Iraqi Journal of Chemical and Petroleum Engineering Vol.16 No.2 (June 2015) 53- 56 ISSN: 1997-4884 Single Well Coning Problem and Applicable Solutions Raad Mohammed Jawad. Alkhalissi Department of Petroleum Technology/University of Technology Baghdad-Iraq Abstract One of the most important and common problems in petroleum engineering; reservoir, and production engineering is coning; either water or gas coning. Almost 75% of the drilled wells worldwide contains this problem, and in Iraq water coning problem is much wider than the gas coning problem thus in this paper we try to clarify most of the reasons causing water coning and some of applicable solutions to avoid it using the simulation program (CMG Builder) to build a single well model considering an Iraqi well in north of Iraq black oil field with a bottom water drive, Coning was decreased by 57% by dividing into sub-layers (8) layers rather than (4) layers, also it was decreased (Coning) by 45% when perforation numbers and positions was changed. Key Word: Well coning, Iraqi well Introduction In simulation many problems can occur according to data and information user apply and water coning is the most common after a period of production. It is usually noted by the water oil ratio, respectively the gas coning is noted by the gas oil ratio in certain wells. Usually to avoid this problem in the oil fields or areas which are predicted to be a coning areas is to use directional drilling in the area or by valve controlling on the well-head, but sometimes it is impossible to predict that or there are some reasons like well depletion which happens after many years of production; in these cases other techniques should be used. Water coning usually happens in oil fields with bottom water drive and it may affects the oil production economics due to water treatment and disposal issues [1] Builder of CMG software is one of the most useful programs in analyzing this problem by simulation and it is used widely to predict and solve many reservoir and production problems like the problem we about to discuss. Theoretical Background (Effect of simple coning) Remember that all the formulas of the critical rate represent, as close experimental coefficient, the equilibrium between viscosity forces and gravity forces which characterize a cone. [2] In the mobile face, ∆p between exterior limit and the well, in radial circular flow [2] ∆p= B.Q.μ Ln (R/r) … (1) Iraqi Journal of Chemical and Petroleum Engineering University of Baghdad College of Engineering Single Well Coning Problem and Applicable Solutions 54 IJCPE Vol.16 No.2 (June 2015) -Available online at: www.iasj.net In the immobile phase ∆p between the two limits ∆p= ∆ρ.g.Hc … (2) The pressure is the same for the two phases along the interface, and combining eqts.(1) and (2) we obtain: … (3) Certain authors like Meyer and Shulga [3] have deliberately ignored real causes of instability of cone near the well. They supposed that the critical height is equal to the free height below perforations: With: Hc= Ht-Hp … (4) Equation (3), become: … (5) Using above formula gives results 2 to 3 times below the reality. Other authors like Sobocinsky and Bournazzel [3] used above formula and added a numerical coefficient deduced from experience done in laboratory: With: = 1.52*10⁻ᶾ (Sobocinsky) = 1.42*10⁻ᶾ (Bournazel) Some Useful Data The following data were used as an input data to the simulator [4] 1- PV T Data Pressure Volume Temperature Data (PV T) are presented in english units in table (1) Table (1), PVT Data Pressure psi Rs liberated scf/bbl Rs insolution cf/bbl B vol/vol Shrinkage factor vol/vol 3450 0 1249.6 1.619 1 3000 193 1056 1.536 0.949 2500 381.4 868.2 1.454 0.898 2000 540 709.6 1.388 0.857 1500 694.1 555.5 1.324 0.818 1000 838.8 410.8 1.266 0.782 650 942.7 306.9 1.233 0.755 200 1096 153.6 1.153 0.712 0.698 60 11662 83.4 1.13 1.049 0.648 0 at 60◦F 1249.6 0 1 0.618 Raad Mohammed Jawad. Alkhalissi -Available online at: www.iasj.net IJCPE Vol.16 No.2 (June 2015) 55 2- Following Table (2) shows the chemical composition of Oil vs. Weight percent Table (2), Composition and weight% Composition Weight% C1 0.3 C2 0.32 C3 0.51 iC4 0.97 nC4 4.86 iC5 7.75 nC5 9.4 C6ɟ 75.89 3- Formations depths (tops and bottom) from RTKB (m) and reservoir formations top as shown in table no.3 below [6] Table (3), Tops and bottoms of different layers Layer Top from RTKB/ m Bottom from RTKB/ m RTKB m Top m Jeribe 2804 1868.5 284.05 1804 Dhiban 18868.5 1913.8 1868.5 Euphrates 1913 1926 1913.8 Serikagni 1926 1955 1926 Basal Anhydrite _____ _____ ____ Jaddala ------- -------- ------- 4- As shown in table number 4 the oil density versus reservoir pressure Table (4) Oil density vs. Pressure Pressure psi Oil density lb/ftᶾ 500 0.6783 4500 0.6751 4000 0.6719 5- Water saturation and porosity versus different reservoir layers, thickness are presented in table (5) below [6] Table (5), Thickness, Water Saturation and Porosity versus Reservoir Layers Building the Model and Finding a Solution In order to build the model a suitable simulator must be used depending on the types of fluids in the field by determining to use a black oil field then Builder of CMG simulator should be used. Using PVT[4] information related to the X-well for our study to build the model using 4 layers totally of 400 meter and 100 meter of radius [6] perforated in the production zone (layer 3) given in the final well report[6] of the well chosen. The water coning problem appeared after running the simulator for 35 years and many steps were taken to avoid this problem. Then next step were taken to avoid the water coning, and these steps are related to each other and were done consequently, Layer Thickness m Water Saturation fraction Porosity fraction Jeribe 18 0.4 0.19 Dhiban 25 1 0.07 Euphrates 18 0.3 0.2 Serikagni 10.5 0.2 0.1 Basal Anhydrite 9.5 0.2 0.2 Oligocene 25 0.8 0.1 Jaddala 20 1 0.05 Single Well Coning Problem and Applicable Solutions 56 IJCPE Vol.16 No.2 (June 2015) -Available online at: www.iasj.net 1- Divide the 4 main layers to sub layers, totally 8 layers it help in minimizing the water coning. It was 13.24 mstb with layer 4 layered model and become 5.87 mstb, so it was minimized by 57% approximately ant this result is due to the decrease in water encroachment from limited aquifer size in one coning well model 2- Change the perforation interval number instead of one layer perforation. 2 layers (the 4 th and 6 th ) were chosen to be perforated (in the 4 layers model, layer 3 was perforated) . This step made the perforation interval much less and on a higher level/ the water production was 5.87 mstb before this step and after it became 4.1 mstb, approximately it was minimized by 31% It is not effective as the previous one as a second step, but if this step were taken to be the first step the result will be minimizing the 13.24 mstb to 6.98 mstb, about 45% 3- This step must be done within limit, not to exceed the original perforation depth. 4- Using one perforation area instead of two, but in this case the oil percentage will be minimized as well, so it is not a preferable step. 5- Trying to minimize the production period for the well, not to exceed 25 years in simulator, predicting for more than 25 years can cause many problems to occur while it might be unrealistic due to limited aquifer size in our one well model. Conclusions 1- Dividing the model to sub layers 8 layers instead of 4 layers result In decreasing water coning by 57% can avoid and minimize the water coning 2- Changing perforations place and number (within limit) led to decrease coning by 45%. 3- Minimizing the production time in the simulator and increasing production period beyond 25 years resulted in many problems which is unrealistic. Nomenclatures mstb: million standard barrel, PVT: pressure, volume and temperature, ∆P: Pressure difference ( ), B: formation volume factor (vol/vol), Q: Flow rate ( ), µ: viscosity (cp), Ln: natural logarithm, R: outer radius (m), r: well radius (m), g: acceleration= 9.81 (m/ ), Qo: oil rate ( /day), ∆ρ in gm/ , K: permeability (md), µo: oil viscosity (cp), Ht: total bed thickness (m), Hp: perforated height (m) and Ht: immobile phase height (m). References 1- Ali Ghalambor (2007), petroleum production engineering a computer assisted approach. 2- R.H. Cotin (1979), Elaboration of Reservoir Exploitation Project. 3- Hussein Rabia (2009), well Engineering and Construction. 4- PVT Report for X-Well (2009). 5- Map for the northern Iraq Field with X-well coordination (2007). 6- Final Well Report for X-well. 7- Leonard F Koederitz (2004), Lecture notes on applied reservoir simulation. 8- Donald W. Peaceman (1977), Fundamentals of numerical reservoir simulation.