Reservoir Model

Reservoir modeling aims to simulate fluid flow and other processes within porous subsurface formations, crucial for optimizing oil and gas extraction, carbon sequestration, and groundwater management. Current research heavily emphasizes the development and application of machine learning techniques, particularly deep learning architectures like Physics-Informed Neural Operators (PINOs) and neural networks, to create efficient surrogate models that significantly accelerate simulations and improve uncertainty quantification. These advancements enable faster history matching, improved reservoir characterization, and more effective optimization of well placement and production strategies, ultimately leading to more efficient and sustainable resource management.