	conduct	VERB
ajst-24888	44	22	model	model	NOUN
ajst-24888	44	23	research	research	NOUN
ajst-24888	44	24	,	,	PUNCT
ajst-24888	44	25	proposed	propose	VERB
ajst-24888	44	26	a	a	DET
ajst-24888	44	27	lithology	lithology	NOUN
ajst-24888	44	28	identification	identification	NOUN
ajst-24888	44	29	method	method	NOUN
ajst-24888	44	30	based	base	VERB
ajst-24888	44	31	on	on	ADP
ajst-24888	44	32	pso	pso	NOUN
ajst-24888	44	33	-	-	PUNCT
ajst-24888	44	34	bp	bp	PROPN
ajst-24888	44	35	.	.	PUNCT
ajst-24888	45	1	the	the	DET
ajst-24888	45	2	lithology	lithology	NOUN
ajst-24888	45	3	identification	identification	NOUN
ajst-24888	45	4	method	method	NOUN
ajst-24888	45	5	based	base	VERB
ajst-24888	45	6	on	on	ADP
ajst-24888	45	7	pso	pso	NOUN
ajst-24888	45	8	-	-	PUNCT
ajst-24888	45	9	bp	bp	PROPN
ajst-24888	45	10	is	be	AUX
ajst-24888	45	11	realized	realize	VERB
ajst-24888	45	12	through	through	ADP
ajst-24888	45	13	data	data	NOUN
ajst-24888	45	14	preprocessing	preprocessing	NOUN
ajst-24888	45	15	of	of	ADP
ajst-24888	45	16	log	log	NOUN
ajst-24888	45	17	source	source	NOUN
ajst-24888	45	18	data	datum	NOUN
ajst-24888	45	19	,	,	PUNCT
ajst-24888	45	20	constructing	construct	VERB
ajst-24888	45	21	network	network	NOUN
ajst-24888	45	22	identification	identification	NOUN
ajst-24888	45	23	model	model	NOUN
ajst-24888	45	24	,	,	PUNCT
ajst-24888	45	25	optimizing	optimize	VERB
ajst-24888	45	26	lithology	lithology	NOUN
ajst-24888	45	27	identification	identification	NOUN
ajst-24888	45	28	model	model	NOUN
ajst-24888	45	29	and	and	CCONJ
ajst-24888	45	30	evaluating	evaluate	VERB
ajst-24888	45	31	the	the	DET
ajst-24888	45	32	output	output	NOUN
ajst-24888	45	33	result	result	NOUN
ajst-24888	45	34	of	of	ADP
ajst-24888	45	35	the	the	DET
ajst-24888	45	36	model	model	NOUN
ajst-24888	45	37	.	.	PUNCT
ajst-24888	46	1	after	after	ADP
ajst-24888	46	2	repeated	repeat	VERB
ajst-24888	46	3	tests	test	NOUN
ajst-24888	46	4	,	,	PUNCT
ajst-24888	46	5	the	the	DET
ajst-24888	46	6	results	result	NOUN
ajst-24888	46	7	show	show	VERB
ajst-24888	46	8	that	that	SCONJ
ajst-24888	46	9	the	the	DET
ajst-24888	46	10	average	average	ADJ
ajst-24888	46	11	accuracy	accuracy	NOUN
ajst-24888	46	12	of	of	ADP
ajst-24888	46	13	lithology	lithology	NOUN
ajst-24888	46	14	identification	identification	NOUN
ajst-24888	46	15	using	use	VERB
ajst-24888	46	16	pso	pso	NOUN
ajst-24888	46	17	-	-	PUNCT
ajst-24888	46	18	bp	bp	PROPN
ajst-24888	46	19	method	method	NOUN
ajst-24888	46	20	can	can	AUX
ajst-24888	46	21	reach	reach	VERB
ajst-24888	46	22	92.2	92.2	NUM
ajst-24888	46	23	%	%	NOUN
ajst-24888	46	24	,	,	PUNCT
ajst-24888	46	25	which	which	PRON
ajst-24888	46	26	provides	provide	VERB
ajst-24888	46	27	reliable	reliable	ADJ
ajst-24888	46	28	support	support	NOUN
ajst-24888	46	29	for	for	ADP
ajst-24888	46	30	reservoir	reservoir	NOUN
ajst-24888	46	31	prediction	prediction	NOUN
ajst-24888	46	32	.	.	PUNCT
ajst-24888	47	1	zhao	zhao	NOUN
ajst-24888	47	2	ranlei	ranlei	NOUN
ajst-24888	48	1	[	[	X
ajst-24888	48	2	11	11	NUM
ajst-24888	48	3	]	]	PUNCT
ajst-24888	48	4	et	et	PROPN
ajst-24888	48	5	al	al	PROPN
ajst-24888	48	6	.	.	PROPN
ajst-24888	48	7	used	use	VERB
ajst-24888	48	8	principal	principal	ADJ
ajst-24888	48	9	component	component	NOUN
ajst-24888	48	10	analysis	analysis	NOUN
ajst-24888	48	11	to	to	PART
ajst-24888	48	12	screen	screen	VERB
ajst-24888	48	13	out	out	ADP
ajst-24888	48	14	four	four	NUM
ajst-24888	48	15	characteristic	characteristic	ADJ
ajst-24888	48	16	logging	log	VERB
ajst-24888	48	17	curves	curve	NOUN
ajst-24888	48	18	sensitive	sensitive	ADJ
ajst-24888	48	19	to	to	ADP
ajst-24888	48	20	volcanic	volcanic	ADJ
ajst-24888	48	21	lithology	lithology	NOUN
ajst-24888	48	22	identification	identification	NOUN
ajst-24888	48	23	as	as	ADP
ajst-24888	48	24	input	input	NOUN
ajst-24888	48	25	,	,	PUNCT
ajst-24888	48	26	and	and	CCONJ
ajst-24888	48	27	used	use	VERB
ajst-24888	48	28	xgboost	xgboost	PROPN
ajst-24888	48	29	algorithm	algorithm	NOUN
ajst-24888	48	30	to	to	PART
ajst-24888	48	31	build	build	VERB
ajst-24888	48	32	a	a	DET
ajst-24888	48	33	lithology	lithology	NOUN
ajst-24888	48	34	identification	identification	NOUN
ajst-24888	48	35	model	model	NOUN
ajst-24888	48	36	for	for	ADP
ajst-24888	48	37	volcanic	volcanic	ADJ
ajst-24888	48	38	lithology	lithology	NOUN
ajst-24888	48	39	identification	identification	NOUN
ajst-24888	48	40	.	.	PUNCT
ajst-24888	49	1	after	after	SCONJ
ajst-24888	49	2	the	the	DET
ajst-24888	49	3	lithology	lithology	NOUN
ajst-24888	49	4	identification	identification	NOUN
ajst-24888	49	5	results	result	NOUN
ajst-24888	49	6	were	be	AUX
ajst-24888	49	7	given	give	VERB
ajst-24888	49	8	by	by	ADP
ajst-24888	49	9	the	the	DET
ajst-24888	49	10	model	model	NOUN
ajst-24888	49	11	,	,	PUNCT
ajst-24888	49	12	the	the	DET
ajst-24888	49	13	results	result	NOUN
ajst-24888	49	14	showed	show	VERB
ajst-24888	49	15	that	that	SCONJ
ajst-24888	49	16	the	the	DET
ajst-24888	49	17	accuracy	accuracy	NOUN
ajst-24888	49	18	rate	rate	NOUN
ajst-24888	49	19	of	of	ADP
ajst-24888	49	20	xgboost	xgboost	ADJ
ajst-24888	49	21	algorithm	algorithm	NOUN
ajst-24888	49	22	in	in	ADP
ajst-24888	49	23	blind	blind	ADJ
ajst-24888	49	24	well	well	NOUN
ajst-24888	49	25	section	section	NOUN
ajst-24888	49	26	identification	identification	NOUN
ajst-24888	49	27	reached	reach	VERB
ajst-24888	49	28	96.13	96.13	NUM
ajst-24888	49	29	%	%	NOUN
ajst-24888	49	30	.	.	PUNCT
ajst-24888	50	1	chen	chen	PROPN
ajst-24888	50	2	ganghua	ganghua	PROPN
ajst-24888	51	1	[	[	X
ajst-24888	51	2	12	12	NUM
ajst-24888	51	3	]	]	PUNCT
ajst-24888	51	4	et	et	PROPN
ajst-24888	51	5	al	al	PROPN
ajst-24888	51	6	.	.	PROPN
ajst-24888	51	7	,	,	PUNCT
ajst-24888	51	8	aiming	aim	VERB
ajst-24888	51	9	at	at	ADP
ajst-24888	51	10	the	the	DET
ajst-24888	51	11	characteristics	characteristic	NOUN
ajst-24888	51	12	of	of	ADP
ajst-24888	51	13	longitudinal	longitudinal	ADJ
ajst-24888	51	14	sequential	sequential	ADJ
ajst-24888	51	15	logging	log	VERB
ajst-24888	51	16	data	datum	NOUN
ajst-24888	51	17	,	,	PUNCT
ajst-24888	51	18	constructed	construct	VERB
ajst-24888	51	19	a	a	DET
ajst-24888	51	20	bidirectional	bidirectional	ADJ
ajst-24888	51	21	short	short	ADJ
ajst-24888	51	22	-	-	PUNCT
ajst-24888	51	23	short	short	ADJ
ajst-24888	51	24	-	-	PUNCT
ajst-24888	51	25	memory	memory	NOUN
ajst-24888	51	26	neural	neural	ADJ
ajst-24888	51	27	network	network	NOUN
ajst-24888	51	28	(	(	PUNCT
ajst-24888	51	29	bilstm	bilstm	NOUN
ajst-24888	51	30	)	)	PUNCT
ajst-24888	51	31	lithography	lithography	NOUN
ajst-24888	51	32	identification	identification	NOUN
ajst-24888	51	33	model	model	NOUN
ajst-24888	51	34	,	,	PUNCT
ajst-24888	51	35	adopted	adopt	VERB
ajst-24888	51	36	random	random	ADJ
ajst-24888	51	37	forest	forest	NOUN
ajst-24888	51	38	method	method	NOUN
ajst-24888	51	39	to	to	PART
ajst-24888	51	40	select	select	VERB
ajst-24888	51	41	features	feature	NOUN
ajst-24888	51	42	of	of	ADP
ajst-24888	51	43	conventional	conventional	ADJ
ajst-24888	51	44	logging	logging	NOUN
ajst-24888	51	45	data	datum	NOUN
ajst-24888	51	46	and	and	CCONJ
ajst-24888	51	47	other	other	ADJ
ajst-24888	51	48	parameters	parameter	NOUN
ajst-24888	51	49	,	,	PUNCT
ajst-24888	51	50	and	and	CCONJ
ajst-24888	51	51	trained	train	VERB
ajst-24888	51	52	bilstm	bilstm	NOUN
ajst-24888	51	53	model	model	NOUN
ajst-24888	51	54	with	with	ADP
ajst-24888	51	55	selected	select	VERB
ajst-24888	51	56	parameters	parameter	NOUN
ajst-24888	51	57	as	as	ADP
ajst-24888	51	58	input	input	NOUN
ajst-24888	51	59	variables	variable	NOUN
ajst-24888	51	60	.	.	PUNCT
ajst-24888	52	1	the	the	DET
ajst-24888	52	2	results	result	NOUN
ajst-24888	52	3	show	show	VERB
ajst-24888	52	4	that	that	SCONJ
ajst-24888	52	5	the	the	DET
ajst-24888	52	6	lithology	lithology	NOUN
ajst-24888	52	7	identification	identification	NOUN
ajst-24888	52	8	accuracy	accuracy	NOUN
ajst-24888	52	9	of	of	ADP
ajst-24888	52	10	the	the	DET
ajst-24888	52	11	bilstm	bilstm	NOUN
ajst-24888	52	12	model	model	NOUN
ajst-24888	52	13	is	be	AUX
ajst-24888	52	14	0.86	0.86	NUM
ajst-24888	52	15	,	,	PUNCT
ajst-24888	52	16	which	which	PRON
ajst-24888	52	17	proves	prove	VERB
ajst-24888	52	18	that	that	SCONJ
ajst-24888	52	19	the	the	DET
ajst-24888	52	20	bilstm	bilstm	NOUN
ajst-24888	52	21	model	model	NOUN
ajst-24888	52	22	is	be	AUX
ajst-24888	52	23	suitable	suitable	ADJ
ajst-24888	52	24	for	for	ADP
ajst-24888	52	25	the	the	DET
ajst-24888	52	26	lithology	lithology	NOUN
ajst-24888	52	27	identification	identification	NOUN
ajst-24888	52	28	of	of	ADP
ajst-24888	52	29	beach	beach	NOUN
ajst-24888	52	30	bar	bar	NOUN
ajst-24888	52	31	sand	sand	NOUN
ajst-24888	52	32	reservoir	reservoir	NOUN
ajst-24888	52	33	.	.	PUNCT
ajst-24888	53	1	the	the	DET
ajst-24888	53	2	application	application	NOUN
ajst-24888	53	3	of	of	ADP
ajst-24888	53	4	machine	machine	NOUN
ajst-24888	53	5	learning	learning	NOUN
ajst-24888	53	6	in	in	ADP
ajst-24888	53	7	lithology	lithology	NOUN
ajst-24888	53	8	identification	identification	NOUN
ajst-24888	53	9	has	have	AUX
ajst-24888	53	10	achieved	achieve	VERB
ajst-24888	53	11	remarkable	remarkable	ADJ
ajst-24888	53	12	results	result	NOUN
ajst-24888	53	13	,	,	PUNCT
ajst-24888	53	14	and	and	CCONJ
ajst-24888	53	15	each	each	DET
ajst-24888	53	16	method	method	NOUN
ajst-24888	53	17	has	have	VERB
ajst-24888	53	18	its	its	PRON
ajst-24888	53	19	advantages	advantage	NOUN
ajst-24888	53	20	and	and	CCONJ
ajst-24888	53	21	disadvantages	disadvantage	NOUN
ajst-24888	53	22	.	.	PUNCT
ajst-24888	54	1	support	support	NOUN
ajst-24888	54	2	vector	vector	NOUN
ajst-24888	54	3	machines	machine	NOUN
ajst-24888	54	4	(	(	PUNCT
ajst-24888	54	5	svm	svm	PROPN
ajst-24888	54	6	)	)	PUNCT
ajst-24888	54	7	and	and	CCONJ
ajst-24888	54	8	random	random	ADJ
ajst-24888	54	9	forests	forest	NOUN
ajst-24888	54	10	(	(	PUNCT
ajst-24888	54	11	rf	rf	NOUN
ajst-24888	54	12	)	)	PUNCT
ajst-24888	54	13	perform	perform	VERB
ajst-24888	54	14	well	well	ADV
ajst-24888	54	15	in	in	ADP
ajst-24888	54	16	handling	handle	VERB
ajst-24888	54	17	high	high	ADJ
ajst-24888	54	18	and	and	CCONJ
ajst-24888	54	19	noisy	noisy	ADJ
ajst-24888	54	20	data	datum	NOUN
ajst-24888	54	21	.	.	PUNCT
ajst-24888	55	1	convolutional	convolutional	ADJ
ajst-24888	55	2	neural	neural	ADJ
ajst-24888	55	3	network	network	NOUN
ajst-24888	55	4	(	(	PUNCT
ajst-24888	55	5	cnn	cnn	PROPN
ajst-24888	55	6	)	)	PUNCT
ajst-24888	55	7	has	have	VERB
ajst-24888	55	8	advantages	advantage	NOUN
ajst-24888	55	9	in	in	ADP
ajst-24888	55	10	extracting	extract	VERB
ajst-24888	55	11	complex	complex	ADJ
ajst-24888	55	12	features	feature	NOUN
ajst-24888	55	13	and	and	CCONJ
ajst-24888	55	14	processing	process	VERB
ajst-24888	55	15	3d	3d	NUM
ajst-24888	55	16	data	datum	NOUN
ajst-24888	55	17	.	.	PUNCT
ajst-24888	56	1	(	(	PUNCT
ajst-24888	56	2	xgboost	xgboost	X
ajst-24888	56	3	)	)	PUNCT
ajst-24888	56	4	has	have	VERB
ajst-24888	56	5	significant	significant	ADJ
ajst-24888	56	6	advantages	advantage	NOUN
ajst-24888	56	7	in	in	ADP
ajst-24888	56	8	handling	handle	VERB
ajst-24888	56	9	large	large	ADJ
ajst-24888	56	10	-	-	PUNCT
ajst-24888	56	11	scale	scale	NOUN
ajst-24888	56	12	data	datum	NOUN
ajst-24888	56	13	and	and	CCONJ
ajst-24888	56	14	improving	improve	VERB
ajst-24888	56	15	predictive	predictive	ADJ
ajst-24888	56	16	performance	performance	NOUN
ajst-24888	56	17	;	;	PUNCT
ajst-24888	56	18	long	long	ADJ
ajst-24888	56	19	short	short	ADJ
ajst-24888	56	20	-	-	PUNCT
ajst-24888	56	21	term	term	NOUN
ajst-24888	56	22	memory	memory	NOUN
ajst-24888	56	23	network	network	NOUN
ajst-24888	56	24	(	(	PUNCT
ajst-24888	56	25	lstm	lstm	PROPN
ajst-24888	56	26	)	)	PUNCT
ajst-24888	56	27	is	be	AUX
ajst-24888	56	28	outstanding	outstanding	ADJ
ajst-24888	56	29	in	in	ADP
ajst-24888	56	30	capturing	capture	VERB
ajst-24888	56	31	the	the	DET
ajst-24888	56	32	features	feature	NOUN
ajst-24888	56	33	of	of	ADP
ajst-24888	56	34	time	time	NOUN
ajst-24888	56	35	series	series	NOUN
ajst-24888	56	36	.	.	PUNCT
ajst-24888	57	1	overall	overall	ADV
ajst-24888	57	2	,	,	PUNCT
ajst-24888	57	3	the	the	DET
ajst-24888	57	4	machine	machine	NOUN
ajst-24888	57	5	learning	learning	NOUN
ajst-24888	57	6	method	method	NOUN
ajst-24888	57	7	has	have	AUX
ajst-24888	57	8	demonstrated	demonstrate	VERB
ajst-24888	57	9	its	its	PRON
ajst-24888	57	10	strong	strong	ADJ
ajst-24888	57	11	adaptability	adaptability	NOUN
ajst-24888	57	12	and	and	CCONJ
ajst-24888	57	13	accuracy	accuracy	NOUN
ajst-24888	57	14	in	in	ADP
ajst-24888	57	15	lithology	lithology	NOUN
ajst-24888	57	16	identification	identification	NOUN
ajst-24888	57	17	.	.	PUNCT
ajst-24888	58	1	in	in	ADP
ajst-24888	58	2	the	the	DET
ajst-24888	58	3	future	future	NOUN
ajst-24888	58	4	,	,	PUNCT
ajst-24888	58	5	by	by	ADP
ajst-24888	58	6	combining	combine	VERB
ajst-24888	58	7	multiple	multiple	ADJ
ajst-24888	58	8	machine	machine	NOUN
ajst-24888	58	9	learning	learning	NOUN
ajst-24888	58	10	methods	method	NOUN
ajst-24888	58	11	and	and	CCONJ
ajst-24888	58	12	interdisciplinary	interdisciplinary	ADJ
ajst-24888	58	13	cooperation	cooperation	NOUN
ajst-24888	58	14	to	to	PART
ajst-24888	58	15	further	far	ADV
ajst-24888	58	16	improve	improve	VERB
ajst-24888	58	17	the	the	DET
ajst-24888	58	18	performance	performance	NOUN
ajst-24888	58	19	and	and	CCONJ
ajst-24888	58	20	interpretation	interpretation	NOUN
ajst-24888	58	21	of	of	ADP
ajst-24888	58	22	the	the	DET
ajst-24888	58	23	model	model	NOUN
ajst-24888	58	24	,	,	PUNCT
ajst-24888	58	25	it	it	PRON
ajst-24888	58	26	will	will	AUX
ajst-24888	58	27	promote	promote	VERB
ajst-24888	58	28	the	the	DET
ajst-24888	58	29	development	development	NOUN
ajst-24888	58	30	of	of	ADP
ajst-24888	58	31	lithology	lithology	NOUN
ajst-24888	58	32	identification	identification	NOUN
ajst-24888	58	33	technology	technology	NOUN
ajst-24888	58	34	,	,	PUNCT
ajst-24888	58	35	and	and	CCONJ
ajst-24888	58	36	provide	provide	VERB
ajst-24888	58	37	more	more	ADJ
ajst-24888	58	38	powerful	powerful	ADJ
ajst-24888	58	39	tools	tool	NOUN
ajst-24888	58	40	and	and	CCONJ
ajst-24888	58	41	methods	method	NOUN
ajst-24888	58	42	for	for	ADP
ajst-24888	58	43	geological	geological	ADJ
ajst-24888	58	44	research	research	NOUN
ajst-24888	58	45	and	and	CCONJ
ajst-24888	58	46	resource	resource	NOUN
ajst-24888	58	47	exploration	exploration	NOUN
ajst-24888	58	48	.	.	PUNCT
ajst-24888	59	1	3	3	X
ajst-24888	59	2	.	.	X
ajst-24888	59	3	classification	classification	NOUN
ajst-24888	59	4	of	of	ADP
ajst-24888	59	5	machine	machine	NOUN
ajst-24888	59	6	learning	learn	VERB
ajst-24888	59	7	methods	method	NOUN
ajst-24888	59	8	in	in	ADP
ajst-24888	59	9	lithology	lithology	NOUN
ajst-24888	59	10	identification	identification	NOUN
ajst-24888	59	11	,	,	PUNCT
ajst-24888	59	12	machine	machine	NOUN
ajst-24888	59	13	learning	learning	NOUN
ajst-24888	59	14	methods	method	NOUN
ajst-24888	59	15	can	can	AUX
ajst-24888	59	16	be	be	AUX
ajst-24888	59	17	divided	divide	VERB
ajst-24888	59	18	into	into	ADP
ajst-24888	59	19	supervised	supervised	ADJ
ajst-24888	59	20	learning	learning	NOUN
ajst-24888	59	21	,	,	PUNCT
ajst-24888	59	22	unsupervised	unsupervised	ADJ
ajst-24888	59	23	learning	learning	NOUN
ajst-24888	59	24	,	,	PUNCT
ajst-24888	59	25	semi	semi	ADJ
ajst-24888	59	26	-	-	ADJ
ajst-24888	59	27	supervised	supervised	ADJ
ajst-24888	59	28	learning	learning	NOUN
ajst-24888	59	29	and	and	CCONJ
ajst-24888	59	30	deep	deep	ADJ
ajst-24888	59	31	learning	learning	NOUN
ajst-24888	59	32	according	accord	VERB
ajst-24888	59	33	to	to	ADP
ajst-24888	59	34	their	their	PRON
ajst-24888	59	35	learning	learning	NOUN
ajst-24888	59	36	styles	style	NOUN
ajst-24888	59	37	and	and	CCONJ
ajst-24888	59	38	application	application	NOUN
ajst-24888	59	39	scenarios	scenario	NOUN
ajst-24888	59	40	.	.	PUNCT
ajst-24888	60	1	each	each	PRON
ajst-24888	60	2	of	of	ADP
ajst-24888	60	3	these	these	DET
ajst-24888	60	4	approaches	approach	NOUN
ajst-24888	60	5	has	have	VERB
ajst-24888	60	6	advantages	advantage	NOUN
ajst-24888	60	7	and	and	CCONJ
ajst-24888	60	8	disadvantages	disadvantage	NOUN
ajst-24888	60	9	,	,	PUNCT
ajst-24888	60	10	and	and	CCONJ
ajst-24888	60	11	is	be	AUX
ajst-24888	60	12	suitable	suitable	ADJ
ajst-24888	60	13	for	for	ADP
ajst-24888	60	14	different	different	ADJ
ajst-24888	60	15	data	datum	NOUN
ajst-24888	60	16	types	type	NOUN
ajst-24888	60	17	and	and	CCONJ
ajst-24888	60	18	task	task	NOUN
ajst-24888	60	19	requirements	requirement	NOUN
ajst-24888	60	20	.	.	PUNCT
ajst-24888	61	1	each	each	DET
ajst-24888	61	2	method	method	NOUN
ajst-24888	61	3	and	and	CCONJ
ajst-24888	61	4	its	its	PRON
ajst-24888	61	5	application	application	NOUN
ajst-24888	61	6	to	to	ADP
ajst-24888	61	7	lithology	lithology	NOUN
ajst-24888	61	8	identification	identification	NOUN
ajst-24888	61	9	are	be	AUX
ajst-24888	61	10	described	describe	VERB
ajst-24888	61	11	in	in	ADP
ajst-24888	61	12	detail	detail	NOUN
ajst-24888	61	13	below	below	ADV
ajst-24888	61	14	.	.	PUNCT
ajst-24888	62	1	3.1	3.1	NUM
ajst-24888	62	2	.	.	PUNCT
ajst-24888	62	3	supervised	supervised	ADJ
ajst-24888	62	4	learning	learn	VERB
ajst-24888	62	5	supervised	supervised	ADJ
ajst-24888	62	6	learning	learning	NOUN
ajst-24888	62	7	is	be	AUX
ajst-24888	62	8	a	a	DET
ajst-24888	62	9	method	method	NOUN
ajst-24888	62	10	of	of	ADP
ajst-24888	62	11	training	train	VERB
ajst-24888	62	12	a	a	DET
ajst-24888	62	13	model	model	NOUN
ajst-24888	62	14	with	with	ADP
ajst-24888	62	15	labeled	label	VERB
ajst-24888	62	16	data	datum	NOUN
ajst-24888	62	17	so	so	SCONJ
ajst-24888	62	18	that	that	SCONJ
ajst-24888	62	19	it	it	PRON
ajst-24888	62	20	can	can	AUX
ajst-24888	62	21	predict	predict	VERB
ajst-24888	62	22	the	the	DET
ajst-24888	62	23	output	output	NOUN
ajst-24888	62	24	based	base	VERB
ajst-24888	62	25	on	on	ADP
ajst-24888	62	26	the	the	DET
ajst-24888	62	27	input	input	NOUN
ajst-24888	62	28	data	datum	NOUN
ajst-24888	62	29	.	.	PUNCT
ajst-24888	63	1	in	in	ADP
ajst-24888	63	2	lithology	lithology	NOUN
ajst-24888	63	3	identification	identification	NOUN
ajst-24888	63	4	,	,	PUNCT
ajst-24888	63	5	supervised	supervised	ADJ
ajst-24888	63	6	learning	learning	NOUN
ajst-24888	63	7	is	be	AUX
ajst-24888	63	8	often	often	ADV
ajst-24888	63	9	used	use	VERB
ajst-24888	63	10	to	to	PART
ajst-24888	63	11	learn	learn	VERB
ajst-24888	63	12	from	from	ADP
ajst-24888	63	13	existing	exist	VERB
ajst-24888	63	14	lithology	lithology	NOUN
ajst-24888	63	15	label	label	NOUN
ajst-24888	63	16	data	datum	NOUN
ajst-24888	63	17	in	in	ADP
ajst-24888	63	18	order	order	NOUN
ajst-24888	63	19	to	to	PART
ajst-24888	63	20	classify	classify	VERB
ajst-24888	63	21	unlabeled	unlabeled	ADJ
ajst-24888	63	22	data	datum	NOUN
ajst-24888	63	23	.	.	PUNCT
ajst-24888	64	1	(	(	PUNCT
ajst-24888	64	2	1	1	X
ajst-24888	64	3	)	)	PUNCT
ajst-24888	64	4	support	support	NOUN
ajst-24888	64	5	vector	vector	NOUN
ajst-24888	64	6	machine	machine	NOUN
ajst-24888	64	7	(	(	PUNCT
ajst-24888	64	8	svm	svm	PROPN
ajst-24888	64	9	)	)	PUNCT
ajst-24888	64	10	[	[	X
ajst-24888	64	11	13	13	NUM
ajst-24888	64	12	]	]	PUNCT
ajst-24888	64	13	:	:	PUNCT
ajst-24888	64	14	svm	svm	PROPN
ajst-24888	64	15	is	be	AUX
ajst-24888	64	16	a	a	DET
ajst-24888	64	17	supervised	supervised	ADJ
ajst-24888	64	18	learning	learn	VERB
ajst-24888	64	19	algorithm	algorithm	NOUN
ajst-24888	64	20	for	for	ADP
ajst-24888	64	21	classification	classification	NOUN
ajst-24888	64	22	and	and	CCONJ
ajst-24888	64	23	regression	regression	NOUN
ajst-24888	64	24	,	,	PUNCT
ajst-24888	64	25	which	which	PRON
ajst-24888	64	26	separates	separate	VERB
ajst-24888	64	27	different	different	ADJ
ajst-24888	64	28	categories	category	NOUN
ajst-24888	64	29	of	of	ADP
ajst-24888	64	30	data	datum	NOUN
ajst-24888	64	31	by	by	ADP
ajst-24888	64	32	finding	find	VERB
ajst-24888	64	33	the	the	DET
ajst-24888	64	34	optimal	optimal	ADJ
ajst-24888	64	35	hyperplane	hyperplane	NOUN
ajst-24888	64	36	.	.	PUNCT
ajst-24888	65	1	in	in	ADP
ajst-24888	65	2	lithology	lithology	NOUN
ajst-24888	65	3	identification	identification	NOUN
ajst-24888	65	4	,	,	PUNCT
ajst-24888	65	5	svm	svm	NOUN
ajst-24888	65	6	can	can	AUX
ajst-24888	65	7	be	be	AUX
ajst-24888	65	8	used	use	VERB
ajst-24888	65	9	to	to	PART
ajst-24888	65	10	distinguish	distinguish	VERB
ajst-24888	65	11	between	between	ADP
ajst-24888	65	12	different	different	ADJ
ajst-24888	65	13	types	type	NOUN
ajst-24888	65	14	of	of	ADP
ajst-24888	65	15	rocks	rock	NOUN
ajst-24888	65	16	.	.	PUNCT
ajst-24888	66	1	(	(	PUNCT
ajst-24888	66	2	2	2	X
ajst-24888	66	3	)	)	PUNCT
ajst-24888	66	4	decision	decision	NOUN
ajst-24888	66	5	tree	tree	NOUN
ajst-24888	67	1	[	[	X
ajst-24888	67	2	14	14	NUM
ajst-24888	67	3	]	]	X
ajst-24888	67	4	:	:	PUNCT
ajst-24888	67	5	decision	decision	NOUN
ajst-24888	67	6	tree	tree	NOUN
ajst-24888	67	7	conducts	conduct	VERB
ajst-24888	67	8	classification	classification	NOUN
ajst-24888	67	9	or	or	CCONJ
ajst-24888	67	10	regression	regression	NOUN
ajst-24888	67	11	by	by	ADP
ajst-24888	67	12	building	build	VERB
ajst-24888	67	13	a	a	DET
ajst-24888	67	14	tree	tree	NOUN
ajst-24888	67	15	model	model	NOUN
ajst-24888	67	16	,	,	PUNCT
ajst-24888	67	17	in	in	ADP
ajst-24888	67	18	which	which	PRON
ajst-24888	67	19	each	each	DET
ajst-24888	67	20	node	node	NOUN
ajst-24888	67	21	represents	represent	VERB
ajst-24888	67	22	a	a	DET
ajst-24888	67	23	feature	feature	NOUN
ajst-24888	67	24	and	and	CCONJ
ajst-24888	67	25	each	each	DET
ajst-24888	67	26	branch	branch	NOUN
ajst-24888	67	27	represents	represent	VERB
ajst-24888	67	28	the	the	DET
ajst-24888	67	29	possible	possible	ADJ
ajst-24888	67	30	value	value	NOUN
ajst-24888	67	31	of	of	ADP
ajst-24888	67	32	the	the	DET
ajst-24888	67	33	feature	feature	NOUN
ajst-24888	67	34	.	.	PUNCT
ajst-24888	68	1	in	in	ADP
ajst-24888	68	2	lithology	lithology	NOUN
ajst-24888	68	3	identification	identification	NOUN
ajst-24888	68	4	,	,	PUNCT
ajst-24888	68	5	decision	decision	NOUN
ajst-24888	68	6	tree	tree	NOUN
ajst-24888	68	7	can	can	AUX
ajst-24888	68	8	intuitively	intuitively	ADV
ajst-24888	68	9	show	show	VERB
ajst-24888	68	10	the	the	DET
ajst-24888	68	11	influence	influence	NOUN
ajst-24888	68	12	of	of	ADP
ajst-24888	68	13	features	feature	NOUN
ajst-24888	68	14	on	on	ADP
ajst-24888	68	15	classification	classification	NOUN
ajst-24888	68	16	results	result	NOUN
ajst-24888	68	17	.	.	PUNCT
ajst-24888	69	1	(	(	PUNCT
ajst-24888	69	2	3	3	X
ajst-24888	69	3	)	)	PUNCT
ajst-24888	69	4	random	random	ADJ
ajst-24888	69	5	forest	forest	NOUN
ajst-24888	70	1	[	[	X
ajst-24888	70	2	15	15	NUM
ajst-24888	70	3	]	]	X
ajst-24888	70	4	:	:	PUNCT
ajst-24888	70	5	random	random	ADJ
ajst-24888	70	6	forest	forest	NOUN
ajst-24888	70	7	is	be	AUX
ajst-24888	70	8	an	an	DET
ajst-24888	70	9	integrated	integrated	ADJ
ajst-24888	70	10	learning	learning	NOUN
ajst-24888	70	11	method	method	NOUN
ajst-24888	70	12	composed	compose	VERB
ajst-24888	70	13	of	of	ADP
ajst-24888	70	14	multiple	multiple	ADJ
ajst-24888	70	15	decision	decision	NOUN
ajst-24888	70	16	trees	tree	NOUN
ajst-24888	70	17	,	,	PUNCT
ajst-24888	70	18	which	which	PRON
ajst-24888	70	19	improves	improve	VERB
ajst-24888	70	20	classification	classification	NOUN
ajst-24888	70	21	accuracy	accuracy	NOUN
ajst-24888	70	22	and	and	CCONJ
ajst-24888	70	23	robustness	robustness	NOUN
ajst-24888	70	24	through	through	ADP
ajst-24888	70	25	voting	voting	NOUN
ajst-24888	70	26	mechanism	mechanism	NOUN
ajst-24888	70	27	.	.	PUNCT
ajst-24888	71	1	in	in	ADP
ajst-24888	71	2	lithology	lithology	NOUN
ajst-24888	71	3	identification	identification	NOUN
ajst-24888	71	4	,	,	PUNCT
ajst-24888	71	5	random	random	ADJ
ajst-24888	71	6	forest	forest	NOUN
ajst-24888	71	7	can	can	AUX
ajst-24888	71	8	process	process	VERB
ajst-24888	71	9	high	high	ADJ
ajst-24888	71	10	dimensional	dimensional	ADJ
ajst-24888	71	11	data	datum	NOUN
ajst-24888	71	12	and	and	CCONJ
ajst-24888	71	13	noise	noise	NOUN
ajst-24888	71	14	data	datum	NOUN
ajst-24888	71	15	,	,	PUNCT
ajst-24888	71	16	and	and	CCONJ
ajst-24888	71	17	the	the	DET
ajst-24888	71	18	effect	effect	NOUN
ajst-24888	71	19	is	be	AUX
ajst-24888	71	20	remarkable	remarkable	ADJ
ajst-24888	71	21	.	.	PUNCT
ajst-24888	72	1	(	(	PUNCT
ajst-24888	72	2	4	4	X
ajst-24888	72	3	)	)	PUNCT
ajst-24888	72	4	neural	neural	ADJ
ajst-24888	72	5	network	network	NOUN
ajst-24888	72	6	[	[	X
ajst-24888	72	7	16	16	NUM
ajst-24888	72	8	]	]	X
ajst-24888	72	9	:	:	PUNCT
ajst-24888	72	10	neural	neural	ADJ
ajst-24888	72	11	network	network	NOUN
ajst-24888	72	12	is	be	AUX
ajst-24888	72	13	a	a	DET
ajst-24888	72	14	model	model	NOUN
ajst-24888	72	15	composed	compose	VERB
ajst-24888	72	16	of	of	ADP
ajst-24888	72	17	multiple	multiple	ADJ
ajst-24888	72	18	neurons	neuron	NOUN
ajst-24888	72	19	,	,	PUNCT
ajst-24888	72	20	which	which	PRON
ajst-24888	72	21	can	can	AUX
ajst-24888	72	22	learn	learn	VERB
ajst-24888	72	23	and	and	CCONJ
ajst-24888	72	24	predict	predict	VERB
ajst-24888	72	25	by	by	ADP
ajst-24888	72	26	simulating	simulate	VERB
ajst-24888	72	27	biological	biological	ADJ
ajst-24888	72	28	neural	neural	ADJ
ajst-24888	72	29	network	network	NOUN
ajst-24888	72	30	.	.	PUNCT
ajst-24888	73	1	in	in	ADP
ajst-24888	73	2	lithology	lithology	NOUN
ajst-24888	73	3	identification	identification	NOUN
ajst-24888	73	4	,	,	PUNCT
ajst-24888	73	5	neural	neural	ADJ
ajst-24888	73	6	network	network	NOUN
ajst-24888	73	7	is	be	AUX
ajst-24888	73	8	especially	especially	ADV
ajst-24888	73	9	suitable	suitable	ADJ
ajst-24888	73	10	for	for	ADP
ajst-24888	73	11	processing	processing	NOUN
ajst-24888	73	12	complex	complex	ADJ
ajst-24888	73	13	nonlinear	nonlinear	ADJ
ajst-24888	73	14	data	datum	NOUN
ajst-24888	73	15	.	.	PUNCT
ajst-24888	74	1	3.2	3.2	NUM
ajst-24888	74	2	.	.	PUNCT
ajst-24888	75	1	unsupervised	unsupervised	ADJ
ajst-24888	75	2	learning	learn	VERB
ajst-24888	75	3	unsupervised	unsupervised	ADJ
ajst-24888	75	4	learning	learning	NOUN
ajst-24888	75	5	is	be	AUX
ajst-24888	75	6	used	use	VERB
ajst-24888	75	7	to	to	PART
ajst-24888	75	8	process	process	VERB
ajst-24888	75	9	unlabeled	unlabeled	ADJ
ajst-24888	75	10	data	datum	NOUN
ajst-24888	75	11	and	and	CCONJ
ajst-24888	75	12	classify	classify	VERB
ajst-24888	75	13	or	or	CCONJ
ajst-24888	75	14	cluster	cluster	NOUN
ajst-24888	75	15	by	by	ADP
ajst-24888	75	16	mining	mine	VERB
ajst-24888	75	17	the	the	DET
ajst-24888	75	18	internal	internal	ADJ
ajst-24888	75	19	structure	structure	NOUN
ajst-24888	75	20	of	of	ADP
ajst-24888	75	21	the	the	DET
ajst-24888	75	22	data	datum	NOUN
ajst-24888	75	23	.	.	PUNCT
ajst-24888	76	1	in	in	ADP
ajst-24888	76	2	lithology	lithology	NOUN
ajst-24888	76	3	identification	identification	NOUN
ajst-24888	76	4	,	,	PUNCT
ajst-24888	76	5	unsupervised	unsupervised	ADJ
ajst-24888	76	6	learning	learning	NOUN
ajst-24888	76	7	is	be	AUX
ajst-24888	76	8	often	often	ADV
ajst-24888	76	9	used	use	VERB
ajst-24888	76	10	to	to	PART
ajst-24888	76	11	discover	discover	VERB
ajst-24888	76	12	patterns	pattern	NOUN
ajst-24888	76	13	and	and	CCONJ
ajst-24888	76	14	regularities	regularity	NOUN
ajst-24888	76	15	in	in	ADP
ajst-24888	76	16	data	datum	NOUN
ajst-24888	76	17	.	.	PUNCT
ajst-24888	77	1	(	(	PUNCT
ajst-24888	77	2	1	1	X
ajst-24888	77	3	)	)	PUNCT
ajst-24888	77	4	k	k	NOUN
ajst-24888	77	5	-	-	PUNCT
ajst-24888	77	6	means	means	NOUN
ajst-24888	77	7	clustering	cluster	VERB
ajst-24888	77	8	[	[	X
ajst-24888	77	9	17	17	NUM
ajst-24888	77	10	]	]	PUNCT
ajst-24888	77	11	:	:	PUNCT
ajst-24888	77	12	k	k	X
ajst-24888	77	13	-	-	PUNCT
ajst-24888	77	14	means	means	NOUN
ajst-24888	77	15	is	be	AUX
ajst-24888	77	16	a	a	DET
ajst-24888	77	17	clustering	clustering	ADJ
ajst-24888	77	18	algorithm	algorithm	NOUN
ajst-24888	77	19	that	that	PRON
ajst-24888	77	20	maximizes	maximize	VERB
ajst-24888	77	21	the	the	DET
ajst-24888	77	22	similarity	similarity	NOUN
ajst-24888	77	23	of	of	ADP
ajst-24888	77	24	the	the	DET
ajst-24888	77	25	data	datum	NOUN
ajst-24888	77	26	within	within	ADP
ajst-24888	77	27	the	the	DET
ajst-24888	77	28	cluster	cluster	NOUN
ajst-24888	77	29	by	by	ADP
ajst-24888	77	30	dividing	divide	VERB
ajst-24888	77	31	the	the	DET
ajst-24888	77	32	data	datum	NOUN
ajst-24888	77	33	into	into	ADP
ajst-24888	77	34	k	k	PROPN
ajst-24888	77	35	clusters	cluster	NOUN
ajst-24888	77	36	.	.	PUNCT
ajst-24888	78	1	in	in	ADP
ajst-24888	78	2	lithology	lithology	NOUN
ajst-24888	78	3	identification	identification	NOUN
ajst-24888	78	4	,	,	PUNCT
ajst-24888	78	5	k	k	NOUN
ajst-24888	78	6	-	-	PUNCT
ajst-24888	78	7	means	means	NOUN
ajst-24888	78	8	can	can	AUX
ajst-24888	78	9	be	be	AUX
ajst-24888	78	10	used	use	VERB
ajst-24888	78	11	for	for	ADP
ajst-24888	78	12	preliminary	preliminary	ADJ
ajst-24888	78	13	classification	classification	NOUN
ajst-24888	78	14	to	to	PART
ajst-24888	78	15	identify	identify	VERB
ajst-24888	78	16	potential	potential	ADJ
ajst-24888	78	17	lithology	lithology	NOUN
ajst-24888	78	18	types	type	NOUN
ajst-24888	78	19	in	in	ADP
ajst-24888	78	20	the	the	DET
ajst-24888	78	21	data	datum	NOUN
ajst-24888	78	22	.	.	PUNCT
ajst-24888	79	1	(	(	PUNCT
ajst-24888	79	2	2	2	X
ajst-24888	79	3	)	)	PUNCT
ajst-24888	79	4	principal	principal	ADJ
ajst-24888	79	5	component	component	NOUN
ajst-24888	79	6	analysis	analysis	NOUN
ajst-24888	79	7	(	(	PUNCT
ajst-24888	79	8	pca	pca	NOUN
ajst-24888	79	9	)	)	PUNCT
ajst-24888	80	1	[	[	X
ajst-24888	80	2	18	18	NUM
ajst-24888	80	3	]	]	X
ajst-24888	80	4	:	:	PUNCT
ajst-24888	80	5	pca	pca	PROPN
ajst-24888	80	6	is	be	AUX
ajst-24888	80	7	a	a	DET
ajst-24888	80	8	dimensionality	dimensionality	NOUN
ajst-24888	80	9	reduction	reduction	NOUN
ajst-24888	80	10	technique	technique	NOUN
ajst-24888	80	11	,	,	PUNCT
ajst-24888	80	12	which	which	PRON
ajst-24888	80	13	maps	map	VERB
ajst-24888	80	14	highdimensional	highdimensional	ADJ
ajst-24888	80	15	data	datum	NOUN
ajst-24888	80	16	to	to	ADP
ajst-24888	80	17	low	low	ADJ
ajst-24888	80	18	-	-	PUNCT
ajst-24888	80	19	dimensional	dimensional	ADJ
ajst-24888	80	20	space	space	NOUN
ajst-24888	80	21	through	through	ADP
ajst-24888	80	22	linear	linear	ADJ
ajst-24888	80	23	transformation	transformation	NOUN
ajst-24888	80	24	and	and	CCONJ
ajst-24888	80	25	retains	retain	VERB
ajst-24888	80	26	the	the	DET
ajst-24888	80	27	main	main	ADJ
ajst-24888	80	28	features	feature	NOUN
ajst-24888	80	29	of	of	ADP
ajst-24888	80	30	the	the	DET
ajst-24888	80	31	data	datum	NOUN
ajst-24888	80	32	.	.	PUNCT
ajst-24888	81	1	in	in	ADP
ajst-24888	81	2	lithology	lithology	NOUN
ajst-24888	81	3	identification	identification	NOUN
ajst-24888	81	4	,	,	PUNCT
ajst-24888	81	5	pca	pca	PROPN
ajst-24888	81	6	can	can	AUX
ajst-24888	81	7	be	be	AUX
ajst-24888	81	8	used	use	VERB
ajst-24888	81	9	for	for	ADP
ajst-24888	81	10	data	data	NOUN
ajst-24888	81	11	dimensionality	dimensionality	NOUN
ajst-24888	81	12	reduction	reduction	NOUN
ajst-24888	81	13	and	and	CCONJ
ajst-24888	81	14	computational	computational	ADJ
ajst-24888	81	15	complexity	complexity	NOUN
ajst-24888	81	16	reduction	reduction	NOUN
ajst-24888	81	17	.	.	PUNCT
ajst-24888	82	1	3.3	3.3	NUM
ajst-24888	82	2	.	.	PUNCT
ajst-24888	83	1	deep	deep	ADJ
ajst-24888	83	2	learning	learn	VERB
ajst-24888	83	3	deep	deep	ADJ
ajst-24888	83	4	learning	learning	NOUN
ajst-24888	83	5	is	be	AUX
ajst-24888	83	6	a	a	DET
ajst-24888	83	7	branch	branch	NOUN
ajst-24888	83	8	of	of	ADP
ajst-24888	83	9	machine	machine	NOUN
ajst-24888	83	10	learning	learning	NOUN
ajst-24888	83	11	that	that	PRON
ajst-24888	83	12	learns	learn	VERB
ajst-24888	83	13	and	and	CCONJ
ajst-24888	83	14	makes	make	VERB
ajst-24888	83	15	predictions	prediction	NOUN
ajst-24888	83	16	by	by	ADP
ajst-24888	83	17	building	build	VERB
ajst-24888	83	18	multi	multi	ADJ
ajst-24888	83	19	-	-	ADJ
ajst-24888	83	20	layered	layered	ADJ
ajst-24888	83	21	neural	neural	ADJ
ajst-24888	83	22	networks	network	NOUN
ajst-24888	83	23	,	,	PUNCT
ajst-24888	83	24	and	and	CCONJ
ajst-24888	83	25	is	be	AUX
ajst-24888	83	26	particularly	particularly	ADV
ajst-24888	83	27	suited	suit	VERB
ajst-24888	83	28	for	for	ADP
ajst-24888	83	29	working	work	VERB
ajst-24888	83	30	with	with	ADP
ajst-24888	83	31	complex	complex	ADJ
ajst-24888	83	32	,	,	PUNCT
ajst-24888	83	33	high	high	ADJ
ajst-24888	83	34	-	-	PUNCT
ajst-24888	83	35	dimensional	dimensional	ADJ
ajst-24888	83	36	data	datum	NOUN
ajst-24888	83	37	.	.	PUNCT
ajst-24888	84	1	in	in	ADP
ajst-24888	84	2	lithology	lithology	NOUN
ajst-24888	84	3	identification	identification	NOUN
ajst-24888	84	4	,	,	PUNCT
ajst-24888	84	5	deep	deep	ADJ
ajst-24888	84	6	learning	learning	NOUN
ajst-24888	84	7	methods	method	NOUN
ajst-24888	84	8	perform	perform	VERB
ajst-24888	84	9	well	well	ADV
ajst-24888	84	10	,	,	PUNCT
ajst-24888	84	11	which	which	PRON
ajst-24888	84	12	can	can	AUX
ajst-24888	84	13	automatically	automatically	ADV
ajst-24888	84	14	extract	extract	VERB
ajst-24888	84	15	features	feature	NOUN
ajst-24888	84	16	and	and	CCONJ
ajst-24888	84	17	accurately	accurately	ADV
ajst-24888	84	18	classify	classify	VERB
ajst-24888	84	19	them	they	PRON
ajst-24888	84	20	.	.	PUNCT
ajst-24888	85	1	(	(	PUNCT
ajst-24888	85	2	1	1	X
ajst-24888	85	3	)	)	PUNCT
ajst-24888	85	4	convolutional	convolutional	ADJ
ajst-24888	85	5	neural	neural	ADJ
ajst-24888	85	6	network	network	NOUN
ajst-24888	85	7	(	(	PUNCT
ajst-24888	85	8	cnn	cnn	PROPN
ajst-24888	85	9	)	)	PUNCT
ajst-24888	86	1	[	[	X
ajst-24888	86	2	19	19	NUM
ajst-24888	86	3	]	]	PUNCT
ajst-24888	86	4	:	:	PUNCT
ajst-24888	86	5	cnn	cnn	PROPN
ajst-24888	86	6	is	be	AUX
ajst-24888	86	7	a	a	DET
ajst-24888	86	8	kind	kind	NOUN
ajst-24888	86	9	of	of	ADP
ajst-24888	86	10	neural	neural	ADJ
ajst-24888	86	11	network	network	NOUN
ajst-24888	86	12	specially	specially	ADV
ajst-24888	86	13	used	use	VERB
ajst-24888	86	14	to	to	PART
ajst-24888	86	15	process	process	VERB
ajst-24888	86	16	image	image	NOUN
ajst-24888	86	17	data	datum	NOUN
ajst-24888	86	18	,	,	PUNCT
ajst-24888	86	19	and	and	CCONJ
ajst-24888	86	20	extracts	extract	VERB
ajst-24888	86	21	local	local	ADJ
ajst-24888	86	22	features	feature	NOUN
ajst-24888	86	23	of	of	ADP
ajst-24888	86	24	images	image	NOUN
ajst-24888	86	25	through	through	ADP
ajst-24888	86	26	convolutional	convolutional	ADJ
ajst-24888	86	27	layer	layer	NOUN
ajst-24888	86	28	and	and	CCONJ
ajst-24888	86	29	pooling	pool	VERB
ajst-24888	86	30	layer	layer	NOUN
ajst-24888	86	31	.	.	PUNCT
ajst-24888	87	1	in	in	ADP
ajst-24888	87	2	lithology	lithology	NOUN
ajst-24888	87	3	identification	identification	NOUN
ajst-24888	87	4	,	,	PUNCT
ajst-24888	87	5	cnn	cnn	PROPN
ajst-24888	87	6	can	can	AUX
ajst-24888	87	7	be	be	AUX
ajst-24888	87	8	used	use	VERB
ajst-24888	87	9	to	to	PART
ajst-24888	87	10	analyze	analyze	VERB
ajst-24888	87	11	seismic	seismic	ADJ
ajst-24888	87	12	image	image	NOUN
ajst-24888	87	13	data	datum	NOUN
ajst-24888	87	14	and	and	CCONJ
ajst-24888	87	15	automatically	automatically	ADV
ajst-24888	87	16	123	123	NUM
ajst-24888	87	17	identify	identify	VERB
ajst-24888	87	18	the	the	DET
ajst-24888	87	19	formation	formation	NOUN
ajst-24888	87	20	characteristics	characteristic	NOUN
ajst-24888	87	21	of	of	ADP
ajst-24888	87	22	different	different	ADJ
ajst-24888	87	23	lithology	lithology	NOUN
ajst-24888	87	24	.	.	PUNCT
ajst-24888	88	1	(	(	PUNCT
ajst-24888	88	2	2	2	X
ajst-24888	88	3	)	)	PUNCT
ajst-24888	88	4	recurrent	recurrent	ADJ
ajst-24888	88	5	neural	neural	ADJ
ajst-24888	88	6	network	network	NOUN
ajst-24888	88	7	(	(	PUNCT
ajst-24888	88	8	rnn	rnn	PROPN
ajst-24888	88	9	)	)	PUNCT
ajst-24888	89	1	[	[	X
ajst-24888	89	2	20	20	NUM
ajst-24888	89	3	]	]	PUNCT
ajst-24888	89	4	:	:	PUNCT
ajst-24888	89	5	rnn	rnn	NOUN
ajst-24888	89	6	is	be	AUX
ajst-24888	89	7	a	a	DET
ajst-24888	89	8	kind	kind	NOUN
ajst-24888	89	9	of	of	ADP
ajst-24888	89	10	neural	neural	ADJ
ajst-24888	89	11	network	network	NOUN
ajst-24888	89	12	used	use	VERB
ajst-24888	89	13	to	to	PART
ajst-24888	89	14	process	process	VERB
ajst-24888	89	15	sequence	sequence	NOUN
ajst-24888	89	16	data	datum	NOUN
ajst-24888	89	17	,	,	PUNCT
ajst-24888	89	18	memorizing	memorize	VERB
ajst-24888	89	19	and	and	CCONJ
ajst-24888	89	20	processing	processing	NOUN
ajst-24888	89	21	time	time	NOUN
ajst-24888	89	22	series	series	PROPN
ajst-24888	89	23	information	information	NOUN
ajst-24888	89	24	through	through	ADP
ajst-24888	89	25	cyclic	cyclic	ADJ
ajst-24888	89	26	structure	structure	NOUN
ajst-24888	89	27	.	.	PUNCT
ajst-24888	90	1	in	in	ADP
ajst-24888	90	2	lithology	lithology	NOUN
ajst-24888	90	3	identification	identification	NOUN
ajst-24888	90	4	,	,	PUNCT
ajst-24888	90	5	rnns	rnns	PROPN
ajst-24888	90	6	can	can	AUX
ajst-24888	90	7	be	be	AUX
ajst-24888	90	8	used	use	VERB
ajst-24888	90	9	to	to	PART
ajst-24888	90	10	analyze	analyze	VERB
ajst-24888	90	11	log	log	NOUN
ajst-24888	90	12	data	datum	NOUN
ajst-24888	90	13	and	and	CCONJ
ajst-24888	90	14	capture	capture	VERB
ajst-24888	90	15	formation	formation	NOUN
ajst-24888	90	16	characteristics	characteristic	NOUN
ajst-24888	90	17	that	that	PRON
ajst-24888	90	18	change	change	VERB
ajst-24888	90	19	with	with	ADP
ajst-24888	90	20	depth	depth	NOUN
ajst-24888	90	21	.	.	PUNCT
ajst-24888	91	1	(	(	PUNCT
ajst-24888	91	2	3	3	X
ajst-24888	91	3	)	)	PUNCT
ajst-24888	91	4	generative	generative	ADJ
ajst-24888	91	5	adversarial	adversarial	ADJ
ajst-24888	91	6	network	network	NOUN
ajst-24888	91	7	(	(	PUNCT
ajst-24888	91	8	gan	gan	PROPN
ajst-24888	91	9	)	)	PUNCT
ajst-24888	92	1	[	[	X
ajst-24888	92	2	21	21	NUM
ajst-24888	92	3	]	]	PUNCT
ajst-24888	92	4	:	:	PUNCT
ajst-24888	92	5	gan	gan	PROPN
ajst-24888	92	6	is	be	AUX
ajst-24888	92	7	a	a	DET
ajst-24888	92	8	deep	deep	ADJ
ajst-24888	92	9	learning	learning	NOUN
ajst-24888	92	10	model	model	NOUN
ajst-24888	92	11	that	that	PRON
ajst-24888	92	12	learns	learn	VERB
ajst-24888	92	13	against	against	ADP
ajst-24888	92	14	each	each	DET
ajst-24888	92	15	other	other	ADJ
ajst-24888	92	16	through	through	ADP
ajst-24888	92	17	generator	generator	NOUN
ajst-24888	92	18	and	and	CCONJ
ajst-24888	92	19	discriminator	discriminator	NOUN
ajst-24888	92	20	,	,	PUNCT
ajst-24888	92	21	which	which	PRON
ajst-24888	92	22	is	be	AUX
ajst-24888	92	23	used	use	VERB
ajst-24888	92	24	to	to	PART
ajst-24888	92	25	generate	generate	VERB
ajst-24888	92	26	realistic	realistic	ADJ
ajst-24888	92	27	data	datum	NOUN
ajst-24888	92	28	samples	sample	NOUN
ajst-24888	92	29	.	.	PUNCT
ajst-24888	93	1	in	in	ADP
ajst-24888	93	2	lithology	lithology	NOUN
ajst-24888	93	3	identification	identification	NOUN
ajst-24888	93	4	,	,	PUNCT
ajst-24888	93	5	gan	gan	PROPN
ajst-24888	93	6	can	can	AUX
ajst-24888	93	7	be	be	AUX
ajst-24888	93	8	used	use	VERB
ajst-24888	93	9	for	for	ADP
ajst-24888	93	10	data	data	NOUN
ajst-24888	93	11	enhancement	enhancement	NOUN
ajst-24888	93	12	to	to	PART
ajst-24888	93	13	generate	generate	VERB
ajst-24888	93	14	synthetic	synthetic	ADJ
ajst-24888	93	15	data	datum	NOUN
ajst-24888	93	16	to	to	PART
ajst-24888	93	17	make	make	VERB
ajst-24888	93	18	up	up	ADP
ajst-24888	93	19	for	for	ADP
ajst-24888	93	20	the	the	DET
ajst-24888	93	21	problem	problem	NOUN
ajst-24888	93	22	of	of	ADP
ajst-24888	93	23	insufficient	insufficient	ADJ
ajst-24888	93	24	data	datum	NOUN
ajst-24888	93	25	.	.	PUNCT
ajst-24888	94	1	4	4	X
ajst-24888	94	2	.	.	X
ajst-24888	94	3	methods	method	NOUN
ajst-24888	94	4	evaluation	evaluation	NOUN
ajst-24888	94	5	indicators	indicator	NOUN
ajst-24888	94	6	[	[	X
ajst-24888	94	7	22	22	NUM
ajst-24888	94	8	]	]	PUNCT
ajst-24888	94	9	in	in	ADP
ajst-24888	94	10	machine	machine	NOUN
ajst-24888	94	11	learning	learning	NOUN
ajst-24888	94	12	-	-	PUNCT
ajst-24888	94	13	based	base	VERB
ajst-24888	94	14	lithology	lithology	NOUN
ajst-24888	94	15	identification	identification	NOUN
ajst-24888	94	16	,	,	PUNCT
ajst-24888	94	17	it	it	PRON
ajst-24888	94	18	is	be	AUX
ajst-24888	94	19	very	very	ADV
ajst-24888	94	20	important	important	ADJ
ajst-24888	94	21	to	to	PART
ajst-24888	94	22	select	select	VERB
ajst-24888	94	23	suitable	suitable	ADJ
ajst-24888	94	24	models	model	NOUN
ajst-24888	94	25	and	and	CCONJ
ajst-24888	94	26	methods	method	NOUN
ajst-24888	94	27	and	and	CCONJ
ajst-24888	94	28	evaluate	evaluate	VERB
ajst-24888	94	29	them	they	PRON
ajst-24888	94	30	effectively	effectively	ADV
ajst-24888	94	31	.	.	PUNCT
ajst-24888	95	1	different	different	ADJ
ajst-24888	95	2	machine	machine	NOUN
ajst-24888	95	3	learning	learn	VERB
ajst-24888	95	4	methods	method	NOUN
ajst-24888	95	5	have	have	VERB
ajst-24888	95	6	advantages	advantage	NOUN
ajst-24888	95	7	and	and	CCONJ
ajst-24888	95	8	disadvantages	disadvantage	NOUN
ajst-24888	95	9	,	,	PUNCT
ajst-24888	95	10	and	and	CCONJ
ajst-24888	95	11	are	be	AUX
ajst-24888	95	12	suitable	suitable	ADJ
ajst-24888	95	13	for	for	ADP
ajst-24888	95	14	different	different	ADJ
ajst-24888	95	15	data	datum	NOUN
ajst-24888	95	16	types	type	NOUN
ajst-24888	95	17	and	and	CCONJ
ajst-24888	95	18	task	task	NOUN
ajst-24888	95	19	requirements	requirement	NOUN
ajst-24888	95	20	.	.	PUNCT
ajst-24888	96	1	the	the	DET
ajst-24888	96	2	following	follow	VERB
ajst-24888	96	3	will	will	AUX
ajst-24888	96	4	describe	describe	VERB
ajst-24888	96	5	in	in	ADP
ajst-24888	96	6	detail	detail	NOUN
ajst-24888	96	7	the	the	DET
ajst-24888	96	8	criteria	criterion	NOUN
ajst-24888	96	9	for	for	ADP
ajst-24888	96	10	comparison	comparison	NOUN
ajst-24888	96	11	and	and	CCONJ
ajst-24888	96	12	evaluation	evaluation	NOUN
ajst-24888	96	13	of	of	ADP
ajst-24888	96	14	methods	method	NOUN
ajst-24888	96	15	,	,	PUNCT
ajst-24888	96	16	common	common	ADJ
ajst-24888	96	17	evaluation	evaluation	NOUN
ajst-24888	96	18	indicators	indicator	NOUN
ajst-24888	96	19	and	and	CCONJ
ajst-24888	96	20	case	case	NOUN
ajst-24888	96	21	studies	study	NOUN
ajst-24888	96	22	in	in	ADP
ajst-24888	96	23	practical	practical	ADJ
ajst-24888	96	24	applications	application	NOUN
ajst-24888	96	25	.	.	PUNCT
ajst-24888	97	1	when	when	SCONJ
ajst-24888	97	2	selecting	select	VERB
ajst-24888	97	3	and	and	CCONJ
ajst-24888	97	4	evaluating	evaluate	VERB
ajst-24888	97	5	machine	machine	NOUN
ajst-24888	97	6	learning	learning	NOUN
ajst-24888	97	7	methods	method	NOUN
ajst-24888	97	8	,	,	PUNCT
ajst-24888	97	9	there	there	PRON
ajst-24888	97	10	are	be	VERB
ajst-24888	97	11	several	several	ADJ
ajst-24888	97	12	criteria	criterion	NOUN
ajst-24888	97	13	that	that	PRON
ajst-24888	97	14	need	need	VERB
ajst-24888	97	15	to	to	PART
ajst-24888	97	16	be	be	AUX
ajst-24888	97	17	considered	consider	VERB
ajst-24888	97	18	:	:	PUNCT
ajst-24888	97	19	when	when	SCONJ
ajst-24888	97	20	dealing	deal	VERB
ajst-24888	97	21	with	with	ADP
ajst-24888	97	22	binary	binary	ADJ
ajst-24888	97	23	classification	classification	NOUN
ajst-24888	97	24	tasks	task	NOUN
ajst-24888	97	25	,	,	PUNCT
ajst-24888	97	26	the	the	DET
ajst-24888	97	27	confusion	confusion	NOUN
ajst-24888	97	28	matrix	matrix	NOUN
ajst-24888	97	29	is	be	AUX
ajst-24888	97	30	drawn	draw	VERB
ajst-24888	97	31	as	as	SCONJ
ajst-24888	97	32	follows	follow	VERB
ajst-24888	97	33	:	:	PUNCT
ajst-24888	97	34	where	where	SCONJ
ajst-24888	97	35	:	:	PUNCT
ajst-24888	97	36	is	be	AUX
ajst-24888	97	37	the	the	DET
ajst-24888	97	38	quantity	quantity	NOUN
ajst-24888	97	39	classified	classify	VERB
ajst-24888	97	40	as	as	ADP
ajst-24888	97	41	positive	positive	ADJ
ajst-24888	97	42	in	in	ADP
ajst-24888	97	43	the	the	DET
ajst-24888	97	44	positive	positive	ADJ
ajst-24888	97	45	sample	sample	NOUN
ajst-24888	97	46	;	;	PUNCT
ajst-24888	97	47	is	be	AUX
ajst-24888	97	48	the	the	DET
ajst-24888	97	49	number	number	NOUN
ajst-24888	97	50	classified	classify	VERB
ajst-24888	97	51	as	as	ADP
ajst-24888	97	52	negative	negative	ADJ
ajst-24888	97	53	in	in	ADP
ajst-24888	97	54	the	the	DET
ajst-24888	97	55	positive	positive	ADJ
ajst-24888	97	56	sample	sample	NOUN
ajst-24888	97	57	;	;	PUNCT
ajst-24888	97	58	is	be	AUX
ajst-24888	97	59	the	the	DET
ajst-24888	97	60	number	number	NOUN
ajst-24888	97	61	of	of	ADP
ajst-24888	97	62	negative	negative	ADJ
ajst-24888	97	63	samples	sample	NOUN
ajst-24888	97	64	classified	classify	VERB
ajst-24888	97	65	as	as	ADP
ajst-24888	97	66	positive	positive	ADJ
ajst-24888	97	67	;	;	PUNCT
ajst-24888	97	68	is	be	AUX
ajst-24888	97	69	the	the	DET
ajst-24888	97	70	amount	amount	NOUN
ajst-24888	97	71	of	of	ADP
ajst-24888	97	72	the	the	DET
ajst-24888	97	73	negative	negative	ADJ
ajst-24888	97	74	sample	sample	NOUN
ajst-24888	97	75	that	that	PRON
ajst-24888	97	76	is	be	AUX
ajst-24888	97	77	classified	classify	VERB
ajst-24888	97	78	as	as	ADP
ajst-24888	97	79	negative	negative	ADJ
ajst-24888	97	80	.	.	PUNCT
ajst-24888	98	1	(	(	PUNCT
ajst-24888	98	2	1	1	X
ajst-24888	98	3	)	)	PUNCT
ajst-24888	98	4	accuracy	accuracy	NOUN
ajst-24888	98	5	refers	refer	VERB
ajst-24888	98	6	to	to	ADP
ajst-24888	98	7	the	the	DET
ajst-24888	98	8	proportion	proportion	NOUN
ajst-24888	98	9	of	of	ADP
ajst-24888	98	10	the	the	DET
ajst-24888	98	11	model	model	NOUN
ajst-24888	98	12	that	that	PRON
ajst-24888	98	13	is	be	AUX
ajst-24888	98	14	correctly	correctly	ADV
ajst-24888	98	15	classified	classified	ADJ
ajst-24888	98	16	in	in	ADP
ajst-24888	98	17	all	all	DET
ajst-24888	98	18	samples	sample	NOUN
ajst-24888	98	19	,	,	PUNCT
ajst-24888	98	20	and	and	CCONJ
ajst-24888	98	21	the	the	DET
ajst-24888	98	22	specific	specific	ADJ
ajst-24888	98	23	expression	expression	NOUN
ajst-24888	98	24	is	be	AUX
ajst-24888	98	25	shown	show	VERB
ajst-24888	98	26	in	in	ADP
ajst-24888	98	27	formula	formula	NOUN
ajst-24888	98	28	1	1	NUM
ajst-24888	98	29	.	.	PUNCT
ajst-24888	99	1	(	(	PUNCT
ajst-24888	99	2	1	1	NUM
ajst-24888	99	3	)	)	PUNCT
ajst-24888	99	4	(	(	PUNCT
ajst-24888	99	5	2	2	X
ajst-24888	99	6	)	)	PUNCT
ajst-24888	99	7	accuracy	accuracy	NOUN
ajst-24888	99	8	rate	rate	NOUN
ajst-24888	99	9	refers	refer	VERB
ajst-24888	99	10	to	to	ADP
ajst-24888	99	11	the	the	DET
ajst-24888	99	12	proportion	proportion	NOUN
ajst-24888	99	13	of	of	ADP
ajst-24888	99	14	all	all	DET
ajst-24888	99	15	samples	sample	NOUN
ajst-24888	99	16	predicted	predict	VERB
ajst-24888	99	17	by	by	ADP
ajst-24888	99	18	the	the	DET
ajst-24888	99	19	model	model	NOUN
ajst-24888	99	20	to	to	PART
ajst-24888	99	21	be	be	AUX
ajst-24888	99	22	positive	positive	ADJ
ajst-24888	99	23	,	,	PUNCT
ajst-24888	99	24	which	which	PRON
ajst-24888	99	25	is	be	AUX
ajst-24888	99	26	actually	actually	ADV
ajst-24888	99	27	positive	positive	ADJ
ajst-24888	99	28	.	.	PUNCT
ajst-24888	100	1	for	for	ADP
ajst-24888	100	2	specific	specific	ADJ
ajst-24888	100	3	expressions	expression	NOUN
ajst-24888	100	4	,	,	PUNCT
ajst-24888	100	5	see	see	VERB
ajst-24888	100	6	equation	equation	NOUN
ajst-24888	100	7	2	2	NUM
ajst-24888	100	8	.	.	PUNCT
ajst-24888	101	1	(	(	PUNCT
ajst-24888	101	2	2	2	NUM
ajst-24888	101	3	)	)	PUNCT
ajst-24888	101	4	(	(	PUNCT
ajst-24888	101	5	3	3	X
ajst-24888	101	6	)	)	PUNCT
ajst-24888	101	7	recall	recall	NOUN
ajst-24888	101	8	rate	rate	NOUN
ajst-24888	101	9	refers	refer	VERB
ajst-24888	101	10	to	to	ADP
ajst-24888	101	11	the	the	DET
ajst-24888	101	12	proportion	proportion	NOUN
ajst-24888	101	13	of	of	ADP
ajst-24888	101	14	samples	sample	NOUN
ajst-24888	101	15	that	that	PRON
ajst-24888	101	16	the	the	DET
ajst-24888	101	17	model	model	NOUN
ajst-24888	101	18	successfully	successfully	ADV
ajst-24888	101	19	predicts	predict	VERB
ajst-24888	101	20	to	to	PART
ajst-24888	101	21	be	be	AUX
ajst-24888	101	22	positive	positive	ADJ
ajst-24888	101	23	among	among	ADP
ajst-24888	101	24	all	all	DET
ajst-24888	101	25	samples	sample	NOUN
ajst-24888	101	26	that	that	PRON
ajst-24888	101	27	are	be	AUX
ajst-24888	101	28	actually	actually	ADV
ajst-24888	101	29	positive	positive	ADJ
ajst-24888	101	30	,	,	PUNCT
ajst-24888	101	31	and	and	CCONJ
ajst-24888	101	32	the	the	DET
ajst-24888	101	33	specific	specific	ADJ
ajst-24888	101	34	expression	expression	NOUN
ajst-24888	101	35	is	be	AUX
ajst-24888	101	36	shown	show	VERB
ajst-24888	101	37	in	in	ADP
ajst-24888	101	38	equation	equation	NOUN
ajst-24888	101	39	3	3	NUM
ajst-24888	101	40	.	.	PUNCT
ajst-24888	102	1	(	(	PUNCT
ajst-24888	102	2	3	3	NUM
ajst-24888	102	3	)	)	PUNCT
ajst-24888	102	4	(	(	PUNCT
ajst-24888	102	5	4	4	X
ajst-24888	102	6	)	)	PUNCT
ajst-24888	102	7	the	the	DET
ajst-24888	102	8	f1	f1	PROPN
ajst-24888	102	9	value	value	NOUN
ajst-24888	102	10	synthesizes	synthesize	VERB
ajst-24888	102	11	the	the	DET
ajst-24888	102	12	performance	performance	NOUN
ajst-24888	102	13	of	of	ADP
ajst-24888	102	14	precision	precision	NOUN
ajst-24888	102	15	rate	rate	NOUN
ajst-24888	102	16	and	and	CCONJ
ajst-24888	102	17	recall	recall	NOUN
ajst-24888	102	18	rate	rate	NOUN
ajst-24888	102	19	,	,	PUNCT
ajst-24888	102	20	and	and	CCONJ
ajst-24888	102	21	its	its	PRON
ajst-24888	102	22	value	value	NOUN
ajst-24888	102	23	range	range	NOUN
ajst-24888	102	24	is	be	AUX
ajst-24888	102	25	[	[	X
ajst-24888	102	26	0,1	0,1	NUM
ajst-24888	102	27	]	]	PUNCT
ajst-24888	102	28	.	.	PUNCT
ajst-24888	103	1	the	the	PRON
ajst-24888	103	2	larger	large	ADJ
ajst-24888	103	3	the	the	DET
ajst-24888	103	4	value	value	NOUN
ajst-24888	103	5	,	,	PUNCT
ajst-24888	103	6	the	the	PRON
ajst-24888	103	7	better	well	ADJ
ajst-24888	103	8	the	the	DET
ajst-24888	103	9	model	model	NOUN
ajst-24888	103	10	performance	performance	NOUN
ajst-24888	103	11	and	and	CCONJ
ajst-24888	103	12	stronger	strong	ADJ
ajst-24888	103	13	generalization	generalization	NOUN
ajst-24888	103	14	ability	ability	NOUN
ajst-24888	103	15	.	.	PUNCT
ajst-24888	104	1	for	for	ADP
ajst-24888	104	2	specific	specific	ADJ
ajst-24888	104	3	expressions	expression	NOUN
ajst-24888	104	4	,	,	PUNCT
ajst-24888	104	5	see	see	VERB
ajst-24888	104	6	equation	equation	NOUN
ajst-24888	104	7	4	4	NUM
ajst-24888	104	8	.	.	SYM
ajst-24888	104	9	2	2	NUM
ajst-24888	104	10	(	(	PUNCT
ajst-24888	104	11	4	4	NUM
ajst-24888	104	12	)	)	PUNCT
ajst-24888	104	13	(	(	PUNCT
ajst-24888	104	14	5	5	X
ajst-24888	104	15	)	)	PUNCT
ajst-24888	104	16	roc	roc	NOUN
ajst-24888	104	17	curve	curve	NOUN
ajst-24888	104	18	and	and	CCONJ
ajst-24888	104	19	area	area	NOUN
ajst-24888	104	20	under	under	ADP
ajst-24888	104	21	the	the	DET
ajst-24888	104	22	curve	curve	NOUN
ajst-24888	104	23	(	(	PUNCT
ajst-24888	104	24	receiver	receiver	ADV
ajst-24888	104	25	operating	operate	VERB
ajst-24888	104	26	characteristic	characteristic	ADJ
ajst-24888	104	27	curve	curve	NOUN
ajst-24888	104	28	and	and	CCONJ
ajst-24888	104	29	area	area	NOUN
ajst-24888	104	30	under	under	ADP
ajst-24888	104	31	the	the	DET
ajst-24888	104	32	curve	curve	NOUN
ajst-24888	104	33	)	)	PUNCT
ajst-24888	104	34	:	:	PUNCT
ajst-24888	104	35	the	the	DET
ajst-24888	104	36	roc	roc	PROPN
ajst-24888	104	37	curve	curve	NOUN
ajst-24888	104	38	evaluates	evaluate	VERB
ajst-24888	104	39	the	the	DET
ajst-24888	104	40	model	model	NOUN
ajst-24888	104	41	performance	performance	NOUN
ajst-24888	104	42	by	by	ADP
ajst-24888	104	43	describing	describe	VERB
ajst-24888	104	44	the	the	DET
ajst-24888	104	45	true	true	ADJ
ajst-24888	104	46	positive	positive	ADJ
ajst-24888	104	47	rate	rate	NOUN
ajst-24888	104	48	(	(	PUNCT
ajst-24888	104	49	tpr	tpr	NOUN
ajst-24888	104	50	)	)	PUNCT
ajst-24888	104	51	and	and	CCONJ
ajst-24888	104	52	false	false	ADJ
ajst-24888	104	53	positive	positive	ADJ
ajst-24888	104	54	rate	rate	NOUN
ajst-24888	104	55	(	(	PUNCT
ajst-24888	104	56	fpr	fpr	NOUN
ajst-24888	104	57	)	)	PUNCT
ajst-24888	104	58	under	under	ADP
ajst-24888	104	59	different	different	ADJ
ajst-24888	104	60	thresholds	threshold	NOUN
ajst-24888	104	61	,	,	PUNCT
ajst-24888	104	62	while	while	SCONJ
ajst-24888	104	63	the	the	DET
ajst-24888	104	64	auc	auc	NOUN
ajst-24888	104	65	is	be	AUX
ajst-24888	104	66	the	the	DET
ajst-24888	104	67	area	area	NOUN
ajst-24888	104	68	under	under	ADP
ajst-24888	104	69	the	the	DET
ajst-24888	104	70	roc	roc	PROPN
ajst-24888	104	71	curve	curve	NOUN
ajst-24888	104	72	,	,	PUNCT
ajst-24888	104	73	and	and	CCONJ
ajst-24888	104	74	the	the	DET
ajst-24888	104	75	closer	close	ADJ
ajst-24888	104	76	to	to	PART
ajst-24888	104	77	1	1	NUM
ajst-24888	104	78	,	,	PUNCT
ajst-24888	104	79	the	the	PRON
ajst-24888	104	80	better	well	ADJ
ajst-24888	104	81	the	the	DET
ajst-24888	104	82	model	model	NOUN
ajst-24888	104	83	performance	performance	NOUN
ajst-24888	104	84	.	.	PUNCT
ajst-24888	105	1	(	(	PUNCT
ajst-24888	105	2	6	6	NUM
ajst-24888	105	3	)	)	PUNCT
ajst-24888	105	4	confusion	confusion	NOUN
ajst-24888	105	5	matrix	matrix	NOUN
ajst-24888	105	6	:	:	PUNCT
ajst-24888	105	7	the	the	DET
ajst-24888	105	8	classification	classification	NOUN
ajst-24888	105	9	performance	performance	NOUN
ajst-24888	105	10	of	of	ADP
ajst-24888	105	11	the	the	DET
ajst-24888	105	12	model	model	NOUN
ajst-24888	105	13	is	be	AUX
ajst-24888	105	14	analyzed	analyze	VERB
ajst-24888	105	15	in	in	ADP
ajst-24888	105	16	detail	detail	NOUN
ajst-24888	105	17	by	by	ADP
ajst-24888	105	18	recording	record	VERB
ajst-24888	105	19	the	the	DET
ajst-24888	105	20	matching	matching	NOUN
ajst-24888	105	21	between	between	ADP
ajst-24888	105	22	the	the	DET
ajst-24888	105	23	predicted	predict	VERB
ajst-24888	105	24	results	result	NOUN
ajst-24888	105	25	and	and	CCONJ
ajst-24888	105	26	the	the	DET
ajst-24888	105	27	actual	actual	ADJ
ajst-24888	105	28	results	result	NOUN
ajst-24888	105	29	.	.	PUNCT
ajst-24888	106	1	the	the	DET
ajst-24888	106	2	confusion	confusion	NOUN
ajst-24888	106	3	matrix	matrix	NOUN
ajst-24888	106	4	includes	include	VERB
ajst-24888	106	5	tp	tp	NOUN
ajst-24888	106	6	,	,	PUNCT
ajst-24888	106	7	tn	tn	PROPN
ajst-24888	106	8	(	(	PUNCT
ajst-24888	106	9	true	true	ADJ
ajst-24888	106	10	negative	negative	NOUN
ajst-24888	106	11	)	)	PUNCT
ajst-24888	106	12	,	,	PUNCT
ajst-24888	106	13	fp	fp	PROPN
ajst-24888	106	14	,	,	PUNCT
ajst-24888	106	15	and	and	CCONJ
ajst-24888	106	16	fn	fn	NOUN
ajst-24888	106	17	.	.	PUNCT
ajst-24888	107	1	(	(	PUNCT
ajst-24888	107	2	7)computational	7)computational	NUM
ajst-24888	107	3	complexity	complexity	NOUN
ajst-24888	107	4	:	:	PUNCT
ajst-24888	107	5	the	the	DET
ajst-24888	107	6	time	time	NOUN
ajst-24888	107	7	and	and	CCONJ
ajst-24888	107	8	resource	resource	NOUN
ajst-24888	107	9	consumption	consumption	NOUN
ajst-24888	107	10	of	of	ADP
ajst-24888	107	11	model	model	NOUN
ajst-24888	107	12	training	training	NOUN
ajst-24888	107	13	and	and	CCONJ
ajst-24888	107	14	prediction	prediction	NOUN
ajst-24888	107	15	,	,	PUNCT
ajst-24888	107	16	which	which	PRON
ajst-24888	107	17	is	be	AUX
ajst-24888	107	18	particularly	particularly	ADV
ajst-24888	107	19	important	important	ADJ
ajst-24888	107	20	when	when	SCONJ
ajst-24888	107	21	dealing	deal	VERB
ajst-24888	107	22	with	with	ADP
ajst-24888	107	23	large	large	ADJ
ajst-24888	107	24	-	-	PUNCT
ajst-24888	107	25	scale	scale	NOUN
ajst-24888	107	26	data	datum	NOUN
ajst-24888	107	27	.	.	PUNCT
ajst-24888	108	1	(	(	PUNCT
ajst-24888	108	2	8)	8)	NUM
ajst-24888	108	3	robustness	robustness	NOUN
ajst-24888	108	4	:	:	PUNCT
ajst-24888	108	5	the	the	DET
ajst-24888	108	6	resistance	resistance	NOUN
ajst-24888	108	7	of	of	ADP
ajst-24888	108	8	the	the	DET
ajst-24888	108	9	model	model	NOUN
ajst-24888	108	10	to	to	ADP
ajst-24888	108	11	noisy	noisy	ADJ
ajst-24888	108	12	data	datum	NOUN
ajst-24888	108	13	and	and	CCONJ
ajst-24888	108	14	outliers	outlier	NOUN
ajst-24888	108	15	,	,	PUNCT
ajst-24888	108	16	which	which	PRON
ajst-24888	108	17	measures	measure	VERB
ajst-24888	108	18	the	the	DET
ajst-24888	108	19	stability	stability	NOUN
ajst-24888	108	20	of	of	ADP
ajst-24888	108	21	the	the	DET
ajst-24888	108	22	model	model	NOUN
ajst-24888	108	23	in	in	ADP
ajst-24888	108	24	practical	practical	ADJ
ajst-24888	108	25	applications	application	NOUN
ajst-24888	108	26	.	.	PUNCT
ajst-24888	109	1	(	(	PUNCT
ajst-24888	109	2	9	9	X
ajst-24888	109	3	)	)	PUNCT
ajst-24888	109	4	generalization	generalization	NOUN
ajst-24888	109	5	ability	ability	NOUN
ajst-24888	109	6	:	:	PUNCT
ajst-24888	109	7	the	the	DET
ajst-24888	109	8	performance	performance	NOUN
ajst-24888	109	9	of	of	ADP
ajst-24888	109	10	the	the	DET
ajst-24888	109	11	model	model	NOUN
ajst-24888	109	12	when	when	SCONJ
ajst-24888	109	13	dealing	deal	VERB
ajst-24888	109	14	with	with	ADP
ajst-24888	109	15	unseen	unseen	ADJ
ajst-24888	109	16	data	datum	NOUN
ajst-24888	109	17	,	,	PUNCT
ajst-24888	109	18	reflecting	reflect	VERB
ajst-24888	109	19	whether	whether	SCONJ
ajst-24888	109	20	the	the	DET
ajst-24888	109	21	model	model	NOUN
ajst-24888	109	22	overfits	overfit	VERB
ajst-24888	109	23	the	the	DET
ajst-24888	109	24	training	training	NOUN
ajst-24888	109	25	data	datum	NOUN
ajst-24888	109	26	.	.	PUNCT
ajst-24888	110	1	5	5	X
ajst-24888	110	2	.	.	X
ajst-24888	110	3	main	main	ADJ
ajst-24888	110	4	challenges	challenge	NOUN
ajst-24888	110	5	and	and	CCONJ
ajst-24888	110	6	future	future	ADJ
ajst-24888	110	7	directions	direction	NOUN
ajst-24888	110	8	although	although	SCONJ
ajst-24888	110	9	machine	machine	NOUN
ajst-24888	110	10	learning	learning	NOUN
ajst-24888	110	11	has	have	AUX
ajst-24888	110	12	made	make	VERB
ajst-24888	110	13	remarkable	remarkable	ADJ
ajst-24888	110	14	progress	progress	NOUN
ajst-24888	110	15	in	in	ADP
ajst-24888	110	16	lithology	lithology	NOUN
ajst-24888	110	17	identification	identification	NOUN
ajst-24888	110	18	,	,	PUNCT
ajst-24888	110	19	there	there	PRON
ajst-24888	110	20	are	be	VERB
ajst-24888	110	21	still	still	ADV
ajst-24888	110	22	many	many	ADJ
ajst-24888	110	23	challenges	challenge	NOUN
ajst-24888	110	24	.	.	PUNCT
ajst-24888	111	1	addressing	address	VERB
ajst-24888	111	2	these	these	DET
ajst-24888	111	3	challenges	challenge	NOUN
ajst-24888	111	4	and	and	CCONJ
ajst-24888	111	5	exploring	explore	VERB
ajst-24888	111	6	future	future	ADJ
ajst-24888	111	7	directions	direction	NOUN
ajst-24888	111	8	will	will	AUX
ajst-24888	111	9	further	far	ADV
ajst-24888	111	10	improve	improve	VERB
ajst-24888	111	11	the	the	DET
ajst-24888	111	12	accuracy	accuracy	NOUN
ajst-24888	111	13	and	and	CCONJ
ajst-24888	111	14	usefulness	usefulness	NOUN
ajst-24888	111	15	of	of	ADP
ajst-24888	111	16	lithology	lithology	NOUN
ajst-24888	111	17	identification	identification	NOUN
ajst-24888	111	18	.	.	PUNCT
ajst-24888	112	1	the	the	DET
ajst-24888	112	2	main	main	ADJ
ajst-24888	112	3	current	current	ADJ
ajst-24888	112	4	challenges	challenge	NOUN
ajst-24888	112	5	and	and	CCONJ
ajst-24888	112	6	future	future	ADJ
ajst-24888	112	7	directions	direction	NOUN
ajst-24888	112	8	are	be	AUX
ajst-24888	112	9	discussed	discuss	VERB
ajst-24888	112	10	in	in	ADP
ajst-24888	112	11	detail	detail	NOUN
ajst-24888	112	12	below	below	ADV
ajst-24888	112	13	.	.	PUNCT
ajst-24888	113	1	5.1	5.1	NUM
ajst-24888	113	2	.	.	PUNCT
ajst-24888	114	1	main	main	ADJ
ajst-24888	114	2	challenges	challenge	NOUN
ajst-24888	114	3	(	(	PUNCT
ajst-24888	114	4	1	1	X
ajst-24888	114	5	)	)	PUNCT
ajst-24888	114	6	data	datum	NOUN
ajst-24888	114	7	quality	quality	NOUN
ajst-24888	114	8	and	and	CCONJ
ajst-24888	114	9	quantity	quantity	NOUN
ajst-24888	114	10	:	:	PUNCT
ajst-24888	114	11	1	1	NUM
ajst-24888	114	12	)	)	PUNCT
ajst-24888	114	13	data	datum	NOUN
ajst-24888	114	14	scarcity	scarcity	NOUN
ajst-24888	114	15	:	:	PUNCT
ajst-24888	114	16	in	in	ADP
ajst-24888	114	17	some	some	DET
ajst-24888	114	18	areas	area	NOUN
ajst-24888	114	19	,	,	PUNCT
ajst-24888	114	20	obtaining	obtain	VERB
ajst-24888	114	21	high	high	ADJ
ajst-24888	114	22	-	-	PUNCT
ajst-24888	114	23	quality	quality	NOUN
ajst-24888	114	24	seismic	seismic	ADJ
ajst-24888	114	25	and	and	CCONJ
ajst-24888	114	26	logging	log	VERB
ajst-24888	114	27	data	datum	NOUN
ajst-24888	114	28	can	can	AUX
ajst-24888	114	29	be	be	AUX
ajst-24888	114	30	very	very	ADV
ajst-24888	114	31	difficult	difficult	ADJ
ajst-24888	114	32	,	,	PUNCT
ajst-24888	114	33	and	and	CCONJ
ajst-24888	114	34	data	datum	NOUN
ajst-24888	114	35	scarcity	scarcity	NOUN
ajst-24888	114	36	can	can	AUX
ajst-24888	114	37	limit	limit	VERB
ajst-24888	114	38	model	model	NOUN
ajst-24888	114	39	training	training	NOUN
ajst-24888	114	40	and	and	CCONJ
ajst-24888	114	41	application	application	NOUN
ajst-24888	114	42	.	.	PUNCT
ajst-24888	115	1	2	2	NUM
ajst-24888	115	2	)	)	PUNCT
ajst-24888	115	3	noise	noise	NOUN
ajst-24888	115	4	and	and	CCONJ
ajst-24888	115	5	outliers	outlier	NOUN
ajst-24888	115	6	:	:	PUNCT
ajst-24888	115	7	geological	geological	ADJ
ajst-24888	115	8	data	datum	NOUN
ajst-24888	115	9	often	often	ADV
ajst-24888	115	10	contain	contain	VERB
ajst-24888	115	11	noise	noise	NOUN
ajst-24888	115	12	and	and	CCONJ
ajst-24888	115	13	outliers	outlier	NOUN
ajst-24888	115	14	,	,	PUNCT
ajst-24888	115	15	and	and	CCONJ
ajst-24888	115	16	these	these	DET
ajst-24888	115	17	inaccurate	inaccurate	ADJ
ajst-24888	115	18	data	datum	NOUN
ajst-24888	115	19	will	will	AUX
ajst-24888	115	20	affect	affect	VERB
ajst-24888	115	21	the	the	DET
ajst-24888	115	22	performance	performance	NOUN
ajst-24888	115	23	of	of	ADP
ajst-24888	115	24	the	the	DET
ajst-24888	115	25	model	model	NOUN
ajst-24888	115	26	,	,	PUNCT
ajst-24888	115	27	requiring	require	VERB
ajst-24888	115	28	effective	effective	ADJ
ajst-24888	115	29	data	datum	NOUN
ajst-24888	115	30	cleaning	clean	VERB
ajst-24888	115	31	and	and	CCONJ
ajst-24888	115	32	preprocessing	preprocessing	NOUN
ajst-24888	115	33	methods	method	NOUN
ajst-24888	115	34	.	.	PUNCT
ajst-24888	116	1	3	3	X
ajst-24888	116	2	)	)	PUNCT
ajst-24888	116	3	multi	multi	ADJ
ajst-24888	116	4	-	-	ADJ
ajst-24888	116	5	source	source	ADJ
ajst-24888	116	6	heterogeneous	heterogeneous	ADJ
ajst-24888	116	7	data	datum	NOUN
ajst-24888	116	8	fusion	fusion	NOUN
ajst-24888	116	9	:	:	PUNCT
ajst-24888	116	10	seismic	seismic	ADJ
ajst-24888	116	11	data	datum	NOUN
ajst-24888	116	12	,	,	PUNCT
ajst-24888	116	13	logging	log	VERB
ajst-24888	116	14	data	datum	NOUN
ajst-24888	116	15	and	and	CCONJ
ajst-24888	116	16	petrophysical	petrophysical	ADJ
ajst-24888	116	17	experiment	experiment	NOUN
ajst-24888	116	18	data	datum	NOUN
ajst-24888	116	19	come	come	VERB
ajst-24888	116	20	from	from	ADP
ajst-24888	116	21	different	different	ADJ
ajst-24888	116	22	sources	source	NOUN
ajst-24888	116	23	and	and	CCONJ
ajst-24888	116	24	in	in	ADP
ajst-24888	116	25	various	various	ADJ
ajst-24888	116	26	formats	format	NOUN
ajst-24888	116	27	,	,	PUNCT
ajst-24888	116	28	so	so	ADV
ajst-24888	116	29	how	how	SCONJ
ajst-24888	116	30	to	to	PART
ajst-24888	116	31	effectively	effectively	ADV
ajst-24888	116	32	merge	merge	VERB
ajst-24888	116	33	and	and	CCONJ
ajst-24888	116	34	utilize	utilize	VERB
ajst-24888	116	35	these	these	DET
ajst-24888	116	36	heterogeneous	heterogeneous	ADJ
ajst-24888	116	37	data	datum	NOUN
ajst-24888	116	38	is	be	AUX
ajst-24888	116	39	a	a	DET
ajst-24888	116	40	challenge	challenge	NOUN
ajst-24888	116	41	.	.	PUNCT
ajst-24888	117	1	(	(	PUNCT
ajst-24888	117	2	2	2	X
ajst-24888	117	3	)	)	PUNCT
ajst-24888	117	4	model	model	NOUN
ajst-24888	117	5	complexity	complexity	NOUN
ajst-24888	117	6	and	and	CCONJ
ajst-24888	117	7	interpretability	interpretability	NOUN
ajst-24888	117	8	:	:	PUNCT
ajst-24888	117	9	1	1	X
ajst-24888	117	10	)	)	PUNCT
ajst-24888	117	11	training	training	NOUN
ajst-24888	117	12	of	of	ADP
ajst-24888	117	13	complex	complex	ADJ
ajst-24888	117	14	models	model	NOUN
ajst-24888	117	15	:	:	PUNCT
ajst-24888	117	16	when	when	SCONJ
ajst-24888	117	17	complex	complex	ADJ
ajst-24888	117	18	models	model	NOUN
ajst-24888	117	19	such	such	ADJ
ajst-24888	117	20	as	as	ADP
ajst-24888	117	21	deep	deep	ADJ
ajst-24888	117	22	learning	learning	NOUN
ajst-24888	117	23	process	process	NOUN
ajst-24888	117	24	large	large	ADJ
ajst-24888	117	25	-	-	PUNCT
ajst-24888	117	26	scale	scale	NOUN
ajst-24888	117	27	data	datum	NOUN
ajst-24888	117	28	,	,	PUNCT
ajst-24888	117	29	the	the	DET
ajst-24888	117	30	training	training	NOUN
ajst-24888	117	31	time	time	NOUN
ajst-24888	117	32	is	be	AUX
ajst-24888	117	33	long	long	ADJ
ajst-24888	117	34	and	and	CCONJ
ajst-24888	117	35	the	the	DET
ajst-24888	117	36	computing	compute	VERB
ajst-24888	117	37	resource	resource	NOUN
ajst-24888	117	38	consumption	consumption	NOUN
ajst-24888	117	39	is	be	AUX
ajst-24888	117	40	large	large	ADJ
ajst-24888	117	41	,	,	PUNCT
ajst-24888	117	42	which	which	PRON
ajst-24888	117	43	requires	require	VERB
ajst-24888	117	44	the	the	DET
ajst-24888	117	45	support	support	NOUN
ajst-24888	117	46	of	of	ADP
ajst-24888	117	47	high	high	ADJ
ajst-24888	117	48	-	-	PUNCT
ajst-24888	117	49	performance	performance	NOUN
ajst-24888	117	50	computing	computing	NOUN
ajst-24888	117	51	platforms	platform	NOUN
ajst-24888	117	52	.	.	PUNCT
ajst-24888	118	1	2	2	X
ajst-24888	118	2	)	)	PUNCT
ajst-24888	118	3	black	black	ADJ
ajst-24888	118	4	-	-	PUNCT
ajst-24888	118	5	box	box	NOUN
ajst-24888	118	6	nature	nature	NOUN
ajst-24888	118	7	of	of	ADP
ajst-24888	118	8	models	model	NOUN
ajst-24888	118	9	:	:	PUNCT
ajst-24888	118	10	complex	complex	ADJ
ajst-24888	118	11	models	model	NOUN
ajst-24888	118	12	,	,	PUNCT
ajst-24888	118	13	especially	especially	ADV
ajst-24888	118	14	deep	deep	ADJ
ajst-24888	118	15	learning	learning	NOUN
ajst-24888	118	16	models	model	NOUN
ajst-24888	118	17	,	,	PUNCT
ajst-24888	118	18	are	be	AUX
ajst-24888	118	19	often	often	ADV
ajst-24888	118	20	considered	consider	VERB
ajst-24888	118	21	"	"	PUNCT
ajst-24888	118	22	black	black	ADJ
ajst-24888	118	23	boxes	box	NOUN
ajst-24888	118	24	"	"	PUNCT
ajst-24888	118	25	that	that	PRON
ajst-24888	118	26	have	have	VERB
ajst-24888	118	27	difficulty	difficulty	NOUN
ajst-24888	118	28	explaining	explain	VERB
ajst-24888	118	29	their	their	PRON
ajst-24888	118	30	internal	internal	ADJ
ajst-24888	118	31	mechanisms	mechanism	NOUN
ajst-24888	118	32	and	and	CCONJ
ajst-24888	118	33	predictions	prediction	NOUN
ajst-24888	118	34	.	.	PUNCT
ajst-24888	119	1	this	this	PRON
ajst-24888	119	2	is	be	AUX
ajst-24888	119	3	particularly	particularly	ADV
ajst-24888	119	4	important	important	ADJ
ajst-24888	119	5	in	in	ADP
ajst-24888	119	6	lithology	lithology	NOUN
ajst-24888	119	7	identification	identification	NOUN
ajst-24888	119	8	,	,	PUNCT
ajst-24888	119	9	as	as	SCONJ
ajst-24888	119	10	geologists	geologist	NOUN
ajst-24888	119	11	need	need	VERB
ajst-24888	119	12	to	to	PART
ajst-24888	119	13	understand	understand	VERB
ajst-24888	119	14	the	the	DET
ajst-24888	119	15	decision	decision	NOUN
ajst-24888	119	16	-	-	PUNCT
ajst-24888	119	17	making	make	VERB
ajst-24888	119	18	process	process	NOUN
ajst-24888	119	19	of	of	ADP
ajst-24888	119	20	the	the	DET
ajst-24888	119	21	model	model	NOUN
ajst-24888	119	22	.	.	PUNCT
ajst-24888	120	1	(	(	PUNCT
ajst-24888	120	2	3	3	X
ajst-24888	120	3	)	)	PUNCT
ajst-24888	120	4	generalization	generalization	NOUN
ajst-24888	120	5	ability	ability	NOUN
ajst-24888	120	6	and	and	CCONJ
ajst-24888	120	7	overfitting	overfitting	NOUN
ajst-24888	120	8	:	:	PUNCT
ajst-24888	120	9	1	1	NUM
ajst-24888	120	10	)	)	PUNCT
ajst-24888	120	11	overfitting	overfitte	VERB
ajst-24888	120	12	problem	problem	NOUN
ajst-24888	120	13	:	:	PUNCT
ajst-24888	120	14	the	the	DET
ajst-24888	120	15	model	model	NOUN
ajst-24888	120	16	performs	perform	VERB
ajst-24888	120	17	well	well	ADV
ajst-24888	120	18	on	on	ADP
ajst-24888	120	19	training	training	NOUN
ajst-24888	120	20	data	datum	NOUN
ajst-24888	120	21	,	,	PUNCT
ajst-24888	120	22	but	but	CCONJ
ajst-24888	120	23	poorly	poorly	ADV
ajst-24888	120	24	on	on	ADP
ajst-24888	120	25	test	test	NOUN
ajst-24888	120	26	data	datum	NOUN
ajst-24888	120	27	,	,	PUNCT
ajst-24888	120	28	indicating	indicate	VERB
ajst-24888	120	29	that	that	SCONJ
ajst-24888	120	30	the	the	DET
ajst-24888	120	31	model	model	NOUN
ajst-24888	120	32	may	may	AUX
ajst-24888	120	33	be	be	AUX
ajst-24888	120	34	overfitting	overfitte	VERB
ajst-24888	120	35	.	.	PUNCT
ajst-24888	121	1	effective	effective	ADJ
ajst-24888	121	2	regularization	regularization	NOUN
ajst-24888	121	3	techniques	technique	NOUN
ajst-24888	121	4	and	and	CCONJ
ajst-24888	121	5	model	model	NOUN
ajst-24888	121	6	validation	validation	NOUN
ajst-24888	121	7	methods	method	NOUN
ajst-24888	121	8	are	be	AUX
ajst-24888	121	9	needed	need	VERB
ajst-24888	121	10	to	to	PART
ajst-24888	121	11	improve	improve	VERB
ajst-24888	121	12	the	the	DET
ajst-24888	121	13	generalization	generalization	NOUN
ajst-24888	121	14	ability	ability	NOUN
ajst-24888	121	15	of	of	ADP
ajst-24888	121	16	the	the	DET
ajst-24888	121	17	model	model	NOUN
ajst-24888	121	18	.	.	PUNCT
ajst-24888	122	1	2	2	NUM
ajst-24888	122	2	)	)	PUNCT
ajst-24888	122	3	diversity	diversity	NOUN
ajst-24888	122	4	and	and	CCONJ
ajst-24888	122	5	heterogeneity	heterogeneity	NOUN
ajst-24888	122	6	:	:	PUNCT
ajst-24888	122	7	the	the	DET
ajst-24888	122	8	geological	geological	ADJ
ajst-24888	122	9	conditions	condition	NOUN
ajst-24888	122	10	of	of	ADP
ajst-24888	122	11	different	different	ADJ
ajst-24888	122	12	regions	region	NOUN
ajst-24888	122	13	vary	vary	VERB
ajst-24888	122	14	greatly	greatly	ADV
ajst-24888	122	15	,	,	PUNCT
ajst-24888	122	16	and	and	CCONJ
ajst-24888	122	17	the	the	DET
ajst-24888	122	18	model	model	NOUN
ajst-24888	122	19	needs	need	VERB
ajst-24888	122	20	to	to	PART
ajst-24888	122	21	be	be	AUX
ajst-24888	122	22	able	able	ADJ
ajst-24888	122	23	to	to	PART
ajst-24888	122	24	handle	handle	VERB
ajst-24888	122	25	diversity	diversity	NOUN
ajst-24888	122	26	and	and	CCONJ
ajst-24888	122	27	heterogeneity	heterogeneity	NOUN
ajst-24888	122	28	to	to	PART
ajst-24888	122	29	ensure	ensure	VERB
ajst-24888	122	30	applicability	applicability	NOUN
ajst-24888	122	31	in	in	ADP
ajst-24888	122	32	different	different	ADJ
ajst-24888	122	33	geological	geological	ADJ
ajst-24888	122	34	contexts	contexts	NOUN
ajst-24888	122	35	.	.	PUNCT
ajst-24888	123	1	(	(	PUNCT
ajst-24888	123	2	4	4	X
ajst-24888	123	3	)	)	PUNCT
ajst-24888	123	4	real	real	ADJ
ajst-24888	123	5	-	-	PUNCT
ajst-24888	123	6	time	time	NOUN
ajst-24888	123	7	processing	processing	NOUN
ajst-24888	123	8	and	and	CCONJ
ajst-24888	123	9	application	application	NOUN
ajst-24888	123	10	:	:	PUNCT
ajst-24888	123	11	1	1	NUM
ajst-24888	123	12	)	)	PUNCT
ajst-24888	123	13	real	real	ADJ
ajst-24888	123	14	-	-	PUNCT
ajst-24888	123	15	time	time	NOUN
ajst-24888	123	16	data	datum	NOUN
ajst-24888	123	17	processing	processing	NOUN
ajst-24888	123	18	:	:	PUNCT
ajst-24888	123	19	in	in	ADP
ajst-24888	123	20	practical	practical	ADJ
ajst-24888	123	21	applications	application	NOUN
ajst-24888	123	22	,	,	PUNCT
ajst-24888	123	23	real	real	ADJ
ajst-24888	123	24	-	-	PUNCT
ajst-24888	123	25	time	time	NOUN
ajst-24888	123	26	processing	processing	NOUN
ajst-24888	123	27	and	and	CCONJ
ajst-24888	123	28	analysis	analysis	NOUN
ajst-24888	123	29	of	of	ADP
ajst-24888	123	30	data	datum	NOUN
ajst-24888	123	31	is	be	AUX
ajst-24888	123	32	an	an	DET
ajst-24888	123	33	important	important	ADJ
ajst-24888	123	34	requirement	requirement	NOUN
ajst-24888	123	35	,	,	PUNCT
ajst-24888	123	36	especially	especially	ADV
ajst-24888	123	37	in	in	ADP
ajst-24888	123	38	oil	oil	NOUN
ajst-24888	123	39	and	and	CCONJ
ajst-24888	123	40	gas	gas	NOUN
ajst-24888	123	41	exploration	exploration	NOUN
ajst-24888	123	42	and	and	CCONJ
ajst-24888	123	43	development	development	NOUN
ajst-24888	123	44	,	,	PUNCT
ajst-24888	123	45	which	which	PRON
ajst-24888	123	46	requires	require	VERB
ajst-24888	123	47	immediate	immediate	ADJ
ajst-24888	123	48	decision	decision	NOUN
ajst-24888	123	49	making	making	NOUN
ajst-24888	123	50	and	and	CCONJ
ajst-24888	123	51	124	124	NUM
ajst-24888	123	52	response	response	NOUN
ajst-24888	123	53	.	.	PUNCT
ajst-24888	124	1	2	2	NUM
ajst-24888	124	2	)	)	PUNCT
ajst-24888	124	3	deployment	deployment	NOUN
ajst-24888	124	4	and	and	CCONJ
ajst-24888	124	5	maintenance	maintenance	NOUN
ajst-24888	124	6	:	:	PUNCT
ajst-24888	124	7	deploying	deploy	VERB
ajst-24888	124	8	machine	machine	NOUN
ajst-24888	124	9	learning	learning	NOUN
ajst-24888	124	10	models	model	NOUN
ajst-24888	124	11	into	into	ADP
ajst-24888	124	12	actual	actual	ADJ
ajst-24888	124	13	production	production	NOUN
ajst-24888	124	14	environments	environment	NOUN
ajst-24888	124	15	and	and	CCONJ
ajst-24888	124	16	conducting	conduct	VERB
ajst-24888	124	17	ongoing	ongoing	ADJ
ajst-24888	124	18	monitoring	monitoring	NOUN
ajst-24888	124	19	and	and	CCONJ
ajst-24888	124	20	maintenance	maintenance	NOUN
ajst-24888	124	21	to	to	PART
ajst-24888	124	22	ensure	ensure	VERB
ajst-24888	124	23	model	model	NOUN
ajst-24888	124	24	stability	stability	NOUN
ajst-24888	124	25	and	and	CCONJ
ajst-24888	124	26	performance	performance	NOUN
ajst-24888	124	27	is	be	AUX
ajst-24888	124	28	a	a	DET
ajst-24888	124	29	real	real	ADJ
ajst-24888	124	30	challenge	challenge	NOUN
ajst-24888	124	31	.	.	PUNCT
ajst-24888	125	1	5.2	5.2	NUM
ajst-24888	125	2	.	.	PUNCT
ajst-24888	126	1	future	future	ADJ
ajst-24888	126	2	development	development	NOUN
ajst-24888	126	3	direction	direction	NOUN
ajst-24888	126	4	(	(	PUNCT
ajst-24888	126	5	1	1	X
ajst-24888	126	6	)	)	PUNCT
ajst-24888	126	7	data	datum	NOUN
ajst-24888	126	8	enhancement	enhancement	NOUN
ajst-24888	126	9	and	and	CCONJ
ajst-24888	126	10	synthesis	synthesis	NOUN
ajst-24888	126	11	:	:	PUNCT
ajst-24888	126	12	1	1	NUM
ajst-24888	126	13	)	)	PUNCT
ajst-24888	126	14	data	datum	NOUN
ajst-24888	126	15	enhancement	enhancement	NOUN
ajst-24888	126	16	technology	technology	NOUN
ajst-24888	126	17	:	:	PUNCT
ajst-24888	126	18	through	through	ADP
ajst-24888	126	19	data	data	NOUN
ajst-24888	126	20	enhancement	enhancement	NOUN
ajst-24888	126	21	technology	technology	NOUN
ajst-24888	126	22	,	,	PUNCT
ajst-24888	126	23	such	such	ADJ
ajst-24888	126	24	as	as	ADP
ajst-24888	126	25	random	random	ADJ
ajst-24888	126	26	transformation	transformation	NOUN
ajst-24888	126	27	,	,	PUNCT
ajst-24888	126	28	noise	noise	NOUN
ajst-24888	126	29	injection	injection	NOUN
ajst-24888	126	30	,	,	PUNCT
ajst-24888	126	31	etc	etc	X
ajst-24888	126	32	.	.	X
ajst-24888	126	33	,	,	PUNCT
ajst-24888	126	34	to	to	PART
ajst-24888	126	35	expand	expand	VERB
ajst-24888	126	36	the	the	DET
ajst-24888	126	37	existing	exist	VERB
ajst-24888	126	38	data	datum	NOUN
ajst-24888	126	39	set	set	VERB
ajst-24888	126	40	and	and	CCONJ
ajst-24888	126	41	improve	improve	VERB
ajst-24888	126	42	the	the	DET
ajst-24888	126	43	robustness	robustness	NOUN
ajst-24888	126	44	of	of	ADP
ajst-24888	126	45	the	the	DET
ajst-24888	126	46	model	model	NOUN
ajst-24888	126	47	.	.	PUNCT
ajst-24888	127	1	2	2	X
ajst-24888	127	2	)	)	PUNCT
ajst-24888	127	3	generate	generate	VERB
ajst-24888	127	4	adversarial	adversarial	ADJ
ajst-24888	127	5	network	network	NOUN
ajst-24888	127	6	(	(	PUNCT
ajst-24888	127	7	gan	gan	PROPN
ajst-24888	127	8	):	):	PUNCT
ajst-24888	127	9	use	use	NOUN
ajst-24888	127	10	gan	gin	VERB
ajst-24888	127	11	to	to	PART
ajst-24888	127	12	generate	generate	VERB
ajst-24888	127	13	synthetic	synthetic	ADJ
ajst-24888	127	14	data	datum	NOUN
ajst-24888	127	15	to	to	PART
ajst-24888	127	16	make	make	VERB
ajst-24888	127	17	up	up	ADP
ajst-24888	127	18	for	for	ADP
ajst-24888	127	19	the	the	DET
ajst-24888	127	20	problem	problem	NOUN
ajst-24888	127	21	of	of	ADP
ajst-24888	127	22	insufficient	insufficient	ADJ
ajst-24888	127	23	data	datum	NOUN
ajst-24888	127	24	and	and	CCONJ
ajst-24888	127	25	provide	provide	VERB
ajst-24888	127	26	more	more	ADJ
ajst-24888	127	27	samples	sample	NOUN
ajst-24888	127	28	for	for	ADP
ajst-24888	127	29	model	model	NOUN
ajst-24888	127	30	training	training	NOUN
ajst-24888	127	31	.	.	PUNCT
ajst-24888	128	1	(	(	PUNCT
ajst-24888	128	2	2	2	X
ajst-24888	128	3	)	)	PUNCT
ajst-24888	128	4	model	model	NOUN
ajst-24888	128	5	interpretability	interpretability	NOUN
ajst-24888	128	6	and	and	CCONJ
ajst-24888	128	7	visualization	visualization	NOUN
ajst-24888	128	8	:	:	PUNCT
ajst-24888	128	9	1	1	NUM
ajst-24888	128	10	)	)	PUNCT
ajst-24888	128	11	interpretative	interpretative	ADJ
ajst-24888	128	12	models	model	NOUN
ajst-24888	128	13	:	:	PUNCT
ajst-24888	128	14	develop	develop	VERB
ajst-24888	128	15	models	model	NOUN
ajst-24888	128	16	with	with	ADP
ajst-24888	128	17	high	high	ADJ
ajst-24888	128	18	interpretative	interpretative	ADJ
ajst-24888	128	19	properties	property	NOUN
ajst-24888	128	20	that	that	PRON
ajst-24888	128	21	enable	enable	VERB
ajst-24888	128	22	geologists	geologist	NOUN
ajst-24888	128	23	to	to	PART
ajst-24888	128	24	understand	understand	VERB
ajst-24888	128	25	and	and	CCONJ
ajst-24888	128	26	trust	trust	VERB
ajst-24888	128	27	the	the	DET
ajst-24888	128	28	decision	decision	NOUN
ajst-24888	128	29	-	-	PUNCT
ajst-24888	128	30	making	make	VERB
ajst-24888	128	31	process	process	NOUN
ajst-24888	128	32	of	of	ADP
ajst-24888	128	33	the	the	DET
ajst-24888	128	34	model	model	NOUN
ajst-24888	128	35	.	.	PUNCT
ajst-24888	129	1	for	for	ADP
ajst-24888	129	2	example	example	NOUN
ajst-24888	129	3	,	,	PUNCT
ajst-24888	129	4	interpretable	interpretable	ADJ
ajst-24888	129	5	artificial	artificial	ADJ
ajst-24888	129	6	intelligence	intelligence	NOUN
ajst-24888	129	7	(	(	PUNCT
ajst-24888	129	8	xai	xai	PROPN
ajst-24888	129	9	)	)	PUNCT
ajst-24888	129	10	technology	technology	NOUN
ajst-24888	129	11	is	be	AUX
ajst-24888	129	12	used	use	VERB
ajst-24888	129	13	to	to	PART
ajst-24888	129	14	provide	provide	VERB
ajst-24888	129	15	transparency	transparency	NOUN
ajst-24888	129	16	in	in	ADP
ajst-24888	129	17	model	model	NOUN
ajst-24888	129	18	decisions	decision	NOUN
ajst-24888	129	19	.	.	PUNCT
ajst-24888	130	1	2	2	X
ajst-24888	130	2	)	)	PUNCT
ajst-24888	130	3	visualization	visualization	NOUN
ajst-24888	130	4	tools	tool	NOUN
ajst-24888	130	5	:	:	PUNCT
ajst-24888	130	6	design	design	VERB
ajst-24888	130	7	intuitive	intuitive	ADJ
ajst-24888	130	8	visualization	visualization	NOUN
ajst-24888	130	9	tools	tool	NOUN
ajst-24888	130	10	that	that	PRON
ajst-24888	130	11	combine	combine	VERB
ajst-24888	130	12	model	model	NOUN
ajst-24888	130	13	predictions	prediction	NOUN
ajst-24888	130	14	with	with	ADP
ajst-24888	130	15	geological	geological	ADJ
ajst-24888	130	16	data	datum	NOUN
ajst-24888	130	17	to	to	PART
ajst-24888	130	18	help	help	VERB
ajst-24888	130	19	geologists	geologist	NOUN
ajst-24888	130	20	better	well	ADV
ajst-24888	130	21	understand	understand	VERB
ajst-24888	130	22	and	and	CCONJ
ajst-24888	130	23	apply	apply	VERB
ajst-24888	130	24	the	the	DET
ajst-24888	130	25	results	result	NOUN
ajst-24888	130	26	.	.	PUNCT
ajst-24888	131	1	(	(	PUNCT
ajst-24888	131	2	3	3	X
ajst-24888	131	3	)	)	PUNCT
ajst-24888	131	4	multi	multi	ADJ
ajst-24888	131	5	-	-	ADJ
ajst-24888	131	6	source	source	NOUN
ajst-24888	131	7	data	datum	NOUN
ajst-24888	131	8	fusion	fusion	NOUN
ajst-24888	131	9	:	:	PUNCT
ajst-24888	131	10	1	1	NUM
ajst-24888	131	11	)	)	PUNCT
ajst-24888	131	12	cross	cross	ADJ
ajst-24888	131	13	-	-	ADJ
ajst-24888	131	14	domain	domain	ADJ
ajst-24888	131	15	data	datum	NOUN
ajst-24888	131	16	fusion	fusion	NOUN
ajst-24888	131	17	:	:	PUNCT
ajst-24888	131	18	develop	develop	VERB
ajst-24888	131	19	effective	effective	ADJ
ajst-24888	131	20	methods	method	NOUN
ajst-24888	131	21	and	and	CCONJ
ajst-24888	131	22	algorithms	algorithm	NOUN
ajst-24888	131	23	to	to	PART
ajst-24888	131	24	integrate	integrate	VERB
ajst-24888	131	25	multi	multi	ADJ
ajst-24888	131	26	-	-	ADJ
ajst-24888	131	27	source	source	ADJ
ajst-24888	131	28	heterogeneous	heterogeneous	ADJ
ajst-24888	131	29	data	datum	NOUN
ajst-24888	131	30	such	such	ADJ
ajst-24888	131	31	as	as	ADP
ajst-24888	131	32	seismic	seismic	ADJ
ajst-24888	131	33	data	datum	NOUN
ajst-24888	131	34	,	,	PUNCT
ajst-24888	131	35	logging	log	VERB
ajst-24888	131	36	data	datum	NOUN
ajst-24888	131	37	and	and	CCONJ
ajst-24888	131	38	geological	geological	ADJ
ajst-24888	131	39	maps	map	NOUN
ajst-24888	131	40	to	to	PART
ajst-24888	131	41	improve	improve	VERB
ajst-24888	131	42	the	the	DET
ajst-24888	131	43	accuracy	accuracy	NOUN
ajst-24888	131	44	and	and	CCONJ
ajst-24888	131	45	generalization	generalization	NOUN
ajst-24888	131	46	ability	ability	NOUN
ajst-24888	131	47	of	of	ADP
ajst-24888	131	48	the	the	DET
ajst-24888	131	49	model	model	NOUN
ajst-24888	131	50	.	.	PUNCT
ajst-24888	132	1	2	2	NUM
ajst-24888	132	2	)	)	PUNCT
ajst-24888	132	3	data	datum	NOUN
ajst-24888	132	4	assimilation	assimilation	NOUN
ajst-24888	132	5	technology	technology	NOUN
ajst-24888	132	6	:	:	PUNCT
ajst-24888	132	7	data	data	NOUN
ajst-24888	132	8	assimilation	assimilation	NOUN
ajst-24888	132	9	technology	technology	NOUN
ajst-24888	132	10	is	be	AUX
ajst-24888	132	11	used	use	VERB
ajst-24888	132	12	to	to	PART
ajst-24888	132	13	combine	combine	VERB
ajst-24888	132	14	physical	physical	ADJ
ajst-24888	132	15	models	model	NOUN
ajst-24888	132	16	and	and	CCONJ
ajst-24888	132	17	observed	observe	VERB
ajst-24888	132	18	data	datum	NOUN
ajst-24888	132	19	to	to	PART
ajst-24888	132	20	improve	improve	VERB
ajst-24888	132	21	data	data	NOUN
ajst-24888	132	22	integrity	integrity	NOUN
ajst-24888	132	23	and	and	CCONJ
ajst-24888	132	24	consistency	consistency	NOUN
ajst-24888	132	25	.	.	PUNCT
ajst-24888	133	1	(	(	PUNCT
ajst-24888	133	2	4	4	X
ajst-24888	133	3	)	)	PUNCT
ajst-24888	133	4	online	online	ADJ
ajst-24888	133	5	learning	learning	NOUN
ajst-24888	133	6	and	and	CCONJ
ajst-24888	133	7	transfer	transfer	VERB
ajst-24888	133	8	learning	learning	NOUN
ajst-24888	133	9	:	:	PUNCT
ajst-24888	133	10	1	1	X
ajst-24888	133	11	)	)	PUNCT
ajst-24888	133	12	online	online	ADJ
ajst-24888	133	13	learning	learning	NOUN
ajst-24888	133	14	:	:	PUNCT
ajst-24888	133	15	develop	develop	VERB
ajst-24888	133	16	online	online	ADJ
ajst-24888	133	17	learning	learn	VERB
ajst-24888	133	18	algorithms	algorithm	NOUN
ajst-24888	133	19	to	to	PART
ajst-24888	133	20	enable	enable	VERB
ajst-24888	133	21	the	the	DET
ajst-24888	133	22	model	model	NOUN
ajst-24888	133	23	to	to	PART
ajst-24888	133	24	update	update	VERB
ajst-24888	133	25	and	and	CCONJ
ajst-24888	133	26	adapt	adapt	VERB
ajst-24888	133	27	to	to	ADP
ajst-24888	133	28	new	new	ADJ
ajst-24888	133	29	data	datum	NOUN
ajst-24888	133	30	in	in	ADP
ajst-24888	133	31	real	real	ADJ
ajst-24888	133	32	time	time	NOUN
ajst-24888	133	33	,	,	PUNCT
ajst-24888	133	34	and	and	CCONJ
ajst-24888	133	35	improve	improve	VERB
ajst-24888	133	36	the	the	DET
ajst-24888	133	37	model	model	NOUN
ajst-24888	133	38	's	's	PART
ajst-24888	133	39	immediate	immediate	ADJ
ajst-24888	133	40	response	response	NOUN
ajst-24888	133	41	ability	ability	NOUN
ajst-24888	133	42	.	.	PUNCT
ajst-24888	134	1	2	2	X
ajst-24888	134	2	)	)	PUNCT
ajst-24888	134	3	transfer	transfer	NOUN
ajst-24888	134	4	learning	learning	NOUN
ajst-24888	134	5	:	:	PUNCT
ajst-24888	134	6	through	through	ADP
ajst-24888	134	7	transfer	transfer	NOUN
ajst-24888	134	8	learning	learn	VERB
ajst-24888	134	9	technology	technology	NOUN
ajst-24888	134	10	,	,	PUNCT
ajst-24888	134	11	the	the	DET
ajst-24888	134	12	model	model	NOUN
ajst-24888	134	13	trained	train	VERB
ajst-24888	134	14	in	in	ADP
ajst-24888	134	15	one	one	NUM
ajst-24888	134	16	region	region	NOUN
ajst-24888	134	17	is	be	AUX
ajst-24888	134	18	applied	apply	VERB
ajst-24888	134	19	to	to	ADP
ajst-24888	134	20	other	other	ADJ
ajst-24888	134	21	regions	region	NOUN
ajst-24888	134	22	to	to	PART
ajst-24888	134	23	improve	improve	VERB
ajst-24888	134	24	the	the	DET
ajst-24888	134	25	adaptability	adaptability	NOUN
ajst-24888	134	26	and	and	CCONJ
ajst-24888	134	27	generalization	generalization	NOUN
ajst-24888	134	28	ability	ability	NOUN
ajst-24888	134	29	of	of	ADP
ajst-24888	134	30	the	the	DET
ajst-24888	134	31	model	model	NOUN
ajst-24888	134	32	.	.	PUNCT
ajst-24888	135	1	by	by	ADP
ajst-24888	135	2	addressing	address	VERB
ajst-24888	135	3	current	current	ADJ
ajst-24888	135	4	challenges	challenge	NOUN
ajst-24888	135	5	and	and	CCONJ
ajst-24888	135	6	exploring	explore	VERB
ajst-24888	135	7	future	future	ADJ
ajst-24888	135	8	directions	direction	NOUN
ajst-24888	135	9	,	,	PUNCT
ajst-24888	135	10	the	the	DET
ajst-24888	135	11	application	application	NOUN
ajst-24888	135	12	of	of	ADP
ajst-24888	135	13	machine	machine	NOUN
ajst-24888	135	14	learning	learning	NOUN
ajst-24888	135	15	in	in	ADP
ajst-24888	135	16	lithology	lithology	NOUN
ajst-24888	135	17	identification	identification	NOUN
ajst-24888	135	18	will	will	AUX
ajst-24888	135	19	continue	continue	VERB
ajst-24888	135	20	to	to	PART
ajst-24888	135	21	improve	improve	VERB
ajst-24888	135	22	,	,	PUNCT
ajst-24888	135	23	providing	provide	VERB
ajst-24888	135	24	more	more	ADV
ajst-24888	135	25	powerful	powerful	ADJ
ajst-24888	135	26	tools	tool	NOUN
ajst-24888	135	27	and	and	CCONJ
ajst-24888	135	28	methods	method	NOUN
ajst-24888	135	29	for	for	ADP
ajst-24888	135	30	geological	geological	ADJ
ajst-24888	135	31	research	research	NOUN
ajst-24888	135	32	and	and	CCONJ
ajst-24888	135	33	oil	oil	NOUN
ajst-24888	135	34	exploration	exploration	NOUN
ajst-24888	135	35	.	.	PUNCT
ajst-24888	136	1	6	6	X
ajst-24888	136	2	.	.	X
ajst-24888	136	3	conclusion	conclusion	NOUN
ajst-24888	136	4	(	(	PUNCT
ajst-24888	136	5	1	1	X
ajst-24888	136	6	)	)	PUNCT
ajst-24888	136	7	machine	machine	NOUN
ajst-24888	136	8	learning	learning	NOUN
ajst-24888	136	9	has	have	AUX
ajst-24888	136	10	shown	show	VERB
ajst-24888	136	11	great	great	ADJ
ajst-24888	136	12	potential	potential	ADJ
ajst-24888	136	13	and	and	CCONJ
ajst-24888	136	14	advantages	advantage	NOUN
ajst-24888	136	15	in	in	ADP
ajst-24888	136	16	lithology	lithology	NOUN
ajst-24888	136	17	identification	identification	NOUN
ajst-24888	136	18	.	.	PUNCT
ajst-24888	137	1	by	by	ADP
ajst-24888	137	2	utilizing	utilize	VERB
ajst-24888	137	3	a	a	DET
ajst-24888	137	4	variety	variety	NOUN
ajst-24888	137	5	of	of	ADP
ajst-24888	137	6	machine	machine	NOUN
ajst-24888	137	7	learning	learning	NOUN
ajst-24888	137	8	methods	method	NOUN
ajst-24888	137	9	,	,	PUNCT
ajst-24888	137	10	geologists	geologist	NOUN
ajst-24888	137	11	can	can	AUX
ajst-24888	137	12	automatically	automatically	ADV
ajst-24888	137	13	extract	extract	VERB
ajst-24888	137	14	features	feature	NOUN
ajst-24888	137	15	from	from	ADP
ajst-24888	137	16	complex	complex	ADJ
ajst-24888	137	17	seismic	seismic	ADJ
ajst-24888	137	18	and	and	CCONJ
ajst-24888	137	19	logging	log	VERB
ajst-24888	137	20	data	datum	NOUN
ajst-24888	137	21	to	to	PART
ajst-24888	137	22	achieve	achieve	VERB
ajst-24888	137	23	efficient	efficient	ADJ
ajst-24888	137	24	and	and	CCONJ
ajst-24888	137	25	accurate	accurate	ADJ
ajst-24888	137	26	lithology	lithology	NOUN
ajst-24888	137	27	classification	classification	NOUN
ajst-24888	137	28	.	.	PUNCT
ajst-24888	138	1	these	these	DET
ajst-24888	138	2	methods	method	NOUN
ajst-24888	138	3	include	include	VERB
ajst-24888	138	4	supervised	supervised	ADJ
ajst-24888	138	5	learning	learning	NOUN
ajst-24888	138	6	,	,	PUNCT
ajst-24888	138	7	unsupervised	unsupervised	ADJ
ajst-24888	138	8	learning	learning	NOUN
ajst-24888	138	9	,	,	PUNCT
ajst-24888	138	10	and	and	CCONJ
ajst-24888	138	11	deep	deep	ADJ
ajst-24888	138	12	learning	learning	NOUN
ajst-24888	138	13	,	,	PUNCT
ajst-24888	138	14	each	each	PRON
ajst-24888	138	15	of	of	ADP
ajst-24888	138	16	which	which	PRON
ajst-24888	138	17	is	be	AUX
ajst-24888	138	18	suitable	suitable	ADJ
ajst-24888	138	19	for	for	ADP
ajst-24888	138	20	different	different	ADJ
ajst-24888	138	21	data	datum	NOUN
ajst-24888	138	22	types	type	NOUN
ajst-24888	138	23	and	and	CCONJ
ajst-24888	138	24	task	task	NOUN
ajst-24888	138	25	requirements	requirement	NOUN
ajst-24888	138	26	,	,	PUNCT
ajst-24888	138	27	providing	provide	VERB
ajst-24888	138	28	diversified	diversified	ADJ
ajst-24888	138	29	solutions	solution	NOUN
ajst-24888	138	30	for	for	ADP
ajst-24888	138	31	lithology	lithology	NOUN
ajst-24888	138	32	identification	identification	NOUN
ajst-24888	138	33	.	.	PUNCT
ajst-24888	139	1	machine	machine	NOUN
ajst-24888	139	2	learning	learn	VERB
ajst-24888	139	3	not	not	PART
ajst-24888	139	4	only	only	ADV
ajst-24888	139	5	improves	improve	VERB
ajst-24888	139	6	the	the	DET
ajst-24888	139	7	accuracy	accuracy	NOUN
ajst-24888	139	8	and	and	CCONJ
ajst-24888	139	9	efficiency	efficiency	NOUN
ajst-24888	139	10	of	of	ADP
ajst-24888	139	11	lithology	lithology	NOUN
ajst-24888	139	12	identification	identification	NOUN
ajst-24888	139	13	,	,	PUNCT
ajst-24888	139	14	but	but	CCONJ
ajst-24888	139	15	also	also	ADV
ajst-24888	139	16	reduces	reduce	VERB
ajst-24888	139	17	the	the	DET
ajst-24888	139	18	workload	workload	NOUN
ajst-24888	139	19	of	of	ADP
ajst-24888	139	20	geologists	geologist	NOUN
ajst-24888	139	21	,	,	PUNCT
ajst-24888	139	22	allowing	allow	VERB
ajst-24888	139	23	them	they	PRON
ajst-24888	139	24	to	to	PART
ajst-24888	139	25	focus	focus	VERB
ajst-24888	139	26	on	on	ADP
ajst-24888	139	27	higher	high	ADJ
ajst-24888	139	28	-	-	PUNCT
ajst-24888	139	29	level	level	NOUN
ajst-24888	139	30	analysis	analysis	NOUN
ajst-24888	139	31	and	and	CCONJ
ajst-24888	139	32	decision	decision	NOUN
ajst-24888	139	33	making	making	NOUN
ajst-24888	139	34	.	.	PUNCT
ajst-24888	140	1	(	(	PUNCT
ajst-24888	140	2	2)although	2)although	NUM
ajst-24888	140	3	machine	machine	NOUN
ajst-24888	140	4	learning	learning	NOUN
ajst-24888	140	5	has	have	AUX
ajst-24888	140	6	made	make	VERB
ajst-24888	140	7	significant	significant	ADJ
ajst-24888	140	8	progress	progress	NOUN
ajst-24888	140	9	in	in	ADP
ajst-24888	140	10	lithology	lithology	NOUN
ajst-24888	140	11	identification	identification	NOUN
ajst-24888	140	12	,	,	PUNCT
ajst-24888	140	13	there	there	PRON
ajst-24888	140	14	are	be	VERB
ajst-24888	140	15	still	still	ADV
ajst-24888	140	16	many	many	ADJ
ajst-24888	140	17	challenges	challenge	NOUN
ajst-24888	140	18	,	,	PUNCT
ajst-24888	140	19	such	such	ADJ
ajst-24888	140	20	as	as	ADP
ajst-24888	140	21	limitations	limitation	NOUN
ajst-24888	140	22	in	in	ADP
ajst-24888	140	23	data	datum	NOUN
ajst-24888	140	24	quality	quality	NOUN
ajst-24888	140	25	and	and	CCONJ
ajst-24888	140	26	quantity	quantity	NOUN
ajst-24888	140	27	,	,	PUNCT
ajst-24888	140	28	problems	problem	NOUN
ajst-24888	140	29	with	with	ADP
ajst-24888	140	30	model	model	NOUN
ajst-24888	140	31	complexity	complexity	NOUN
ajst-24888	140	32	and	and	CCONJ
ajst-24888	140	33	interpretability	interpretability	NOUN
ajst-24888	140	34	,	,	PUNCT
ajst-24888	140	35	generalization	generalization	NOUN
ajst-24888	140	36	capabilities	capability	NOUN
ajst-24888	140	37	and	and	CCONJ
ajst-24888	140	38	risks	risk	NOUN
ajst-24888	140	39	of	of	ADP
ajst-24888	140	40	overfitting	overfitte	VERB
ajst-24888	140	41	,	,	PUNCT
ajst-24888	140	42	and	and	CCONJ
ajst-24888	140	43	the	the	DET
ajst-24888	140	44	need	need	NOUN
ajst-24888	140	45	for	for	ADP
ajst-24888	140	46	real	real	ADJ
ajst-24888	140	47	-	-	PUNCT
ajst-24888	140	48	time	time	NOUN
ajst-24888	140	49	processing	processing	NOUN
ajst-24888	140	50	and	and	CCONJ
ajst-24888	140	51	application	application	NOUN
ajst-24888	140	52	.	.	PUNCT
ajst-24888	141	1	addressing	address	VERB
ajst-24888	141	2	these	these	DET
ajst-24888	141	3	challenges	challenge	NOUN
ajst-24888	141	4	requires	require	VERB
ajst-24888	141	5	a	a	DET
ajst-24888	141	6	combination	combination	NOUN
ajst-24888	141	7	of	of	ADP
ajst-24888	141	8	technologies	technology	NOUN
ajst-24888	141	9	such	such	ADJ
ajst-24888	141	10	as	as	ADP
ajst-24888	141	11	data	data	NOUN
ajst-24888	141	12	enhancement	enhancement	NOUN
ajst-24888	141	13	,	,	PUNCT
ajst-24888	141	14	model	model	NOUN
ajst-24888	141	15	interpretability	interpretability	NOUN
ajst-24888	141	16	,	,	PUNCT
ajst-24888	141	17	multi	multi	ADJ
ajst-24888	141	18	-	-	ADJ
ajst-24888	141	19	source	source	NOUN
ajst-24888	141	20	data	datum	NOUN
ajst-24888	141	21	fusion	fusion	NOUN
ajst-24888	141	22	,	,	PUNCT
ajst-24888	141	23	online	online	ADJ
ajst-24888	141	24	learning	learning	NOUN
ajst-24888	141	25	,	,	PUNCT
ajst-24888	141	26	and	and	CCONJ
ajst-24888	141	27	transfer	transfer	VERB
ajst-24888	141	28	learning	learn	VERB
ajst-24888	141	29	to	to	PART
ajst-24888	141	30	develop	develop	VERB
ajst-24888	141	31	more	more	ADV
ajst-24888	141	32	accurate	accurate	ADJ
ajst-24888	141	33	and	and	CCONJ
ajst-24888	141	34	interpretable	interpretable	ADJ
ajst-24888	141	35	models	model	NOUN
ajst-24888	141	36	.	.	PUNCT
ajst-24888	142	1	(	(	PUNCT
ajst-24888	142	2	3	3	X
ajst-24888	142	3	)	)	PUNCT
ajst-24888	142	4	in	in	ADP
ajst-24888	142	5	the	the	DET
ajst-24888	142	6	future	future	NOUN
ajst-24888	142	7	,	,	PUNCT
ajst-24888	142	8	the	the	DET
ajst-24888	142	9	application	application	NOUN
ajst-24888	142	10	of	of	ADP
ajst-24888	142	11	machine	machine	NOUN
ajst-24888	142	12	learning	learning	NOUN
ajst-24888	142	13	in	in	ADP
ajst-24888	142	14	lithology	lithology	NOUN
ajst-24888	142	15	identification	identification	NOUN
ajst-24888	142	16	will	will	AUX
ajst-24888	142	17	continue	continue	VERB
ajst-24888	142	18	to	to	PART
ajst-24888	142	19	expand	expand	VERB
ajst-24888	142	20	and	and	CCONJ
ajst-24888	142	21	deepen	deepen	VERB
ajst-24888	142	22	.	.	PUNCT
ajst-24888	143	1	data	datum	NOUN
ajst-24888	143	2	enhancement	enhancement	NOUN
ajst-24888	143	3	and	and	CCONJ
ajst-24888	143	4	synthesis	synthesis	NOUN
ajst-24888	143	5	technologies	technology	NOUN
ajst-24888	143	6	,	,	PUNCT
ajst-24888	143	7	interpretive	interpretive	ADJ
ajst-24888	143	8	models	model	NOUN
ajst-24888	143	9	and	and	CCONJ
ajst-24888	143	10	visualization	visualization	NOUN
ajst-24888	143	11	tools	tool	NOUN
ajst-24888	143	12	,	,	PUNCT
ajst-24888	143	13	multi	multi	ADJ
ajst-24888	143	14	-	-	ADJ
ajst-24888	143	15	source	source	NOUN
ajst-24888	143	16	data	datum	NOUN
ajst-24888	143	17	fusion	fusion	NOUN
ajst-24888	143	18	,	,	PUNCT
ajst-24888	143	19	online	online	ADJ
ajst-24888	143	20	learning	learning	NOUN
ajst-24888	143	21	and	and	CCONJ
ajst-24888	143	22	transfer	transfer	NOUN
ajst-24888	143	23	learning	learning	NOUN
ajst-24888	143	24	will	will	AUX
ajst-24888	143	25	be	be	AUX
ajst-24888	143	26	the	the	DET
ajst-24888	143	27	main	main	ADJ
ajst-24888	143	28	development	development	NOUN
ajst-24888	143	29	directions	direction	NOUN
ajst-24888	143	30	in	in	ADP
ajst-24888	143	31	the	the	DET
ajst-24888	143	32	future	future	NOUN
ajst-24888	143	33	.	.	PUNCT
ajst-24888	144	1	these	these	DET
ajst-24888	144	2	directions	direction	NOUN
ajst-24888	144	3	will	will	AUX
ajst-24888	144	4	not	not	PART
ajst-24888	144	5	only	only	ADV
ajst-24888	144	6	help	help	AUX
ajst-24888	144	7	overcome	overcome	VERB
ajst-24888	144	8	current	current	ADJ
ajst-24888	144	9	challenges	challenge	NOUN
ajst-24888	144	10	,	,	PUNCT
ajst-24888	144	11	but	but	CCONJ
ajst-24888	144	12	will	will	AUX
ajst-24888	144	13	also	also	ADV
ajst-24888	144	14	drive	drive	VERB
ajst-24888	144	15	innovative	innovative	ADJ
ajst-24888	144	16	applications	application	NOUN
ajst-24888	144	17	of	of	ADP
ajst-24888	144	18	machine	machine	NOUN
ajst-24888	144	19	learning	learn	VERB
ajst-24888	144	20	in	in	ADP
ajst-24888	144	21	lithology	lithology	NOUN
ajst-24888	144	22	identification	identification	NOUN
ajst-24888	144	23	.	.	PUNCT
ajst-24888	145	1	with	with	ADP
ajst-24888	145	2	the	the	DET
ajst-24888	145	3	continuous	continuous	ADJ
ajst-24888	145	4	progress	progress	NOUN
ajst-24888	145	5	of	of	ADP
ajst-24888	145	6	technology	technology	NOUN
ajst-24888	145	7	and	and	CCONJ
ajst-24888	145	8	the	the	DET
ajst-24888	145	9	accumulation	accumulation	NOUN
ajst-24888	145	10	of	of	ADP
ajst-24888	145	11	practical	practical	ADJ
ajst-24888	145	12	experience	experience	NOUN
ajst-24888	145	13	,	,	PUNCT
ajst-24888	145	14	machine	machine	NOUN
ajst-24888	145	15	learning	learning	NOUN
ajst-24888	145	16	will	will	AUX
ajst-24888	145	17	certainly	certainly	ADV
ajst-24888	145	18	play	play	VERB
ajst-24888	145	19	a	a	DET
ajst-24888	145	20	more	more	ADV
ajst-24888	145	21	critical	critical	ADJ
ajst-24888	145	22	role	role	NOUN
ajst-24888	145	23	in	in	ADP
ajst-24888	145	24	lithology	lithology	NOUN
ajst-24888	145	25	identification	identification	NOUN
ajst-24888	145	26	,	,	PUNCT
ajst-24888	145	27	providing	provide	VERB
ajst-24888	145	28	powerful	powerful	ADJ
ajst-24888	145	29	and	and	CCONJ
ajst-24888	145	30	efficient	efficient	ADJ
ajst-24888	145	31	tools	tool	NOUN
ajst-24888	145	32	for	for	ADP
ajst-24888	145	33	geological	geological	ADJ
ajst-24888	145	34	research	research	NOUN
ajst-24888	145	35	and	and	CCONJ
ajst-24888	145	36	petroleum	petroleum	NOUN
ajst-24888	145	37	exploration	exploration	NOUN
ajst-24888	145	38	,	,	PUNCT
ajst-24888	145	39	and	and	CCONJ
ajst-24888	145	40	helping	help	VERB
ajst-24888	145	41	the	the	DET
ajst-24888	145	42	efficient	efficient	ADJ
ajst-24888	145	43	development	development	NOUN
ajst-24888	145	44	and	and	CCONJ
ajst-24888	145	45	utilization	utilization	NOUN
ajst-24888	145	46	of	of	ADP
ajst-24888	145	47	resources	resource	NOUN
ajst-24888	145	48	.	.	PUNCT
ajst-24888	146	1	references	reference	NOUN
ajst-24888	146	2	[	[	X
ajst-24888	146	3	1	1	NUM
ajst-24888	146	4	]	]	X
ajst-24888	146	5	wu	wu	PROPN
ajst-24888	146	6	quande	quande	PROPN
ajst-24888	146	7	,	,	PUNCT
ajst-24888	146	8	ma	ma	PROPN
ajst-24888	146	9	zhizhong	zhizhong	PROPN
ajst-24888	146	10	,	,	PUNCT
ajst-24888	146	11	guo	guo	PROPN
ajst-24888	146	12	keyi	keyi	PROPN
ajst-24888	146	13	,	,	PUNCT
ajst-24888	146	14	et	et	PROPN
ajst-24888	146	15	al	al	PROPN
ajst-24888	146	16	.	.	PUNCT
ajst-24888	147	1	intelligent	intelligent	ADJ
ajst-24888	147	2	lithology	lithology	NOUN
ajst-24888	147	3	identification	identification	NOUN
ajst-24888	147	4	method	method	NOUN
ajst-24888	147	5	of	of	ADP
ajst-24888	147	6	tunnel	tunnel	NOUN
ajst-24888	147	7	surrounding	surround	VERB
ajst-24888	147	8	rock	rock	NOUN
ajst-24888	147	9	based	base	VERB
ajst-24888	147	10	on	on	ADP
ajst-24888	147	11	machine	machine	NOUN
ajst-24888	147	12	learning	learn	VERB
ajst-24888	148	1	[	[	X
ajst-24888	148	2	j	j	X
ajst-24888	148	3	/	/	SYM
ajst-24888	148	4	ol	ol	PROPN
ajst-24888	148	5	]	]	PUNCT
ajst-24888	148	6	.	.	PUNCT
ajst-24888	149	1	roadbed	roadbe	VERB
ajst-24888	149	2	engineering,16[2024	engineering,16[2024	NOUN
ajst-24888	149	3	-	-	PUNCT
ajst-24888	149	4	07	07	NUM
ajst-24888	149	5	-	-	PUNCT
ajst-24888	149	6	22	22	NUM
ajst-24888	149	7	]	]	PUNCT
ajst-24888	149	8	.	.	PUNCT
ajst-24888	150	1	[	[	X
ajst-24888	150	2	2	2	NUM
ajst-24888	150	3	]	]	X
ajst-24888	150	4	cheng	cheng	PROPN
ajst-24888	150	5	guojian	guojian	PROPN
ajst-24888	150	6	,	,	PUNCT
ajst-24888	150	7	guo	guo	PROPN
ajst-24888	150	8	wenhui	wenhui	PROPN
ajst-24888	150	9	,	,	PUNCT
ajst-24888	150	10	fan	fan	NOUN
ajst-24888	150	11	pengzhao	pengzhao	NOUN
ajst-24888	150	12	.	.	PUNCT
ajst-24888	151	1	rock	rock	NOUN
ajst-24888	151	2	image	image	NOUN
ajst-24888	151	3	classification	classification	NOUN
ajst-24888	151	4	based	base	VERB
ajst-24888	151	5	on	on	ADP
ajst-24888	151	6	convolutional	convolutional	ADJ
ajst-24888	151	7	neural	neural	ADJ
ajst-24888	151	8	networks	network	NOUN
ajst-24888	152	1	[	[	X
ajst-24888	152	2	j	j	X
ajst-24888	152	3	]	]	X
ajst-24888	152	4	.	.	PUNCT
ajst-24888	153	1	journal	journal	PROPN
ajst-24888	153	2	of	of	ADP
ajst-24888	153	3	xi	xi	PROPN
ajst-24888	153	4	'	'	PUNCT
ajst-24888	153	5	an	an	DET
ajst-24888	153	6	shiyou	shiyou	PROPN
ajst-24888	153	7	university	university	NOUN
ajst-24888	153	8	(	(	PUNCT
ajst-24888	153	9	natural	natural	ADJ
ajst-24888	153	10	science	science	NOUN
ajst-24888	153	11	edition),2017,32(04):116	edition),2017,32(04):116	PROPN
ajst-24888	153	12	-	-	PUNCT
ajst-24888	153	13	122	122	NUM
ajst-24888	153	14	.	.	PUNCT
ajst-24888	154	1	[	[	X
ajst-24888	154	2	3	3	X
ajst-24888	154	3	]	]	X
ajst-24888	154	4	jiang	jiang	PROPN
ajst-24888	154	5	li	li	PROPN
ajst-24888	154	6	,	,	PUNCT
ajst-24888	154	7	zhang	zhang	PROPN
ajst-24888	154	8	zhimo	zhimo	PROPN
ajst-24888	154	9	,	,	PUNCT
ajst-24888	154	10	wang	wang	PROPN
ajst-24888	154	11	qiwei	qiwei	PROPN
ajst-24888	154	12	,	,	PUNCT
ajst-24888	154	13	et	et	PROPN
ajst-24888	154	14	al	al	PROPN
ajst-24888	154	15	.	.	PROPN
ajst-24888	154	16	comparative	comparative	ADJ
ajst-24888	154	17	study	study	NOUN
ajst-24888	154	18	on	on	ADP
ajst-24888	154	19	lithology	lithology	NOUN
ajst-24888	154	20	classification	classification	NOUN
ajst-24888	154	21	of	of	ADP
ajst-24888	154	22	petroleum	petroleum	NOUN
ajst-24888	154	23	logging	log	VERB
ajst-24888	154	24	data	datum	NOUN
ajst-24888	154	25	based	base	VERB
ajst-24888	154	26	on	on	ADP
ajst-24888	154	27	different	different	ADJ
ajst-24888	154	28	machine	machine	NOUN
ajst-24888	154	29	learning	learning	NOUN
ajst-24888	154	30	models	model	NOUN
ajst-24888	155	1	[	[	X
ajst-24888	155	2	j	j	X
ajst-24888	155	3	]	]	X
ajst-24888	155	4	.	.	PUNCT
ajst-24888	156	1	geophysical	geophysical	ADJ
ajst-24888	156	2	and	and	CCONJ
ajst-24888	156	3	geochemical	geochemical	ADJ
ajst-24888	156	4	exploration	exploration	NOUN
ajst-24888	156	5	,	,	PUNCT
ajst-24888	156	6	2024,48(02):489	2024,48(02):489	NOUN
ajst-24888	156	7	-	-	SYM
ajst-24888	156	8	497	497	NUM
ajst-24888	156	9	.	.	PUNCT
ajst-24888	157	1	[	[	X
ajst-24888	157	2	4	4	X
ajst-24888	157	3	]	]	X
ajst-24888	157	4	wang	wang	PROPN
ajst-24888	157	5	xinling	xinling	PROPN
ajst-24888	157	6	,	,	PUNCT
ajst-24888	157	7	zhu	zhu	PROPN
ajst-24888	157	8	xinyi	xinyi	PROPN
ajst-24888	157	9	,	,	PUNCT
ajst-24888	157	10	zhang	zhang	PROPN
ajst-24888	157	11	hongbing	hongbing	PROPN
ajst-24888	157	12	,	,	PUNCT
ajst-24888	157	13	et	et	PROPN
ajst-24888	158	1	al	al	PROPN
ajst-24888	158	2	.	.	PUNCT
ajst-24888	158	3	lithology	lithology	PROPN
ajst-24888	158	4	identification	identification	NOUN
ajst-24888	158	5	method	method	NOUN
ajst-24888	158	6	of	of	ADP
ajst-24888	158	7	lwd	lwd	NOUN
ajst-24888	158	8	based	base	VERB
ajst-24888	158	9	on	on	ADP
ajst-24888	158	10	random	random	ADJ
ajst-24888	158	11	tree	tree	NOUN
ajst-24888	158	12	embedding	embed	VERB
ajst-24888	158	13	[	[	X
ajst-24888	158	14	j	j	X
ajst-24888	158	15	]	]	X
ajst-24888	158	16	.	.	PUNCT
ajst-24888	159	1	journal	journal	PROPN
ajst-24888	159	2	of	of	ADP
ajst-24888	159	3	jilin	jilin	PROPN
ajst-24888	159	4	university	university	PROPN
ajst-24888	159	5	(	(	PUNCT
ajst-24888	159	6	earth	earth	PROPN
ajst-24888	159	7	science	science	NOUN
ajst-24888	159	8	edition	edition	PROPN
ajst-24888	159	9	)	)	PUNCT
ajst-24888	159	10	,	,	PUNCT
ajst-24888	159	11	2024,54(02):701	2024,54(02):701	NUM
ajst-24888	159	12	-	-	SYM
ajst-24888	159	13	708	708	NUM
ajst-24888	159	14	.	.	PUNCT
ajst-24888	160	1	[	[	X
ajst-24888	160	2	5	5	X
ajst-24888	160	3	]	]	PUNCT
ajst-24888	160	4	wang	wang	PROPN
ajst-24888	160	5	jiao	jiao	PROPN
ajst-24888	160	6	,	,	PUNCT
ajst-24888	160	7	wang	wang	PROPN
ajst-24888	160	8	chenbai	chenbai	PROPN
ajst-24888	160	9	,	,	PUNCT
ajst-24888	160	10	tan	tan	PROPN
ajst-24888	160	11	zhenkun	zhenkun	PROPN
ajst-24888	160	12	,	,	PUNCT
ajst-24888	160	13	et	et	PROPN
ajst-24888	160	14	al	al	PROPN
ajst-24888	160	15	.	.	PROPN
ajst-24888	161	1	high	high	ADJ
ajst-24888	161	2	order	order	NOUN
ajst-24888	161	3	radial	radial	ADJ
ajst-24888	161	4	vortex	vortex	NOUN
ajst-24888	161	5	beam	beam	NOUN
ajst-24888	161	6	superposition	superposition	NOUN
ajst-24888	161	7	oam	oam	PROPN
ajst-24888	161	8	pattern	pattern	NOUN
ajst-24888	161	9	recognition	recognition	NOUN
ajst-24888	161	10	method	method	NOUN
ajst-24888	161	11	based	base	VERB
ajst-24888	161	12	on	on	ADP
ajst-24888	161	13	convolutional	convolutional	ADJ
ajst-24888	161	14	neural	neural	ADJ
ajst-24888	161	15	networks	network	NOUN
ajst-24888	162	1	[	[	X
ajst-24888	162	2	j	j	X
ajst-24888	162	3	/	/	SYM
ajst-24888	162	4	ol	ol	PROPN
ajst-24888	162	5	]	]	PUNCT
ajst-24888	162	6	.	.	PUNCT
ajst-24888	163	1	science	science	NOUN
ajst-24888	163	2	in	in	ADP
ajst-24888	163	3	china	china	PROPN
ajst-24888	163	4	:	:	PUNCT
ajst-24888	163	5	physics	physics	PROPN
ajst-24888	163	6	,	,	PUNCT
ajst-24888	163	7	mechanics	mechanic	NOUN
ajst-24888	163	8	and	and	CCONJ
ajst-24888	163	9	astronomy	astronomy	NOUN
ajst-24888	163	10	,	,	PUNCT
ajst-24888	163	11	1	1	NUM
ajst-24888	163	12	-	-	SYM
ajst-24888	163	13	8	8	NUM
ajst-24888	164	1	[	[	X
ajst-24888	164	2	2024	2024	NUM
ajst-24888	164	3	-	-	SYM
ajst-24888	164	4	07	07	NUM
ajst-24888	164	5	-	-	PUNCT
ajst-24888	164	6	22	22	NUM
ajst-24888	164	7	]	]	PUNCT
ajst-24888	164	8	.	.	PUNCT
ajst-24888	165	1	[	[	X
ajst-24888	165	2	6	6	NUM
ajst-24888	165	3	]	]	X
ajst-24888	165	4	fang	fang	X
ajst-24888	165	5	dazhi	dazhi	PROPN
ajst-24888	165	6	,	,	PUNCT
ajst-24888	165	7	ma	ma	PROPN
ajst-24888	165	8	wejun	wejun	PROPN
ajst-24888	165	9	,	,	PUNCT
ajst-24888	165	10	yan	yan	PROPN
ajst-24888	165	11	xu	xu	PROPN
ajst-24888	165	12	,	,	PUNCT
ajst-24888	165	13	et	et	PROPN
ajst-24888	165	14	al	al	PROPN
ajst-24888	165	15	.	.	PUNCT
ajst-24888	165	16	lithology	lithology	NOUN
ajst-24888	165	17	identification	identification	NOUN
ajst-24888	165	18	based	base	VERB
ajst-24888	165	19	on	on	ADP
ajst-24888	165	20	wavelet	wavelet	NOUN
ajst-24888	165	21	noise	noise	NOUN
ajst-24888	165	22	reduction	reduction	NOUN
ajst-24888	165	23	and	and	CCONJ
ajst-24888	165	24	artificial	artificial	ADJ
ajst-24888	165	25	intelligence	intelligence	NOUN
ajst-24888	165	26	[	[	X
ajst-24888	165	27	j	j	X
ajst-24888	165	28	]	]	X
ajst-24888	165	29	.	.	PUNCT
ajst-24888	166	1	well	well	ADV
ajst-24888	166	2	logging	log	VERB
ajst-24888	166	3	technology,2023,47(04):438	technology,2023,47(04):438	NOUN
ajst-24888	166	4	-	-	PUNCT
ajst-24888	166	5	446	446	NUM
ajst-24888	166	6	.	.	PUNCT
ajst-24888	167	1	(	(	PUNCT
ajst-24888	167	2	in	in	ADP
ajst-24888	167	3	chinese	chinese	PROPN
ajst-24888	167	4	)	)	PUNCT
ajst-24888	168	1	[	[	X
ajst-24888	168	2	7	7	X
ajst-24888	168	3	]	]	X
ajst-24888	168	4	wang	wang	PROPN
ajst-24888	168	5	qi	qi	PROPN
ajst-24888	168	6	,	,	PUNCT
ajst-24888	168	7	yang	yang	PROPN
ajst-24888	168	8	tianwei	tianwei	PROPN
ajst-24888	168	9	,	,	PUNCT
ajst-24888	168	10	liu	liu	PROPN
ajst-24888	168	11	yongzhen	yongzhen	PROPN
ajst-24888	168	12	,	,	PUNCT
ajst-24888	168	13	et	et	PROPN
ajst-24888	168	14	al	al	PROPN
ajst-24888	168	15	.	.	PUNCT
ajst-24888	168	16	lithology	lithology	NOUN
ajst-24888	168	17	identification	identification	NOUN
ajst-24888	168	18	of	of	ADP
ajst-24888	168	19	complex	complex	ADJ
ajst-24888	168	20	carbonate	carbonate	NOUN
ajst-24888	168	21	rocks	rock	NOUN
ajst-24888	168	22	based	base	VERB
ajst-24888	168	23	on	on	ADP
ajst-24888	168	24	random	random	ADJ
ajst-24888	168	25	forest	forest	NOUN
ajst-24888	168	26	algorithm	algorithm	NOUN
ajst-24888	169	1	[	[	X
ajst-24888	169	2	j	j	X
ajst-24888	169	3	]	]	X
ajst-24888	169	4	.	.	PUNCT
ajst-24888	170	1	chinese	chinese	ADJ
ajst-24888	170	2	journal	journal	PROPN
ajst-24888	170	3	of	of	ADP
ajst-24888	170	4	engineering	engineering	NOUN
ajst-24888	170	5	geophysics,2020,17(05):550	geophysics,2020,17(05):550	ADV
ajst-24888	170	6	-	-	SYM
ajst-24888	170	7	558	558	NUM
ajst-24888	170	8	.	.	PUNCT
ajst-24888	171	1	[	[	X
ajst-24888	171	2	8	8	NUM
ajst-24888	171	3	]	]	X
ajst-24888	171	4	chen	chen	PROPN
ajst-24888	171	5	weizheng	weizheng	PROPN
ajst-24888	171	6	.	.	PUNCT
ajst-24888	172	1	application	application	NOUN
ajst-24888	172	2	of	of	ADP
ajst-24888	172	3	neural	neural	ADJ
ajst-24888	172	4	network	network	NOUN
ajst-24888	172	5	to	to	ADP
ajst-24888	172	6	lithology	lithology	NOUN
ajst-24888	172	7	identification	identification	NOUN
ajst-24888	172	8	in	in	ADP
ajst-24888	172	9	sandstone	sandstone	NOUN
ajst-24888	172	10	type	type	NOUN
ajst-24888	172	11	uranium	uranium	NOUN
ajst-24888	172	12	mine	mine	NOUN
ajst-24888	172	13	logging	log	VERB
ajst-24888	172	14	[	[	X
ajst-24888	172	15	j	j	X
ajst-24888	172	16	]	]	X
ajst-24888	172	17	.	.	PUNCT
ajst-24888	173	1	heilongjiang	heilongjiang	PROPN
ajst-24888	173	2	science	science	PROPN
ajst-24888	173	3	,	,	PUNCT
ajst-24888	173	4	2024,15(12):8	2024,15(12):8	PROPN
ajst-24888	173	5	-	-	SYM
ajst-24888	173	6	12	12	NUM
ajst-24888	173	7	.	.	PUNCT
ajst-24888	174	1	[	[	X
ajst-24888	174	2	9	9	NUM
ajst-24888	174	3	]	]	X
ajst-24888	174	4	zhou	zhou	PROPN
ajst-24888	174	5	yuankai	yuankai	PROPN
ajst-24888	174	6	,	,	PUNCT
ajst-24888	174	7	liu	liu	PROPN
ajst-24888	174	8	hu	hu	PROPN
ajst-24888	174	9	.	.	PROPN
ajst-24888	174	10	research	research	NOUN
ajst-24888	174	11	on	on	ADP
ajst-24888	174	12	lithology	lithology	NOUN
ajst-24888	174	13	identification	identification	NOUN
ajst-24888	174	14	of	of	ADP
ajst-24888	174	15	logging	log	VERB
ajst-24888	174	16	based	base	VERB
ajst-24888	174	17	on	on	ADP
ajst-24888	174	18	deep	deep	ADJ
ajst-24888	174	19	learning	learning	NOUN
ajst-24888	174	20	method	method	NOUN
ajst-24888	175	1	[	[	X
ajst-24888	175	2	j	j	X
ajst-24888	175	3	]	]	X
ajst-24888	175	4	.	.	PUNCT
ajst-24888	176	1	uranium	uranium	NOUN
ajst-24888	176	2	geology,2024,40(02):336	geology,2024,40(02):336	NOUN
ajst-24888	176	3	-	-	PUNCT
ajst-24888	176	4	345	345	NUM
ajst-24888	176	5	.	.	PUNCT
ajst-24888	177	1	[	[	X
ajst-24888	177	2	10	10	NUM
ajst-24888	177	3	]	]	X
ajst-24888	177	4	gao	gao	PROPN
ajst-24888	177	5	ya	ya	PROPN
ajst-24888	177	6	tian	tian	PROPN
ajst-24888	177	7	,	,	PUNCT
ajst-24888	177	8	yang	yang	PROPN
ajst-24888	177	9	junguo	junguo	PROPN
ajst-24888	177	10	.	.	PUNCT
ajst-24888	178	1	research	research	NOUN
ajst-24888	178	2	on	on	ADP
ajst-24888	178	3	lithology	lithology	NOUN
ajst-24888	178	4	identification	identification	NOUN
ajst-24888	178	5	method	method	NOUN
ajst-24888	178	6	based	base	VERB
ajst-24888	178	7	on	on	ADP
ajst-24888	178	8	pso	pso	NOUN
ajst-24888	178	9	-	-	PUNCT
ajst-24888	178	10	bp	bp	PROPN
ajst-24888	179	1	[	[	X
ajst-24888	179	2	j	j	X
ajst-24888	179	3	]	]	X
ajst-24888	179	4	.	.	PUNCT
ajst-24888	180	1	computer	computer	NOUN
ajst-24888	180	2	and	and	CCONJ
ajst-24888	180	3	digital	digital	ADJ
ajst-24888	180	4	engineering	engineering	NOUN
ajst-24888	180	5	,	,	PUNCT
ajst-24888	180	6	2024,52(04):1119	2024,52(04):1119	NUM
ajst-24888	180	7	-	-	SYM
ajst-24888	180	8	1124	1124	NUM
ajst-24888	180	9	.	.	PUNCT
ajst-24888	181	1	(	(	PUNCT
ajst-24888	181	2	in	in	ADP
ajst-24888	181	3	chinese	chinese	PROPN
ajst-24888	181	4	)	)	PUNCT
ajst-24888	182	1	[	[	X
ajst-24888	182	2	11	11	NUM
ajst-24888	182	3	]	]	X
ajst-24888	182	4	zhao	zhao	NOUN
ajst-24888	182	5	ranlei	ranlei	NOUN
ajst-24888	182	6	,	,	PUNCT
ajst-24888	182	7	yang	yang	PROPN
ajst-24888	182	8	liushuan	liushuan	PROPN
ajst-24888	182	9	,	,	PUNCT
ajst-24888	182	10	xu	xu	PROPN
ajst-24888	182	11	xiao	xiao	PROPN
ajst-24888	182	12	,	,	PUNCT
ajst-24888	182	13	et	et	PROPN
ajst-24888	183	1	al	al	PROPN
ajst-24888	183	2	.	.	PUNCT
ajst-24888	183	3	lithology	lithology	NOUN
ajst-24888	183	4	identification	identification	NOUN
ajst-24888	183	5	of	of	ADP
ajst-24888	183	6	volcanic	volcanic	ADJ
ajst-24888	183	7	rocks	rock	NOUN
ajst-24888	183	8	based	base	VERB
ajst-24888	183	9	on	on	ADP
ajst-24888	183	10	xgboost	xgboost	X
ajst-24888	183	11	algorithm	algorithm	PROPN
ajst-24888	184	1	[	[	X
ajst-24888	184	2	j	j	X
ajst-24888	184	3	/	/	SYM
ajst-24888	184	4	ol	ol	PROPN
ajst-24888	184	5	]	]	PUNCT
ajst-24888	184	6	.	.	PUNCT
ajst-24888	185	1	progress	progress	NOUN
ajst-24888	185	2	in	in	ADP
ajst-24888	185	3	geophysics,1	geophysics,1	NOUN
ajst-24888	185	4	-	-	PUNCT
ajst-24888	185	5	12[2024	12[2024	NUM
ajst-24888	185	6	-	-	PUNCT
ajst-24888	185	7	07	07	NUM
ajst-24888	185	8	-	-	PUNCT
ajst-24888	185	9	22	22	NUM
ajst-24888	185	10	]	]	PUNCT
ajst-24888	185	11	.	.	PUNCT
ajst-24888	186	1	125	125	NUM
ajst-24888	187	1	[	[	SYM
ajst-24888	187	2	12	12	NUM
ajst-24888	187	3	]	]	X
ajst-24888	187	4	chen	chen	PROPN
ajst-24888	187	5	ganghua	ganghua	PROPN
ajst-24888	187	6	,	,	PUNCT
ajst-24888	187	7	zhang	zhang	PROPN
ajst-24888	187	8	yuxia	yuxia	PROPN
ajst-24888	187	9	,	,	PUNCT
ajst-24888	187	10	wang	wang	PROPN
ajst-24888	187	11	jun	jun	PROPN
ajst-24888	187	12	,	,	PUNCT
ajst-24888	187	13	et	et	PROPN
ajst-24888	187	14	al	al	PROPN
ajst-24888	187	15	.	.	PUNCT
ajst-24888	187	16	application	application	NOUN
ajst-24888	187	17	of	of	ADP
ajst-24888	187	18	bidirectional	bidirectional	ADJ
ajst-24888	187	19	long	long	ADJ
ajst-24888	187	20	and	and	CCONJ
ajst-24888	187	21	short	short	ADJ
ajst-24888	187	22	time	time	NOUN
ajst-24888	187	23	memory	memory	NOUN
ajst-24888	187	24	neural	neural	ADJ
ajst-24888	187	25	network	network	NOUN
ajst-24888	187	26	in	in	ADP
ajst-24888	187	27	reservoir	reservoir	NOUN
ajst-24888	187	28	lithology	lithology	NOUN
ajst-24888	187	29	identification	identification	NOUN
ajst-24888	187	30	of	of	ADP
ajst-24888	187	31	beach	beach	NOUN
ajst-24888	187	32	bar	bar	NOUN
ajst-24888	187	33	sand	sand	NOUN
ajst-24888	188	1	[	[	X
ajst-24888	188	2	j	j	X
ajst-24888	188	3	]	]	X
ajst-24888	188	4	.	.	PUNCT
ajst-24888	189	1	well	well	ADV
ajst-24888	189	2	logging	log	VERB
ajst-24888	189	3	technology,2023,47(03):319	technology,2023,47(03):319	PROPN
ajst-24888	189	4	-	-	PUNCT
ajst-24888	189	5	325	325	NUM
ajst-24888	189	6	.	.	PUNCT
ajst-24888	190	1	[	[	X
ajst-24888	190	2	13	13	NUM
ajst-24888	190	3	]	]	X
ajst-24888	190	4	tong	tong	PROPN
ajst-24888	190	5	rongchao	rongchao	PROPN
ajst-24888	190	6	.	.	PUNCT
ajst-24888	190	7	application	application	NOUN
ajst-24888	190	8	of	of	ADP
ajst-24888	190	9	machine	machine	NOUN
ajst-24888	190	10	learning	learning	NOUN
ajst-24888	190	11	in	in	ADP
ajst-24888	190	12	lithology	lithology	NOUN
ajst-24888	190	13	intelligent	intelligent	ADJ
ajst-24888	190	14	identification	identification	NOUN
ajst-24888	190	15	[	[	X
ajst-24888	190	16	j	j	X
ajst-24888	190	17	]	]	X
ajst-24888	190	18	.	.	PUNCT
ajst-24888	191	1	chemical	chemical	NOUN
ajst-24888	191	2	minerals	mineral	NOUN
ajst-24888	191	3	and	and	CCONJ
ajst-24888	191	4	processing	processing	NOUN
ajst-24888	191	5	,	,	PUNCT
ajst-24888	191	6	2022	2022	NUM
ajst-24888	191	7	,	,	PUNCT
ajst-24888	191	8	51(08):43	51(08):43	NUM
ajst-24888	191	9	-	-	SYM
ajst-24888	191	10	47	47	NUM
ajst-24888	191	11	+	+	NOUN
ajst-24888	191	12	54	54	NUM
ajst-24888	191	13	.	.	PUNCT
ajst-24888	192	1	[	[	X
ajst-24888	192	2	14	14	NUM
ajst-24888	192	3	]	]	X
ajst-24888	192	4	wang	wang	PROPN
ajst-24888	192	5	xinling	xinling	PROPN
ajst-24888	192	6	,	,	PUNCT
ajst-24888	192	7	zhu	zhu	PROPN
ajst-24888	192	8	xinyi	xinyi	PROPN
ajst-24888	192	9	,	,	PUNCT
ajst-24888	192	10	zhang	zhang	PROPN
ajst-24888	192	11	hongbing	hongbing	PROPN
ajst-24888	192	12	,	,	PUNCT
ajst-24888	192	13	et	et	PROPN
ajst-24888	192	14	al	al	PROPN
ajst-24888	192	15	.	.	PROPN
ajst-24888	192	16	based	base	VERB
ajst-24888	192	17	on	on	ADP
ajst-24888	192	18	random	random	ADJ
ajst-24888	192	19	tree	tree	NOUN
ajst-24888	192	20	embedded	embed	VERB
ajst-24888	192	21	while	while	SCONJ
ajst-24888	192	22	drilling	drill	VERB
ajst-24888	192	23	logging	log	VERB
ajst-24888	192	24	lithology	lithology	NOUN
ajst-24888	192	25	recognition	recognition	NOUN
ajst-24888	192	26	method	method	NOUN
ajst-24888	193	1	[	[	X
ajst-24888	193	2	j	j	X
ajst-24888	193	3	]	]	X
ajst-24888	193	4	.	.	PUNCT
ajst-24888	194	1	journal	journal	PROPN
ajst-24888	194	2	of	of	ADP
ajst-24888	194	3	jilin	jilin	PROPN
ajst-24888	194	4	university	university	PROPN
ajst-24888	194	5	(	(	PUNCT
ajst-24888	194	6	earth	earth	NOUN
ajst-24888	194	7	sciences	science	NOUN
ajst-24888	194	8	)	)	PUNCT
ajst-24888	194	9	,	,	PUNCT
ajst-24888	194	10	2024	2024	NUM
ajst-24888	194	11	,	,	PUNCT
ajst-24888	194	12	(	(	PUNCT
ajst-24888	194	13	02	02	NUM
ajst-24888	194	14	):	):	PUNCT
ajst-24888	194	15	701	701	NUM
ajst-24888	194	16	-	-	SYM
ajst-24888	194	17	708	708	NUM
ajst-24888	194	18	.	.	PUNCT
ajst-24888	195	1	[	[	X
ajst-24888	195	2	15	15	NUM
ajst-24888	195	3	]	]	X
ajst-24888	195	4	huang	huang	PROPN
ajst-24888	195	5	an	an	PROPN
ajst-24888	195	6	,	,	PUNCT
ajst-24888	195	7	cai	cai	PROPN
ajst-24888	195	8	wenyuan	wenyuan	PROPN
ajst-24888	195	9	,	,	PUNCT
ajst-24888	195	10	wei	wei	PROPN
ajst-24888	195	11	xinlu	xinlu	PROPN
ajst-24888	195	12	,	,	PUNCT
ajst-24888	195	13	et	et	PROPN
ajst-24888	195	14	al	al	PROPN
ajst-24888	195	15	.	.	PUNCT
ajst-24888	195	16	lithology	lithology	NOUN
ajst-24888	195	17	identification	identification	NOUN
ajst-24888	195	18	of	of	ADP
ajst-24888	195	19	volcanic	volcanic	ADJ
ajst-24888	195	20	logging	logging	NOUN
ajst-24888	195	21	based	base	VERB
ajst-24888	195	22	on	on	ADP
ajst-24888	195	23	improved	improve	VERB
ajst-24888	195	24	random	random	ADJ
ajst-24888	195	25	forest	forest	NOUN
ajst-24888	196	1	[	[	X
ajst-24888	196	2	j	j	X
ajst-24888	196	3	]	]	X
ajst-24888	196	4	.	.	PUNCT
ajst-24888	197	1	science	science	NOUN
ajst-24888	197	2	technology	technology	NOUN
ajst-24888	197	3	and	and	CCONJ
ajst-24888	197	4	engineering	engineering	NOUN
ajst-24888	197	5	,	,	PUNCT
ajst-24888	197	6	2023,23	2023,23	NUM
ajst-24888	197	7	(	(	PUNCT
ajst-24888	197	8	09	09	NUM
ajst-24888	197	9	):	):	PUNCT
ajst-24888	197	10	3696	3696	NUM
ajst-24888	197	11	-	-	SYM
ajst-24888	197	12	3704	3704	NUM
ajst-24888	197	13	.	.	PUNCT
ajst-24888	198	1	[	[	X
ajst-24888	198	2	16	16	NUM
ajst-24888	198	3	]	]	X
ajst-24888	198	4	dong	dong	PROPN
ajst-24888	198	5	wenhao	wenhao	PROPN
ajst-24888	198	6	,	,	PUNCT
ajst-24888	198	7	zhang	zhang	PROPN
ajst-24888	198	8	huai	huai	PROPN
ajst-24888	198	9	.	.	PUNCT
ajst-24888	198	10	lithology	lithology	NOUN
ajst-24888	198	11	identification	identification	NOUN
ajst-24888	198	12	of	of	ADP
ajst-24888	198	13	cuttings	cutting	NOUN
ajst-24888	198	14	based	base	VERB
ajst-24888	198	15	on	on	ADP
ajst-24888	198	16	transfer	transfer	NOUN
ajst-24888	198	17	learning	learning	NOUN
ajst-24888	199	1	[	[	X
ajst-24888	199	2	j	j	X
ajst-24888	199	3	]	]	X
ajst-24888	199	4	.	.	PUNCT
ajst-24888	200	1	journal	journal	PROPN
ajst-24888	200	2	of	of	ADP
ajst-24888	200	3	university	university	PROPN
ajst-24888	200	4	of	of	ADP
ajst-24888	200	5	chinese	chinese	PROPN
ajst-24888	200	6	academy	academy	PROPN
ajst-24888	200	7	of	of	ADP
ajst-24888	200	8	sciences,2023	sciences,2023	NOUN
ajst-24888	200	9	,	,	PUNCT
ajst-24888	200	10	40	40	NUM
ajst-24888	200	11	(	(	PUNCT
ajst-24888	200	12	06	06	NUM
ajst-24888	200	13	):	):	PUNCT
ajst-24888	200	14	743	743	NUM
ajst-24888	200	15	-	-	SYM
ajst-24888	200	16	750	750	NUM
ajst-24888	200	17	.	.	PUNCT
ajst-24888	201	1	[	[	X
ajst-24888	201	2	17	17	NUM
ajst-24888	201	3	]	]	X
ajst-24888	201	4	gao	gao	PROPN
ajst-24888	201	5	chuqiao	chuqiao	PROPN
ajst-24888	201	6	,	,	PUNCT
ajst-24888	201	7	zhan	zhan	PROPN
ajst-24888	201	8	wang	wang	PROPN
ajst-24888	201	9	,	,	PUNCT
ajst-24888	201	10	zhao	zhao	PROPN
ajst-24888	201	11	bin	bin	PROPN
ajst-24888	201	12	,	,	PUNCT
ajst-24888	201	13	et	et	PROPN
ajst-24888	201	14	al	al	PROPN
ajst-24888	201	15	.	.	PUNCT
ajst-24888	201	16	lithology	lithology	NOUN
ajst-24888	201	17	identification	identification	NOUN
ajst-24888	201	18	of	of	ADP
ajst-24888	201	19	igneous	igneous	ADJ
ajst-24888	201	20	rocks	rock	NOUN
ajst-24888	201	21	based	base	VERB
ajst-24888	201	22	on	on	ADP
ajst-24888	201	23	hierarchical	hierarchical	ADJ
ajst-24888	201	24	decomposition	decomposition	NOUN
ajst-24888	201	25	,	,	PUNCT
ajst-24888	201	26	principal	principal	ADJ
ajst-24888	201	27	component	component	NOUN
ajst-24888	201	28	and	and	CCONJ
ajst-24888	201	29	gaussian	gaussian	ADJ
ajst-24888	201	30	mixture	mixture	NOUN
ajst-24888	201	31	clustering	cluster	VERB
ajst-24888	201	32	[	[	X
ajst-24888	201	33	j	j	X
ajst-24888	201	34	/	/	SYM
ajst-24888	201	35	ol	ol	PROPN
ajst-24888	201	36	]	]	PUNCT
ajst-24888	201	37	.	.	PUNCT
ajst-24888	202	1	journal	journal	PROPN
ajst-24888	202	2	of	of	ADP
ajst-24888	202	3	yangtze	yangtze	PROPN
ajst-24888	202	4	university	university	PROPN
ajst-24888	202	5	(	(	PUNCT
ajst-24888	202	6	natural	natural	ADJ
ajst-24888	202	7	science	science	NOUN
ajst-24888	202	8	edition),1	edition),1	PROPN
ajst-24888	202	9	-	-	PUNCT
ajst-24888	202	10	12[2024	12[2024	NUM
ajst-24888	202	11	-	-	PUNCT
ajst-24888	202	12	07	07	NUM
ajst-24888	202	13	-	-	PUNCT
ajst-24888	202	14	22	22	NUM
ajst-24888	202	15	]	]	PUNCT
ajst-24888	202	16	.	.	PUNCT
ajst-24888	203	1	[	[	X
ajst-24888	203	2	18	18	NUM
ajst-24888	203	3	]	]	PUNCT
ajst-24888	203	4	bi	bi	PROPN
ajst-24888	203	5	wenyi	wenyi	PROPN
ajst-24888	203	6	,	,	PUNCT
ajst-24888	203	7	zhang	zhang	PROPN
ajst-24888	203	8	jinyang	jinyang	PROPN
ajst-24888	203	9	.	.	PUNCT
ajst-24888	204	1	dense	dense	ADJ
ajst-24888	204	2	based	base	VERB
ajst-24888	204	3	on	on	ADP
ajst-24888	204	4	principal	principal	ADJ
ajst-24888	204	5	component	component	NOUN
ajst-24888	204	6	analysis	analysis	NOUN
ajst-24888	204	7	of	of	ADP
ajst-24888	204	8	glutenite	glutenite	ADJ
ajst-24888	204	9	reservoir	reservoir	NOUN
ajst-24888	204	10	lithology	lithology	NOUN
ajst-24888	204	11	recognition	recognition	NOUN
ajst-24888	204	12	method	method	NOUN
ajst-24888	205	1	[	[	X
ajst-24888	205	2	j	j	X
ajst-24888	205	3	]	]	X
ajst-24888	205	4	.	.	PUNCT
ajst-24888	206	1	science	science	NOUN
ajst-24888	206	2	and	and	CCONJ
ajst-24888	206	3	technology	technology	NOUN
ajst-24888	206	4	,	,	PUNCT
ajst-24888	206	5	the	the	DET
ajst-24888	206	6	wind	wind	NOUN
ajst-24888	206	7	,	,	PUNCT
ajst-24888	206	8	2021	2021	NUM
ajst-24888	206	9	,	,	PUNCT
ajst-24888	206	10	(	(	PUNCT
ajst-24888	206	11	7	7	NUM
ajst-24888	206	12	):	):	NUM
ajst-24888	206	13	106107	106107	NUM
ajst-24888	206	14	.	.	PUNCT
ajst-24888	207	1	[	[	X
ajst-24888	207	2	19	19	NUM
ajst-24888	207	3	]	]	X
ajst-24888	207	4	sun	sun	PROPN
ajst-24888	207	5	junyang	junyang	PROPN
ajst-24888	207	6	,	,	PUNCT
ajst-24888	207	7	fu	fu	ADJ
ajst-24888	207	8	yunlai	yunlai	PROPN
ajst-24888	207	9	,	,	PUNCT
ajst-24888	207	10	lv	lv	PROPN
ajst-24888	207	11	jing	jing	PROPN
ajst-24888	207	12	,	,	PUNCT
ajst-24888	207	13	et	et	PROPN
ajst-24888	207	14	al	al	PROPN
ajst-24888	207	15	.	.	PROPN
ajst-24888	207	16	research	research	NOUN
ajst-24888	207	17	on	on	ADP
ajst-24888	207	18	counting	count	VERB
ajst-24888	207	19	method	method	NOUN
ajst-24888	207	20	of	of	ADP
ajst-24888	207	21	sea	sea	NOUN
ajst-24888	207	22	cucumber	cucumber	NOUN
ajst-24888	207	23	seedlings	seedling	NOUN
ajst-24888	207	24	based	base	VERB
ajst-24888	207	25	on	on	ADP
ajst-24888	207	26	improved	improved	ADJ
ajst-24888	207	27	yolov7	yolov7	PROPN
ajst-24888	207	28	model	model	NOUN
ajst-24888	208	1	[	[	X
ajst-24888	208	2	j	j	X
ajst-24888	208	3	/	/	SYM
ajst-24888	208	4	ol	ol	PROPN
ajst-24888	208	5	]	]	PUNCT
ajst-24888	208	6	.	.	PUNCT
ajst-24888	209	1	computer	computer	NOUN
ajst-24888	209	2	technology	technology	NOUN
ajst-24888	209	3	and	and	CCONJ
ajst-24888	209	4	development	development	NOUN
ajst-24888	209	5	,	,	PUNCT
ajst-24888	209	6	1	1	NUM
ajst-24888	209	7	-	-	SYM
ajst-24888	209	8	7	7	NUM
ajst-24888	210	1	[	[	X
ajst-24888	210	2	2024	2024	NUM
ajst-24888	210	3	-	-	SYM
ajst-24888	210	4	07	07	NUM
ajst-24888	210	5	-	-	PUNCT
ajst-24888	210	6	22	22	NUM
ajst-24888	210	7	]	]	PUNCT
ajst-24888	210	8	.	.	PUNCT
ajst-24888	211	1	[	[	X
ajst-24888	211	2	20	20	NUM
ajst-24888	211	3	]	]	X
ajst-24888	211	4	guo	guo	PROPN
ajst-24888	211	5	bin	bin	PROPN
ajst-24888	211	6	,	,	PUNCT
ajst-24888	211	7	liu	liu	PROPN
ajst-24888	211	8	zhao	zhao	PROPN
ajst-24888	211	9	,	,	PUNCT
ajst-24888	211	10	zhu	zhu	PROPN
ajst-24888	211	11	mingang	mingang	PROPN
ajst-24888	211	12	.	.	PUNCT
ajst-24888	211	13	research	research	PROPN
ajst-24888	211	14	on	on	ADP
ajst-24888	211	15	embankment	embankment	ADJ
ajst-24888	211	16	settlement	settlement	NOUN
ajst-24888	211	17	prediction	prediction	NOUN
ajst-24888	211	18	method	method	NOUN
ajst-24888	211	19	based	base	VERB
ajst-24888	211	20	on	on	ADP
ajst-24888	211	21	emd	emd	PROPN
ajst-24888	211	22	-	-	PUNCT
ajst-24888	211	23	rnn	rnn	PROPN
ajst-24888	211	24	[	[	X
ajst-24888	211	25	j	j	X
ajst-24888	211	26	/	/	SYM
ajst-24888	211	27	ol	ol	PROPN
ajst-24888	211	28	]	]	PUNCT
ajst-24888	211	29	.	.	PUNCT
ajst-24888	212	1	water	water	NOUN
ajst-24888	212	2	resources	resource	NOUN
ajst-24888	212	3	and	and	CCONJ
ajst-24888	212	4	hydropower	hydropower	NOUN
ajst-24888	212	5	letters,1	letters,1	ADJ
ajst-24888	212	6	-	-	PUNCT
ajst-24888	212	7	9[2024	9[2024	NUM
ajst-24888	212	8	-	-	PUNCT
ajst-24888	212	9	07	07	NUM
ajst-24888	212	10	-	-	PUNCT
ajst-24888	212	11	22	22	NUM
ajst-24888	212	12	]	]	PUNCT
ajst-24888	212	13	.	.	PUNCT
ajst-24888	213	1	[	[	X
ajst-24888	213	2	21	21	NUM
ajst-24888	213	3	]	]	X
ajst-24888	213	4	liu	liu	PROPN
ajst-24888	213	5	y	y	PROPN
ajst-24888	213	6	,	,	PUNCT
ajst-24888	213	7	dan	dan	PROPN
ajst-24888	213	8	b	b	PROPN
ajst-24888	213	9	,	,	PUNCT
ajst-24888	213	10	yi	yi	PROPN
ajst-24888	213	11	c	c	PROPN
ajst-24888	213	12	c	c	X
ajst-24888	213	13	,	,	PUNCT
ajst-24888	213	14	et	et	PROPN
ajst-24888	213	15	al	al	PROPN
ajst-24888	213	16	.	.	PROPN
ajst-24888	213	17	research	research	NOUN
ajst-24888	213	18	on	on	ADP
ajst-24888	213	19	gear	gear	NOUN
ajst-24888	213	20	fault	fault	NOUN
ajst-24888	213	21	classification	classification	NOUN
ajst-24888	213	22	method	method	NOUN
ajst-24888	213	23	based	base	VERB
ajst-24888	213	24	on	on	ADP
ajst-24888	213	25	improved	improved	ADJ
ajst-24888	213	26	saggan	saggan	NOUN
ajst-24888	213	27	model	model	NOUN
ajst-24888	214	1	[	[	X
ajst-24888	214	2	j	j	X
ajst-24888	214	3	/	/	SYM
ajst-24888	214	4	ol	ol	PROPN
ajst-24888	214	5	]	]	PUNCT
ajst-24888	214	6	.	.	PUNCT
ajst-24888	215	1	mechanical	mechanical	ADJ
ajst-24888	215	2	and	and	CCONJ
ajst-24888	215	3	electrical	electrical	ADJ
ajst-24888	215	4	engineering,1	engineering,1	NOUN
ajst-24888	215	5	-	-	PUNCT
ajst-24888	215	6	11[2024	11[2024	NUM
ajst-24888	215	7	-	-	PUNCT
ajst-24888	215	8	0722	0722	NUM
ajst-24888	215	9	]	]	PUNCT
ajst-24888	215	10	.	.	PUNCT
ajst-24888	216	1	[	[	X
ajst-24888	216	2	22	22	NUM
ajst-24888	216	3	]	]	X
ajst-24888	216	4	tian	tian	PROPN
ajst-24888	216	5	tian	tian	PROPN
ajst-24888	216	6	,	,	PUNCT
ajst-24888	216	7	cheng	cheng	PROPN
ajst-24888	216	8	zhiyou	zhiyou	PROPN
ajst-24888	216	9	,	,	PUNCT
ajst-24888	216	10	ju	ju	PROPN
ajst-24888	216	11	wei	wei	PROPN
ajst-24888	216	12	,	,	PUNCT
ajst-24888	216	13	et	et	PROPN
ajst-24888	216	14	al	al	PROPN
ajst-24888	216	15	.	.	PROPN
ajst-24888	216	16	study	study	NOUN
ajst-24888	216	17	on	on	ADP
ajst-24888	216	18	small	small	ADJ
ajst-24888	216	19	sample	sample	NOUN
ajst-24888	216	20	classification	classification	NOUN
ajst-24888	216	21	of	of	ADP
ajst-24888	216	22	tea	tea	NOUN
ajst-24888	216	23	diseases	disease	NOUN
ajst-24888	216	24	based	base	VERB
ajst-24888	216	25	on	on	ADP
ajst-24888	216	26	simam	simam	ADJ
ajst-24888	216	27	-	-	PUNCT
ajst-24888	216	28	convnext	convnext	NOUN
ajst-24888	216	29	-	-	PUNCT
ajst-24888	216	30	fl	fl	NOUN
ajst-24888	217	1	[	[	X
ajst-24888	217	2	j	j	X
ajst-24888	217	3	]	]	X
ajst-24888	217	4	.	.	PUNCT
ajst-24888	218	1	transactions	transaction	NOUN
ajst-24888	218	2	of	of	ADP
ajst-24888	218	3	the	the	DET
ajst-24888	218	4	chinese	chinese	ADJ
ajst-24888	218	5	society	society	NOUN
ajst-24888	218	6	for	for	ADP
ajst-24888	218	7	agricultural	agricultural	ADJ
ajst-24888	218	8	machinery	machinery	NOUN
ajst-24888	218	9	,	,	PUNCT
ajst-24888	218	10	2024,55(03):275	2024,55(03):275	NUM
ajst-24888	218	11	-	-	SYM
ajst-24888	218	12	281	281	NUM
ajst-24888	218	13	.	.	PUNCT