Evaluation of Gas and Downhole Water Sink-Assisted Gravity Drainage GDWS-AGD Process in Saturated Oil Reservoirs with Infinite-Acting Aquifer
- Dahlia A Al-Obaidi (The University of Baghdad) | Watheq J Al-Mudhafar (Basrah Oil Company & The University of Texas at Austin) | Andrew K Wojtanowicz (Louisiana State University) | Mohammed S Al-Jawad (The University of Baghdad) | Dayanand Saini (California State University)
- Document ID
- Society of Petroleum Engineers
- SPE Western Regional Meeting, 23-26 April, San Jose, California, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Gas Injection, Strong Water Aquifers, Downhole Water Sink, Gravity Drainage, Enhanced Oil Recovery
- 2 in the last 30 days
- 54 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
A hybrid Gas-Enhanced and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been suggested to enhance oil recovery by placing vertical injectors for CO2 at the top of the reservoir with a series of horizontal oil-producing and water-drainage wells located above and below the oil-water contact, respectively. The injected gas builds a gas cap that drives the oil to the (upper) oil-producing wells while the bottom water-drainage wells control water cresting. The hybrid process of GDWS-AGD process has been first developed and tested in vertical wells to minimize water cut in reservoirs with bottom water drive and strong water coning tendencies. The wells were dual-completed with 7-inch production casing and 2-3/8 inch tubings and perforated above the oil-water contact (OWC) for oil production and below OWC for water drainage. The two completions were hydraulically isolated inside the well by a packer. The bottom (water sink) completion drained water with a submersible pump.
The GDWS-AGD was efficiently adopted to improve oil recovery at the PUNQ saturated oil field. The PUNQ Field has an infinite active aquifer with very strong edge and bottom water drives. A black oil reservoir flow model was implemented for CO2 flooding simulation of the GDWS-AGD process in comparison with the Gas-Assisted Gravity Drainage (GAGD) process. The comparison was performed to obtain the clearest image about the performance of the combined GDWS-AGD process. Next, Design of Experiments (DoE) and proxy modeling were incorporated to find the most sensitive parameters that affect the GDWS-AGD process performance. The candidate parameters are porosity, horizontal and vertical permeability for each layer, radius of aquifer and rock compressibility.
In the GDWS-AGD, the produced water not only reduced water cut and coning, but also significantly reduced the reservoir pressure, resulting in improving gas injectivity. In addition, the GDWS-AGD process improved cumulative oil production. More specifically, the results showed that cumulative oil production increased from 3.8*105m3 to 4.7*105m3 and water cut decreased from 97% to 92% in all the horizontal oil producers. For the proxy model, it was cleared from Sobol analysis that the porosity for layer 5 was more influential parameter than others on cumulative oil through GDWS-AGD process with 31% main effects and 0.025% interaction effects, while the horizontal permeability for layer 4 was the most influential parameter with 24% main effects and 1.5% interaction effects. The novelty of GDWS-AGD process comes from its effectiveness to improve oil recovery with reducing the water coning, water cut, and improving gas injectivity. This leads to more economic implementation, especially with respect to the operational surface facilities.
|File Size||2 MB||Number of Pages||15|
Al-Mudhafar,Watheq J.,Wojtanowicz, A. K. and Rao, D. N. 2017. "Hybrid Process of Gas and Downhole Water Sink-Assisted Gravity Drainage (G&DWS-AGD) to Enhance Oil Recovery in Reservoirs with Water Coning." Carbon Management Technology Conference. https://doi.org/10.7122/502487-MS.
Al-Mudhafar,Watheq J.,Dandina N. Rao, and Sanjay Srinivasan. 2018. "Reservoir Sensitivity Analysis for Heterogeneity and Anisotropy Effects Quantification through the Cyclic CO2-Assisted Gravity Drainage EOR Process – A Case Study from South Rumaila Oil Field." Fuel 221 (October 2017). Elsevier: 455–68. https://doi.org/10.1016/j.fuel.2018.02.121.
Barker, John,Maarten Cuypers, and Lars Holden. 2001. "Quantifying Uncertainty in Production Forecasts: Another Look at the PUNQ-S3 Problem." SPE Journal 6 (1): 1–11. https://doi.org/10.2118/74707-PA.
Box, George,J Stuart Hunter, and William G Hunter. 2009. "Statistics Experimenters: Desing, Innovation, and Discovery." https://doi.org/10.1080/00401706.1979.10489788.
Floris, F. J. T.,M. D. Bush,M. Cuypers,F. Roggero, and A.-R. Syversveen. 2001. "Methods for Quantifying the Uncertainty of Production Forecasts: A Comparative Study." Petroleum Geoscience 7 (S): S87–96. https://doi.org/10.1144/petgeo.7.S.S87.
Gao, Guohua, and Mohammad Zafari. 2005. "Quantifying Uncertainty for the PUNQ-S3 Problem in a Bayesian Setting with RML and EnKF." SPE Reservoir Simulation Symposium, no. December: 506–15. http://www.onepetro.org/mslib/servlet/onepetropreview?id=00093324.
Gao, Guohua,Mohammad Zafari, and Albert C. Reynolds. 2006. "Quantifying Uncertainty for the PUNQ-S3 Problem in a Bayesian Setting With RML and EnKF." SPE Journal 11 (4): 506–15. https://doi.org/10.2118/93324-PA.
Li, Dachang, and L.W. Lake. 2013. "Scaling Fluid Flow Through Heterogeneous Permeable Media." SPE Advanced Technology Series 3 (1): 188–97. https://doi.org/10.2118/26648-PA.
Rao, D N,S C Ayirala,M M Kulkarni, and A P Sharma. 2004. "Development of Gas Assisted Gravity Drainage (GAGD) Process for Improved Light Oil Recovery." Spe. https://doi.org/10.2523/89357-MS.
Silva, R. R. C., and B. Maini. 2016. Evaluation of Gas Assisted Gravity Drainage GAGD in Naturally Fractured Reservoirs NFR. SPE Improved Oil Recovery Conference. https://doi.org/10.2118/179585-MS.
White, Christopher, and Steve Royer. 2003. "Experimental Design as a Framework for Reservoir Studies." SPE Reservoir Simulation Symposium, 1–14. https://doi.org/10.2118/79676-MS.