Abstract

Latest advances in shale gas reservoir simulation and modeling have made it possible to optimize and enhance the production from organic rich shale gas reservoirs.

Reservoir simulator is no longer used with a simple description of the complex shale gas reservoirs, but with multiple, equally probable realizations to allow risk assessment. Nevertheless, the perennial challenge in shale reservoir modeling is to strike a balance between explicit representation of reservoir complexity and long simulation run time for multiple realizations.

Focus of this study is on the development, calibration and validation of a Shale Surrogate Reservoir Model (AI-based proxy model) that represents a series of complex shale numerical simulation models. The Shale Surrogate Reservoir Model is then used for fast track analysis of the shale numerical model. Reservoir simulation model for a generic shale gas reservoir are constructed using a popular commercial simulator that is capable of handling complex fracture network (natural and multiple stages of hydraulic fractures), different sorption types (instantaneous and time dependent one), and capturing long transient nature of the flow in shale matrix. Validation of the Shale Surrogate Reservoir model using several blind simulation runs is also presented.

Shale Surrogate Reservoir Model is a replica for the numerical simulation model with response that is measured in fractions of a second. As such, it provides the means for comprehensive and fast track analysis of the model in a relatively short period of time, allowing the reservoir engineer to scrutinize different realizations and propose development strategies.

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