Fast History Matching of Finite-Difference Models Using Streamline-Based Sensitivities
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We propose a novel approach to history matching finite-difference models that combines the advantages of streamline models with the versatility of finite-difference simulation. Current streamline models are limited in their ability to incorporate complex physical processes and cross-streamline mechanisms in a computationally efficient manner. A unique feature of streamline models is their ability to analytically compute the sensitivity of the production data with respect to reservoir parameters using a single flow simulation. These sensitivities define the relationship between changes in production response because of small changes in reservoir parameters and, thus, form the basis for many history-matching algorithms. In our approach, we use the streamline-defived sensitivities to facilitate history matching during finite-difference simulation. First, the velocity field from the finite-difference model is used to compute streamline trajectories, time of flight, and parameter sensitivities. The sensitivities are then used in an inversion algorithm to update the reservoir model during finite difference simulation. The use of a finite-difference model allows us to account for detailed process physics and compressibility effects. Although the streamline-derived sensitivities are only approximate, they do not seem to noticeably impact the quality of the match or the efficiency of the approach. For history matching, we use a generalized travel-time inversion (GTTI) that is shown to be robust because of its quasilinear properties and that converges in only a few iterations. The approach is very fast and avoids many of the subjective judgments and time-consuming trial-and-error steps associated with manual history matching. We demonstrate the power and utility of our approach with a synthetic example and two field examples. The first one is from a CO2 pilot area in the Goldsmith San Andreas Unit (GSAU), a dolomite formation in west Texas with more than 20 years of waterflood production history. The second example is from a Middle Eastern reservoir and involves history matching a multimillion-cell geologic model with 16 injectors and 70 producers. The final model preserved all of the prior geologic constraints while matching 30 years of production history. Copyright © 2005 Society of Petroleum Engineers.
author list (cited authors)
Cheng, H., Kharghoria, A., He, Z., & Datta-Gupta, A.