Material Balance Applied to Dynamic Reservoir-Surveillance Patterns
- Rod P. Batycky (StreamSim Technologies) | Marco R. Thiele (Streamsim Technologies)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- August 2018
- Document Type
- Journal Paper
- 566 - 575
- 2018.Society of Petroleum Engineers
- reservoir pattern surveillance, reservoir streamline patterns, pattern material balance
- 5 in the last 30 days
- 289 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Determining the remaining spatial oil-saturation distribution or current reservoir-pressure distribution for a mature (water, solvent, CO2) flood is a cornerstone of reservoir management for improving sweep and selecting infill-well locations. Decisions of these types are typically supported by reservoir flow simulation models that have been calibrated to historical injection/production data.
In this paper, we present a novel-pattern material-balance (PatMB) approach to estimating remaining fluids in place as an alternative to flow simulation. First, we use the historical injection/production volumes to solve for streamlines and streamline-derived pattern metrics such as well-allocation factors and injector/producer-pair reservoir pore volumes (PVs). Then, we apply material balance on these volumes over time to estimate the remaining oil in place (ROIP) and pressures at the end of history. Resembling reservoir simulation, the method considers changing well patterns through time, requires a 3D static geological model, and yields 3D saturation distributions of oil, water, and gas. However, unlike reservoir simulation, because historical injected and produced voidage terms are honored, calibration is only possible through the 3D distribution of PV and fluids initially in place.
We present results for the Berrymoor-pattern waterflood and show that the ROIP distribution is a strong function of the original-oil-in-place (OOIP) distribution, well locations, and historical oil, gas, and water production/injection volumes. For this case, the ROIP distribution is almost insensitive to interwell permeability distributions, suggesting that the primary focus when estimating ROIP with the PatMB approach is to ensure a good estimate of OOIP, major flow units, and the correct injection/production data. We also compare our method to reservoir flow simulation for a large water/hydrocarbon miscible flood (HCMF), and we observed that the ROIP maps compare well, with both methods highlighting similar areas for potential infill locations. However, the remaining-gas-in-place maps differed with PatMB, showing a more diffused distribution than flow simulation of the gas. We attribute the difference to the fact that PatMB does not account for transport effects such as separation of the phases caused by density differences.
|File Size||1 MB||Number of Pages||10|
Batycky, R. P. and Thiele, M. R. 2000. System and Methods for the Visual Interpretation of Well Rate Allocation Factors. US Patent No. 6519531.
Batycky, R. P., Seto, A. C., and Fenwick, D. H. 2007. Assisted History Matching of a 1.4-Million-Cell Simulation Model for Judy Creek—A Pool Waterflood/HCMF Using a Streamline-Based Workflow. Presented at the SPE Annual Technical Conference and Exhibition, Anaheim, California, 11–14 November. SPE-108701-MS. https://doi.org/10.2118/108701-MS.
Batycky, R. P., Thiele, M. R., Baker, R. O. et al. 2008. Revisiting Reservoir Flood-Surveillance Methods Using Streamlines. SPE Res Eval & Eng 11 (2): 387–394. SPE-95402-PA. https://doi.org/10.2118/95402-MS.
Chapman, L. R. and Thompson, R. R. 1989. Waterflood Surveillance in the Kuparuk River Unit With Computerized Pattern Analysis. J Pet Technol 41 (3): 277–282. SPE-17429-PA. https://doi.org/10.2118/17429-PA.
Cobb, W. M. and Marek, F. J. 1997. Determination of Volumetric Sweep Efficiency in Mature Waterfloods Using Production Data. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 5–8 October. SPE-38902-MS. https://doi.org/10.2118/38902-MS.
3DSL. 2017. 0531 Reference Manual.
Dake, L.P. 1978. Fundamentals of Reservoir Engineering. Amsterdam: Elsevier Science B.V. p. 86.
Hedges, P. L. and Scherer, P. W. 1996. Group-Oriented Software Solution for Pattern Material Balance of an Areally Extensive Field, Kuparuk River Field, Alaska. Presented at the Petroleum Computer Conference, Dallas, 2–5 June. SPE-35987-MS. https://doi.org/10.2118/35987-MS.
Mijnarends, R., Frolov, A., Grishko, F. et al. 2015. Advanced Data-Driven Performance Analysis for Mature Waterfloods (Russian). Presented at the SPE Russian Petroleum Technology Conference, Moscow, 26–28 October. SPE-174872-MS. https://doi.org/10.2118/174872-MS.
Samier, P., Quettier, L., and Thiele, M. 2001. Applications of Streamline Simulations to Reservoir Studies. Presented at the SPE Reservoir Simulation Symposium, Houston, 11–14 February. SPE-66362-MS. https://doi.org/10.2118/66362-MS.
Sharma, A. K. and Anil, K. 1996. Areal Pattern Distribution of Remaining Oil Saturation in a Mature West Texas Waterflood—A Case History. Presented at the Permian Basin Oil and Gas Recovery Conference, Midland, Texas, 27–29 March. SPE-35202-MS. https://doi.org/10.2118/35202-MS.