Pattern Recognition-Driven Automatic Drainage Region Mapping to Accelerate Reservoir Simulations

Abstract

History matching is widely considered as the most time- and resource-consuming phase of reservoir simulation modeling. Even with the advent of modern, computer-assisted, history matching methods, the dynamic calibration of large-scale simulation models represents a considerable computational undertake. The challenges become even more pronounced with incorporation of subsurface and production uncertainty. This paper outlines a step forward in acceleration of reservoir simulation studies by applying a split/merge approach constrained by no-flow boundary drainage region. The method transforms the history-matching process into an accelerated progressive sequence of dynamic model updates in time and space. Each segment defined as distinctive drainage region, the boundaries of the drainage regions are mapped based on no-flow conditions. Each segment is dynamically calibrated and history matched simultaneously in parallel. Lastly, the segments are merged back to reconstruct the original model to run the prediction phase. The detail of the workflow is described, as well as the implementation of the workflow in a synthetic model. A comparison between the conventional approach and the new approach is discussed. Recommendation and a way forward are shared to capitalize on the accelerated method for future reservoir studies.