Gas and Downhole Water Sink-Assisted Gravity Drainage GDWS-AGD EOR Process: Field-Scale Evaluation and Recovery Optimization
- Authors
- Watheq J. Al-Mudhafar (Louisiana State University) | Andrew K. Wojtanowicz (Louisiana State University) | Dandina N. Rao (Louisiana State University)
- DOI
- https://doi.org/10.2118/190163-MS
- Document ID
- SPE-190163-MS
- Publisher
- Society of Petroleum Engineers
- Source
- SPE Improved Oil Recovery Conference, 14-18 April, Tulsa, Oklahoma, USA
- Publication Date
- 2018
- Document Type
- Conference Paper
- Language
- English
- ISBN
- 978-1-61399-570-9
- Copyright
- 2018. Society of Petroleum Engineers
- Disciplines
- 5.5 Reservoir Simulation, 2.1.3 Completion Equipment, 5.7.2 Recovery Factors, 2 Well completion, 5.4.2 Gas Injection Methods, 5.4 Improved and Enhanced Recovery, 5.4 Improved and Enhanced Recovery, 5 Reservoir Desciption & Dynamics, 5.7 Reserves Evaluation, 2.2 Installation and Completion Operations
- Keywords
- Downhole Water Sink, Assisted Gravity Drainage, Infinite Edge and/or Bottom Water Drive, Immiscible CO2 Flooding, Enhance Oil Recovery
- Downloads
- 2 in the last 30 days
- 141 since 2007
- Show more detail
- View rights & permissions
SPE Member Price: | USD 8.50 |
SPE Non-Member Price: | USD 25.00 |
The Gas and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been developed to overcome of the limitations of Gas flooding processes in reservoir with strong aquifers. These limitations include high levels of water cut and high tendency of water coning. The GDWS-AGD process minimizes the water cut in oil production wells, improve gas injectivity, and further enhance the recovery of bypassed oil, especially in reservoirs with strong water coning tendencies.
The GDWS-AGD process conceptually states installing two 7 inch production casings bi-laterally and completing by two 2-3/8 inch horizontal tubings: oil producer above the oil-water contact (OWC) and one underneath OWC for water sink drainage. The two completions are hydraulically isolated by a packer inside the casing. The water sink completion is produced with a submersible pump that prevents the water from breaking through the oil column and getting into the horizontal oil-producing perforations.
The GDWS-AGD process was evaluated to enhance oil recovery in the heterogeneous upper sandstone pay in South Rumaila Oil field, which has an infinite active aquifer with a huge edge water drive. A compositional reservoir flow model was adopted for the CO2 flooding simulation and optimization of the GDWS-AGD process. Design of Experiments (DoE) and proxy metamodeling were integrated to determine the optimal operational decision parameters that affect the GDWS-AGD process performance: maximum injection rate and pressure in injection wells, maximum oil rate and minimum bottom hole pressure in production wells, and maximum water rates and minimum bottom hole pressure in the water sink wells. More specifically, Latin hypercube sampling and radial basis neural networks were used for the optimization of the GDWS-AGD process performance and to build the proxy model, respectively.
In the GDWS-AGD process results, the water cut and coning tendency were significantly reduced along with the reservoir pressure. That resulted to improve gas injectivity and increase oil recovery. Further improvement in oil recovery was achieved by the DoE optimization after determining the optimal set of operational decision factors that constrains the oil and water production with gas injection. The advantage of GDWS-AGD process comes from its potential feasibility to enhance oil recovery while reducing water coning, water cut, and improving gas injectivity. That gives another privilege for the GDWSAGD process to reach significant improvement in oil recovery in comparison to other gas injection processes, such as the Gas-Assisted Gravity Drainage (GAGD) process, particularly in reservoirs with strong water aquifers.
File Size | 2 MB | Number of Pages | 20 |
Amudo, C., T. Graf, R. R. Dandekar, and J. M. Randle. The Pains and Gains of Experimental Design and Response Surface Applications in Reservoir Simulation Studies. SPE Reservoir Simulation Symposium, (2-4 February), Houston, Texas (2009). http://dx.doi.org/10.2118/118709-MS.
Ansari, E., Hughes, R. (2016). Response surface method for assessing energy production from geopressured geothermal reservoirs. Geotherm Energy, 4:15. https://doi.org/10.1186/s40517-016-0057-5
Al-Mudhafar, W. J. Statistical Reservoir Characterization, Simulation, and Optimization Of Field Scale-Gas Assisted Gravity Drainage (GAGD) Process with Uncertainty Assessments. PhD Dissertation. Louisiana State University (2016). http://etd.lsu.edu/docs/available/etd-04072016-165145/.
Al-Mudhafar, W. Multiple-Point Geostatistical Lithofacies Simulation of Fluvial Sand-Rich Depositional Environment: A Case Study from Zubair Formation/South Rumaila Oil Field. Offshore Technology Conference, (2–5 May), Houston, TX, USA (2016). http://dx.doi.org/10.4043/27273-MS.
Al-Mudhafar, W. J., Dalton, C. A., Al Musabeh, M. I. Metamodeling via Hybridized Particle Swarm with Polynomial and Splines Regression for Optimization of CO2-EOR in Unconventional Oil Reservoirs. SPE Reservoir Characterization and Simulation Conference and Exhibition, (8-10 May), Abu Dhabi, UAE (2017). https://doi.org/10.2118/186045-MS
Al-Mudhafar, W. J., Rao, D. N. Proxy-Based Metamodeling Optimization of the Gas-Assisted Gravity Drainage GAGD Process in Heterogeneous Sandstone Reservoirs. SPE Western Regional Meeting, (23-27 April), Bakersfield, California, USA (2017). https://doi.org/10.2118/185701-MS
Al-Mudhafar, W. J., Rao, D. N., McCreery, E. B. Evaluation of Immiscible CO2 Enhance Oil Recovery through the CGI, WAG, and GAGD Processes in South Rumaila Oil Field. The 79th EAGE Conference and Exhibition, Paris, France (2017). http://dx.doi.org/10.3997/2214-4609.201701349.
Al-Mudhafar, W. J., Wojtanowicz, A. K., Rao, D. N. Hybrid Process of Gas and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) to Enhance Oil Recovery in Reservoirs with Water Coning. The Carbon Management Technology Conference, (17-20 July), Houston, Texas, USA (2017). https://doi.org/10.7122/502487-MS
Avansi, G. D. Use of Proxy Models in the Selection of Production Strategy and Economic Evaluation of Petroleum Fields. SPE Annual Technical Conference and Exhibition, (4-7 October), New Orleans, Louisiana (2009). http://dx.doi.org/10.2118/129512-STU.
Bhat, C. R. Quasi-Random Maximum Simulated Likelihood Estimation of the Mixed Multinomial Logit Model. Transportation Research Part B: Methodological, (35)7, 677-693 (2001). http://dx.doi.org/10.1016/S0191-2615(00)00014-X.
Dalton, C. A., Broussard, M. B., Al-Mudhafar, W. J. Proxy-Based Optimization of Hydraulic Fracturing Design in Horizontal Wells Through CO2 Flooding in Shale Oil Reservoirs. The 51st U.S. Rock Mechanics/Geomechanics Symposium, (25-28 June), San Francisco, California, USA (2017). https://www.onepetro.org/conference-paper/ARMA-2017-0737
Fedutenko, EYang, C., Card, C., and L. X. Nghiem. Time-Dependent Proxy Modeling of SAGD Process. SPE Heavy Oil Conference-Canada, Calgary, AB, Canada (2013). http://dx.doi.org/10.2118/165395-MS.
Hamdi, H., Hajizadeh, Y. and M. Costa Sousa. Population-based sampling methods for geological well testing. Computational Geoscience, 19:1089 (2015). https://doi.org/10.1007/s10596-015-9522-7
Kabir, C. S., Mohammed, N. I., Choudhary, M. K. Lessons Learned From Energy Models: Iraqs South Rumaila Case Study. SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain (2007). http://dx.doi.org/10.2118/105131-MS.
Kitching, D., Farmer, R., Abuzaid, M. In Search of the Remaining Oil in the "Main Pay" Member of the Zubair Formation through Surveillance Oil Mapping, Rumaila Field, Southern Iraq. Second EAGE Workshop on Iraq (2013). http://dx.doi.org/10.3997/2214-4609.20131456.
Kulkarni, M. M., Rao, D. N. Experimental Investigation of Miscible and Immiscible Water-Alternating-Gas (WAG) Process Performance. Journal of Petroleum Science and Engineering, 48: 1-20 (2005). http://dx.doi.org/10.1016/j.petrol.2005.05.001.
Mahmoud, T., Rao, D. N. Range of Operability of Gas-Assisted Gravity Drainage Process. Society of Petroleum Engineers. SPE Symposium on Improved Oil Recovery, (20-23 April), Tulsa, Oklahoma, USA (2008). https://doi.org/10.2118/113474-MS
McKay, M. D., Beckman, R. J., Conover, W. J. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics (JSTOR Abstract) (American Statistical Association) 21 (2): 239-245 (1979). http://dx.doi.org/10.2307/1268522.
Mohammed, W. J., Al Jawad, M. S., Al-Shamaa, D. A. Reservoir Flow Simulation study for a Sector in Main Pay-South Rumaila Oil Field. SPE Oil and Gas India Conference and Exhibition, Mumbai, India (2010). http://dx.doi.org/10.2118/126427-MS.
Orr, M. J. L. 1996. Introduction to Radial Basis Function Networks. http://www.anc.ed.ac.uk/~mjo/papers/intro.ps
Osterloh, W. T. Use of Multiple-Response Optimization To Assist Reservoir Simulation Probabilistic Forecasting and History Matching. SPE Annual Technical Conference and Exhibition, (21-24 September), Denver, Colorado (2008). http://dx.doi.org/10.2118/116196-MS.
Qin, W., Luo, P., Meng, J., Li, H., Mao, T., Wojtanowicz, A. K., Feng, M. Successful Field Trials for Water Control in High Water Cut Wells Using an Improved Downhole Water Sink/Drainage System. Abu Dhabi International Petroleum Exhibition and Conference, (13-16 November), Abu Dhabi, UAE (2017). https://doi.org/10.2118/188958-MS.
Rao, D. N., Ayirala, S. C., Kulkarni, M. M., Sharma, A. P. Development of Gas Assisted Gravity Drainage (GAGD) Process for Improved Light Oil Recovery. SPE/DOE Symposium on Improved Oil Recovery, Tulsa, Oklahoma, USA (2004). http://dx.doi.org/10.2118/89357-MS.
Stein, M. Large Sample Properties of Simulations Using Latin Hypercube Sampling. Technometrics. 29, 143-151 (1987). http://www.jstor.org/stable/1269769.
White, C. D., and S. A. Royer. Experimental Design as a Framework for Reservoir Studies. SPE Reservoir Simulation Symposium, Houston, Texas (2003). http://dx.doi.org/10.2118/79676-MS.
Wojtanowicz, A. K. Down-Hole Water Sink Technology for Water Coning Control in Wells. Louisiana State University, WIERTNICTWO NAFTA GAZ, T O M 23/1, Pp 575-586 (2006). http://journals.bg.agh.edu.pl/WIERTNICTWO/2006-01/W_2006_1_63.pdf.
Wojtanowicz, A. K., Xu, H., and Bassiouni, Z. A. Oilwell Coning Control using Dual Completion with Tailpipe Water Sink. SPE production operation symposium, (7-9 April), Oklahoma (1991). https://doi.org/10.2118/21654-MS.
Wells, M., Kitching, D., Finucane, D., Kostic, B. an Integrated Description of the Stratigraphy and Depositional Environment of the Main Pay Member of the Zubair Formation, Rumaila, Iraq. Second EAGE Workshop on Iraq, Dead Sea, Jordan (2013). http://dx.doi.org/10.3997/2214-4609.20131455.
Vanegas Prada, J. W., Cunha, L. B. Prediction of SAGD Performance Using Response Surface Correlations Developed by Experimental Design Techniques. Petroleum Society of Canada (2008). http://dx.doi.org/10.2118/08-09-58.
Whabi, A. M. Zubair Reservoir (Cretaceous) in Zuluf Field, Saudi Arabia: Depositional Facies and Facies Distribution. AAPG Search and Discovery Article No. 90188 (2014). http://www.searchanddiscovery.com/abstracts/html/2014/90188geo/abstracts/wahbi.htm.
White, C. D., Willis, B. J., Narayanan, K., Dutton, S. P. Identifying and Estimating Significant Geologic Parameters with Experimental Design. SPEJ, 6(03), 311-324 (2001). http://dx.doi.org/10.2118/74140-PA.
Yeten, B., Castellini, A., Guyaguler, B., Chen, W. H. A Comparison Study on Experimental Design and Response Surface Methodologies. SPE Reservoir Simulation Symposium, (31 January-2 February), The Woodlands, Texas (2005). http://dx.doi.org/10.2118/93347-MS.
Zangl, G., Graf, T., Al-Kinani, A. Proxy Modeling in Production Optimization. SPE Europec/EAGE Annual Conference and Exhibition, (12-15 June), Vienna, Austria (2006). http://dx.doi.org/10.2118/100131-MS.
Zhang, X. Y., M. N. Trame, L. J. Lesko and S. Schmidt. 2015. Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models. CPT: Pharmacometrics & Systems Pharmacology. 4(2):69-79. http://dx.doi.org/10.1002/psp4.6
Zerpa, L. E., Queipo, N. V., Pintos, S., Tillero, E., Alter, D. An Efficient Response Surface Approach for the Optimization of ASP Flooding Processes: ASP Pilot Project LL-03 Reservoir. SPE Latin American & Caribbean Petroleum Engineering Conference, (15-18 April), Buenos Aires, Argentina (2007). http://dx.doi.org/10.2118/107847-MS.
Zubarev, D. I. Pros and Cons of Applying a Proxy Model as a Substitute for Full Reservoir Simulations. SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana (2009). http://dx.doi.org/10.2118/124815-MS.