Improving Chemical-Enhanced-Oil-Recovery Simulations and Reducing Subsurface Uncertainty Using Downscaling Conditioned to Tracer Data
- Victor A. Torrealba (King Abdullah University of Science and Technology) | Hussein Hoteit (King Abdullah University of Science and Technology) | Adwait Chawathe (Chevron Corporation)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- November 2019
- Document Type
- Journal Paper
- 1,426 - 1,435
- 2019.Society of Petroleum Engineers
- uncertainty analysis, enhanced oil recovery, downscaling, tracers, simulation
- 11 in the last 30 days
- 122 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Chemical-enhanced oil-recovery (CEOR) mechanisms are strongly influenced by gridblock size and reservoir heterogeneity compared with conventional waterflooding (WF) simulations. In WF-simulation models, simulation grids are commonly upscaled (coarsened) on the basis of a single-phase flow to perform history matching and sensitivity analyses within affordable computational times. However, this coarse-grid resolution (typically, approximately 100 ft) is insufficient for CEOR, and hence usually fails to capture key physical mechanisms. These coarse models also tend to increase numerical dispersion, artificially increase the level of mixing, and have inadequate resolution to capture certain geological features to which EOR processes can be highly sensitive. Thus, coarse models often overestimate the sweep efficiency as a result of numerical dispersion, and underestimate the displacement efficiency as a result of the artificial dilution of chemicals.
Therefore, grid refinement is necessary for CEOR simulations when the original (fine) Earth model is not available or when major disconnects occur between the original Earth model and the history-matched coarse WF model. However, recreating the fine-scale heterogeneity without degrading the history match from the coarse grid remains a challenge. Because of the different recovery mechanisms involved in CEOR, such as miscibility and thermodynamic phase behavior, the impact of grid downscaling on CEOR simulations is not well-understood.
In this work, we introduce a geostatistical downscaling method that can be conditioned to tracer data, for refining coarse history-matched WF models. The proposed downscaling method refines the coarse grid and populates the relevant properties in the newly created, finer gridblocks, reproducing the fine-scale heterogeneity while retaining the fluid material balance. The method treats the values of rock properties in the coarse grid as hard data, and the corresponding variograms and property distributions as soft data. We outline a work flow that reduces uncertainties in the geological properties by integrating dynamic data such as sweep efficiency from the interwell tracers. We provide several test cases, and demonstrate the applicability of the proposed method to improving the history match of a CEOR pilot.
|File Size||1 MB||Number of Pages||10|
Arya, A., Hewett, T. A., Larson, R. G. et al. 1988. Dispersion and Reservoir Heterogeneity. SPE Res Eval & Eng 3 (1): 139–148. SPE-14364-PA. https://doi.org/10.2118/14364-PA.
Aziz, K. and Settari, A. 1979. Petroleum Reservoir Simulation. London: Science Publishers.
Brouwer, G. K. and Fokker, P. A. 2013. Upscaling and Downscaling With an Effective Medium Theory, Applied to Heterogeneous Reservoir. Presented at the 75th EAGE Conference and Exhibition incorporating SPE Europec, London, 10–13 June. SPE-164803-MS. https://doi.org/10.2118/164803-MS.
Chawathe, A. and Taggart, I. 2004. Insights Into Upscaling Using 3D Streamlines. SPE Res Eval & Eng 7 (4): 285–296. SPE-88846-PA. https://doi.org/10.2118/88846-PA.
Cheng, H., Shook, G. M., Malik, T. et al. 2012. Interwell Tracer Tests To Optimize Operating Conditions for a Surfactant Field Trial: Design, Evaluation, and Implications. SPE Res Eval & Eng 15 (2): 229–242. SPE-144899-PA. https://doi.org/10.2118/144899-PA.
Christie, M. A. 1996. Upscaling for Reservoir Simulation. J Pet Technol 48 (11): 1004–1010. SPE-37324-JPT. https://doi.org/10.2118/37324-JPT.
Christie, M. A. and Blunt, M. J. 2001. Tenth SPE Comparative Solution Project: A Comparison of Upscaling Techniques. SPE Res Eval & Eng 4 (4): 308–317. SPE-72469-PA. https://doi.org/10.2118/72469-PA.
Goudarzi, A., Delshad, M., Mohanty, K. K. et al. 2012. Impact of Matrix Block Size on Oil Recovery Response Using Surfactants in Fractured Carbonates. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 8–10 October. SPE-160219-MS. https://doi.org/10.2118/160219-MS.
Green, D. W. and Willhite, G. P. 1998. Enhanced Oil Recovery. Henry L. Doherty Memorial Fund of AIME. Richardson, Texas: Society of Petroleum Engineers.
Haajizadeh, M., Fayers, F. J., and Cockin, A. P. 2000. Effects of Phase Behavior, Dispersion, and Gridding on Sweep Patterns for Nearly Miscible Gas Displacement. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 1–4 October. SPE-62995-MS. https://doi.org/10.2118/62995-MS.
Helmig, R. 1997. Multiphase Flow and Transport Processes in the Subsurface: A Contribution to the Modeling of Hydrosystems. Springer.
Hoteit, H. and Chawathe, A. 2016. Making Field-Scale Chemical Enhanced-Oil-Recovery Simulations a Practical Reality With Dynamic Gridding. SPE J. 21 (6): 2220–2237. SPE-169688-PA. https://doi.org/10.2118/169688-PA.
Kalla, S., White, C. D., Gunning, J. et al. 2009. Downscaling Multiple Seismic Inversion Constraints to Fine-Scale Flow Models. SPE J. 14 (4): 746–758. SPE-110771-PA. https://doi.org/10.2118/110771-PA.
Koval, E. J. 1963. A Method for Predicting the Performance of Unstable Miscible Displacement in Heterogeneous Media. SPE J. 3 (2): 145–154. SPE-450-PA. https://doi.org/10.2118/450-PA.
Koyassan Veedu, F., Delshad, M., and Pope, G. A. 2010. Scaleup Methodology for Chemical Flooding. Presented at the SPE Annual Technical Conference and Exhibition, Florence, Italy, 19–22 September. SPE-135543-MS. https://doi.org/10.2118/135543-MS.
Lake, L. W. and Jensen, J. L. 1989. A Review of Heterogeneity Measures Used in Reservoir Characterization. SPE-20156-MS, eLibrary.
Lake, L. W., Johns, R., Rossen, B. et al. 2014. Fundamentals of Enhanced Oil Recovery. Richardson, Texas: Society of Petroleum Engineers.
Møyner, O., Krogstad, S., and Lie, K.-A. 2015. The Application of Flow Diagnostics for Reservoir Management. SPE J. 20 (2): 306–323. SPE-171557-PA. https://doi.org/10.2118/171557-PA.
Najafabadi, N. F. and Chawathe, A. 2016. Proper Simulation of Chemical EOR (CEOR) Pilots—A Real Case Study. Presented at the SPE Improved Oil Recovery Conference, Tulsa, 11–13 April. SPE-179659-MS. https://doi.org/10.2118/179659-MS.
Rashid, B., Muggeridge, A., Bal, A.-L. et al. 2012. Quantifying the Impact of Permeability Heterogeneity on Secondary-Recovery Performance. SPE J. 17 (2): 455–468. SPE-135125-PA. https://doi.org/10.2118/135125-PA.
Ren, W., McLennan, J., Cunha, L. B. et al. 2005. An Exact Downscaling Methodology in the Presence of Heterogeneity: Application to the Athabasca Oilsands. Presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, 1–3 November. SPE-97874-MS. https://doi.org/10.2118/97874-MS.
Shahvali, M., Mallison, B., Wei, K. et al. 2012. An Alternative to Streamlines for Flow Diagnostics on Structured and Unstructured Grids. SPE J. 17 (3): 768–778. SPE-146446-PA. https://doi.org/10.2118/146446-PA.
Sheng, J. J., Leonhardt, B., and Azri, N. 2015. Status of Polymer-Flooding Technology. J Can Pet Technol 54 (2): 116–126. SPE-174541-PA. https://doi.org/10.2118/174541-PA.
Shook, G. M and Mitchell, K. M. 2009. A Robust Measure of Heterogeneity for Ranking Earth Models: The F PHI Curve and Dynamic Lorenz Coefficient. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 4–7 October. SPE-124625-MS. https://doi.org/10.2118/124625-MS.
Sorbie, K. S. 1991. Polymer-Improved Oil Recovery. Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-011-3044-8.
Stalkup, F. I., Lo, L. L., and Dean, R. H. 1990. Sensitivity to Gridding of Miscible Flood Predictions Made With Upstream Differenced Simulators. Presented at the SPE/DOE Enhanced Oil Recovery Symposium, Tulsa, 22–25 April. SPE-20178-MS. https://doi.org/10.2118/20178-MS.
Tran, T. T., Wen, X.-H., and Behrens, R. A. 2001. Efficient Conditioning of 3D Fine-Scale Reservoir Model to Multiphase Production Data Using Streamline-Based Coarse-Scale Inversion and Geostatistical Downscaling. SPE J. 6 (4): 364–374. SPE-74708-PA. https://doi.org/10.2118/74708-PA.
Trykozko, A., Brouwer, G., and Zijl, W. 2008. Downscaling: A Complement to Homogenization. International Journal of Numerical Analysis and Modeling. SUPPL. 5: 157–170. Retrieved from https://repository.tudelft.nl/view/tno/uuid:4d07f039-a6b0-44af-94e4-0b1589bb1851/
Wen, X.-H., Durlofsky, L. J., and Chen, Y. 2006. Efficient 3D Implementation of Local-Global Upscaling for Reservoir Simulation. SPE J. 11 (4): 443–453. SPE-92965-PA. https://doi.org/10.2118/92965-PA.
Zhang, Z., Geiger, S., Rood, M. et al. 2017. Flow Diagnostics on Fully Unstructured Grids. Presented at the SPE Reservoir Simulation Conference, Montgomery, Texas, 20–22 February. SPE-182635-MS. https://doi.org/10.2118/182635-MS.