Unconventional/complex reservoirs

Deep-Learning Framework Forecasts Dynamics of Carbon Dioxide Mineralization

This paper develops a deep-learning work flow that can predict the changes in carbon dioxide mineralization over time and space in saline aquifers, offering a more-efficient approach compared with traditional physics-based simulations.

MS Conceptual reactive rock reservoir model populated with the heterogeneous permeability values (10 – 100 mD), cylindrical view.
MS Conceptual reactive rock reservoir model populated with the heterogeneous permeability values (10 – 100 mD), cylindrical view.

Reactive rocks, when exposed to CO2-charged waters, can undergo a series of reactions leading to the formation of stable carbonates. These carbonates can store carbon for thousands of years. To better understand the interplay between CO2 and brine in these reactive formations, numerical simulations are a useful tool. However, simulating fluid flow in these reservoirs can pose significant computational challenges.

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