Geologic Modeling of Eagle Ford Facies Continuity Based on Outcrop Images and Depositional Processes
- Pejman Tahmasebi (University of Texas at Austin (currently with University of Wyoming)) | Farzam Javadpour (University of Texas at Austin) | Gregory Frébourg (University of Texas at Austin (currently with Thermal Energy Partners))
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- August 2018
- Document Type
- Journal Paper
- 1,359 - 1,371
- 2018.Society of Petroleum Engineers
- higher-order statistics, mudrock reservoirs, Stochastic modeling, Eagle Ford Group, facies
- 0 in the last 30 days
- 203 since 2007
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Geologic modeling of mudrock reservoirs is complicated by the presence of multiscale heterogeneities and lithofacies lateral discontinuity. The resolution of wireline logs is also too low to capture many small-scale heterogeneities that affect fluid flow. In addition, the large distance between logged wells results in uncertain long-range correlations. Supplementary to wireline log data, high-resolution outcrop images offer a direct representation of detailed heterogeneities and lithofacies connectivity. We used high-resolution panoramic outcrop images to collect data on lithofacies heterogeneity and the role that depositional processes play in this heterogeneity. We then used these data in different classes of reservoir algorithms—two-point-based, object-based, and higher-order statistics—to build a geologic model. To present our methodology, we used data collected from Eagle Ford outcrops in west Texas. We found the higher-order-statistics method to be especially efficient, capable of reproducing details of heterogeneity and lithofacies connectivity.
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