Reproduction of channel stacking patterns in geomodeling: metrics and impact of the modeling strategy on reservoir flow behavior

@inproceedings{scarpa_reproduction_RM2023,
 abstract = {Channelized turbidite systems are often grouped into complexes and exhibit various stacking patterns. The internal architectures of these systems play a crucial role in controlling the connectivity between high-permeability and low-permeability sedimentary bodies, making them a fundamental property of reservoirs. While some studies have analyzed the static connectivity of different stacking patterns, few have quantitatively evaluated the dynamic implications of these patterns on fluid flow circulation. In this study, we investigate the impact of different classes of geostatistical modeling methods on static and dynamic connectivity using multiple metrics. The stacking patterns are generated using an object-based method based on Lindenmayer systems. A dataset of 300 stochastic realizations is categorized into three groups: i) disorganized channels, ii) independent channels conditioned to a vertical sand proportion map, and iii) organized stacking that reproduces vertical and lateral migration of channels. To analyze the hydrodynamic responses, we set up a two-phase system consisting of oil and water. Reservoir simulations are performed in all stochastic scenarios, and connectivity is computed on simulation grids to determine correlations between metrics. This approach enables a comparison of flow simulations and highlights the delayed water breakthrough time in disorganized stacking patterns and less optimistic recovery efficiency in organized stacking patterns. Our study confirms the positive forecasting bias observed in conventional geostatistical modeling. By investigating both static and dynamic connectivity metrics, we provide an understanding of the impact of different stacking patterns on fluid flow behavior in channelized turbidite systems.},
 author = {Scarpa, Enrico and Collon, Pauline and Panfilov, Irina and Caumon, Guillaume},
 booktitle = {2023 {RING} meeting},
 language = {en},
 pages = {21},
 publisher = {ASGA},
 title = {Reproduction of channel stacking patterns in geomodeling: metrics and impact of the modeling strategy on reservoir flow behavior},
 year = {2023}
}