OPTIMIZATION OF OIL OBTAINED IN B FIELD M LAYER X BLOCK WITH RESERVOIR SIMULATION

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1 OPTIMIZATION OF OIL OBTAINED IN B FIELD M LAYER X BLOCK WITH RESERVOIR SIMULATION Bianca Marella Putri Salusu 1), Sugiatmo Kasmungin 2), Andry Prima 3) 1) Mahasiswa Jurusan Teknik Perminyakan Universitas Trisakti 2,3) Pembimbing Skripsi Teknik Perminyakan Universitas Trisakti bianca.salusu@gmail.com Abstract There are a lot of mature fields in Indonesia that have been produced since a long time ago. B Field is one of the mature fields in Indonesia that is still producing until today. Up till now, in B field has been drilled 570 wells with 55 prospects layers. The production of B Field that has been done since 1931 affects the pressure drop in this field. This drop in pressure also led to a decrease in production in the field. To increase the recovery factor in the field, production forecast is done by using reservoir simulation method. In the reservoir simulation process, some injection scenarios planning are done as alternatives to know which scenario gives the most optimum oil production. The reservoir simulation process includes the data preparation, reservoir modeling, initialization, history matching, field development simulation scenarios, and injection rate sensitivity. There are three scenarios applied to find the most optimum recovery method in M Layer through reservoir simulation. Out of the three scenarios that have been done, the Author proposes scenario III as the best scenario because it gives the highest cumulative value of oil production. Keywords: waterflooding, reservoir simulation, recovery factor, production scenario and injection rate sensitivity. Preface B Field is one of the fields in Indonesia with many blocks that have been produced since For this study, author limits the research on X block which is separated by a sealing fault into X1 and X2. The production of B Field which has been done since a long time ago affects the decrease in pressure that led to decrease in production in that field. Initial pressure of this reservoir was 568 psi and the current pressure is 530 psi. Besides, the original oil in place in B Field M Layer X Block is MBBL and until now it has been produced around MBBL. As a result, the recovery factor is 31.2%. In order to increase the recovery factor in B Field, workover, drilling infill well and injection well is planned with 3 different scenarios. Waterflooding is one way to increase oil production after the oil rate is decreased in primary recovery phase. After the primary recovery phase is done, the reservoir pressure will decrease so that the reservoir pressure is needed to be added through secondary recovery phase. Waterflooding (secondary recovery) is a way of increasing production by using water as an injection material. The purpose of injecting water to the reservoir is to make the water column fill the reservoir rock pores and boost the oil in the reservoir pores so that the reservoir pressure can be maintained and the production can be improved. One of the way to improve oil recovery is by making injection pattern, to get as maximum swept pattern as possible. The use of injection pattern should pass through several stages which are the use of existing wells, then if the pattern is not maximum, it is necessary to add new wells. The considerations in choosing production injection well pattern depend on structure map, water saturation map, and LKO. In this case, peripheral pattern is done in B Field X Block through reservoir simulation method. This study was also limited by not taking gas production and economic limit into account. In order to look for the most optimum recovery enhancement, a few scenarios are done in this field. One of the methods to know the best scenario to be applied is by using reservoir simulation method. The principal of reservoir simulation is using numerical calculations. The study conducted on this reservoir simulation gives 147

2 detailed results because the simulated reservoir is divided into grids that have their respective values and calculations performed. Waterflooding Waterflooding is a method to increase the amount of oil obtained which is categorized as immiscible flooding. Injection water injected with a certain flow rate will provide displacement and swept efficiency in the reservoir. The water is expected to move behind and oil moves in front. As the injection water arrives, the water production will increase rapidly. This condition is called breakthrough. After breakthrough, water saturation in the reservoir will become very high that at the end of the process the fluid produced will be dominated by water, which is signed by the increase of water cut. The process of oil sweeping by water affects the amount of oil that can be obtained. The higher the swept efficiency, the greater the amount of oil will be produced. In waterflooding, sweeping will be more dominant in the bottom of the reservoir as it has adequate gravity. This is different from gas injection that sweeps in the upper layer more because gas is lighter than oil gravity. Reservoir Simulation The reservoir simulation is a mathematical process used to predict reservoir behavior by using a model. In this case the model is assumed to have properties similar to the actual reservoir state. The purpose of the reservoir simulation is to estimate the reservoir behavior of a field under various conditions of production plan. The stages in performing the reservoir simulation are as follows: data preparation, reservoir modeling, initialization, history matching, and production scenario application. Procedures Processing and analyzing production data well will determine the completion time in the simulation process. The results of production data analysis can be used to validate the reservoir geological model, as a simulation input and assist in accelerating the history matching process. Data on the initial condition of the reservoir were obtained after core analysis of the reservoir rock to determine its physical properties. Table 1 Initial Reservoir Conditions Parameter M Layer X Block Pi, psi 568 T, o F Rsi, scf/stb 56 Boi, bbl/stb 1.26 Pb. psi OOIP, MSTB OWC, ft API 48 Then, reservoir modeling is done based on the result of geological modeling (static) combined with reservoir data (dynamic). The reservoir modeling characteristics built with the CMG (Computer Modeling Group) software are shown in the table

3 Table 2 B Field M Layer X Block Modeling Characteristics M Layer X Block Total Blocks Grid Type 107 x 75 x 8 Active Grid Simulator IMEX Constraint Liquid Rate After reservoir modeling and grid top and other maps are obtained, initialization should be performed. This step aims to equalize the initial condition of the reservoir (in place and pressure) with the model. In this process, the value of Original Oil In Place (OOIP) from simulation results with OOIP of volumetric calculations will be synchronized. After the initialization process is completed, the wells & recurrent should be inputted where the data inputted is well trajectory and well production data. The data is entered into the simulator to know the production of the field and this production data are used as field production history data created by simulator. Then, history matching process is done. History matching is the process of modifying the parameters used in modeling, in order to create alignment between models with real conditions, based on measured parameter data over a given time period. This stage is crucial in performing reservoir simulation. The purpose of the alignment process is to validate the reservoir simulation model with the actual reservoir condition. This alignment is performed by determining the total liquid as a reference alignment, then the alignment begins by changing the relative permeability value that exists until the simulation model and the actual model are matching. The relative permeability changes made will not change what has been done in the initialization process. Parameters that are altered to obtain expected alignment results are aquifer, permeability, transmissibility, and relative permeability curves. The alignment is made to the production rate of each key well and to the cumulative production of each block and field. The selection of key well is done by looking at wells contributing 70% of the total field production. In this research, there are 4 key wells from 15 wells. Below is the result of history matching for cumulative Field B production. Figure 1 History Matching of B Field X Block Cumulative Production The difference between history matching results between the real condition and the simulation result should be less than 5%. In this process, the cumulative difference of history matching result for liquid and oil are 3.32% and 2.4%, respectively. Then scenarios development plan for field B in order to improve oil acquisition are carried out by implementing the drilling and workover for production and injection wells. The structure development scenario is prepared with technical, operational and economic 149

4 considerations, including geological and reservoir conditions, dispersion of reservoir rock and fluid properties, remaining reserve, and injection rate (sensitivity rate) in M Zone to see the technical feasibility condition of implementation in Structure B. There are 3 scenarios done in order to develop this field. Scenario I In this scenario, production is done by doing workover to 11 production wells on both blocks, 7 wells on X1 and 4 wells on X2. The production rate at these wells are 300 bbl / day in accordance with the average production rate previously. Oil acquisition in the first scenario obtained a recovery factor of 44.63% with incremental recovery factor of 13.34%. The cumulative amount of oil production is MBBL. X2 X1 Figure 2 Scenario I Scenario II The second scenario is a continuation of scenario I with the addition of 3 production wells in total on X2. The analysis of the addition of 1, 2, and 3 wells showed that the addition of 1 well (B001) gives the biggest recovery factor which is 45.09%. The cumulative oil production obtained from this scenario is MBBL. X2 X1 B001 B002 B003 Figure 3 Scenario II 150

5 Scenario III The third scenario is a continuation of scenario II with the addition of 6 injection wells, 3 wells on X1 and 3 wells on X2. Besides, workover is done to 2 production wells which are converted to injection wells. As a result, there are 8 injection wells in total. The injection rate for these wells are 300 BBL/day and these wells are made with peripheral pattern. The cumulative oil production obtained from this scenario is MBBL with the recovery factor of 49.82%. X2 X1 Figure 4 Scenario III From the three scenarios, the biggest recovery was obtained in scenario 3 with recovery factor of 49.82% and incremental recovery factor of 18.53%. The cumulative production obtained in this scenario is MBBL. From this scenario, injection rate sensitivity is done from 150 to 900 BPD. Figure 5 Injection Rate VS Cumulative Oil Production The result of the injection rate sensitivity shows that the optimal rate to be applied in B Field M Layer X Block is 500 BPD with the recovery factor 50.74%. It is because the injection water from these wells help the reservoir to maintain its pressure by replacing the pore volume left by reservoir fluids. As a result, the pressure will be more stable and the production will increase. 151

6 Conclusions a) The value of Original Oil In Place (OOIP) based on simulation is MSTB while the value of OOIP based on the calculation of volumetric is MSTB. The difference of initial oil in place of both methods is 0.4%. b) Scenario I (workover for 11 production wells) resulted in a cumulative oil production of MBBL with a recovery factor of 44.63%. c) Scenario II (Scenario I + 1 production well) obtained a cumulative oil production of MBBL with a recovery factor of 45.09%. d) Scenario III (Scenario II + 6 injection wells + 2 workover injection wells) resulted a cumulative oil production of MBBL with a recovery factor of 49.82%. e) The best scenario to be performed in this research is Scenario III (12 production wells and 8 injection wells with peripheral patterns) with injection rate of 500 BPD that gives a recovery factor of 50.74%. References Al-Adasani, A., & Bai, B., 2010, Recent Developments and Updated Screening Criteria of Enhanced Oil Recovery Techniques, International Oil and Gas Conference and Exhibition in China, 1 24, China. Al-Harbi, B., 2013, Advanced Vizualisation for Reservoir Simulation, Annual Technical Symposium and Exhibition, SPE , Khobar, Saudi Arabia. Balqis, A., 2017, Optimasi Skenario Pengembangan Lapangan ABFN Menggunakan Simulasi Reservoir, Skripsi Program Sarjana, Teknik Perminyakan, Universitas Trisakti. Beckner, B.L., 2015, General Parallel Reservoir Simulation, International Petroleum Technology Conference, IPTC MS, Doha, Qatar. Gencer, S.C., 2007, Data Management in Reservoir Simulation, SPE Reservoir Simulation Symposium, Houston, Texas. Kamelia, M., 2016, Perencanaan dan Optimasi Sumur Waterflooding Pada Lapangan MKS Menggunakan Simulasi Reservoir, Skripsi Program Sarjana, Teknik Perminyakan, Universitas Trisakti. Lee, W.J., 2011, Reservoir Simulation: A Reliable Technology? SPE Annual Technical Conference and Exhibition, SPE , Colorado, USA. Lumina, A., 2016, Alternatif Injeksi Air Dalam Usaha Peningkatan Produksi Pada Lapangan R Dengan Menggunakan Simulasi Reservoir, Skripsi Program Sarjana, Teknik Perminyakan, Universitas Trisakti. Matthai, S. K., 2008, Reservoir Simulation: Mathematical Techniques in Oil Recovery, Geofluids (Vol. 8). Pamungkas, J., 2011, Pemodelan dan Aplikasi Simulasi Reservoir Edisi - I, Teknik Perminyakan UPN Veteran Yogyakarta, Yogyakarta. Rukmana, D., 2011, Teknik Reservoir Teori dan Aplikasi, Teknik Perminyakan Universitas Pembangunan Nasional UPN Yogyakarta. Tarek, A., 2006, Reservoir Engineering Handbook Third Edition, Gulf Publishing Company, Houston, Texas. Willhite, G. P.,1986, Waterflooding, Dallas: Society of Petroleum Engineers. 152