Breakthrough in Fractured Reservoir Modeling: p-EDFM Approach Resolves Complexities and Accelerates Hydrocarbon Recovery

Abstract Fractured reservoirs present unique challenges in the oil and gas sector due to their complex genesis and fluid flow dynamics. Modeling these reservoirs requires overcoming various hurdles, including characterizing complex fracture networks, understanding dual-porosity flow dynamics, and managing scale dependencies. This paper highlights advancements in fractured reservoir modeling technology achieved through a collaborative effort between industry and academia. Our research and technological advancements have culminated in a commercial simulation solution tailored for fractured heterogeneous reservoirs, integrating the projection-based embedded discrete fracture modeling approach (p-EDFM). This method effectively models multiphase fluid flow within highly fractured formations, sidestepping grid complexities and expediting simulation processes. In p-EDFM, fractures are distinctly represented as discrete entities, each with their unique geometry and properties, embedded within a porous matrix with its own characteristics. This breakthrough significantly enhances simulation capabilities for practical applications and establishes a solid foundation for future strides in dynamic, multilevel, multiscale simulations. The new modeling technology facilitates more accurate reservoir characterization, enabling enhanced reservoir management strategies that optimize production rates and maximize hydrocarbon recovery. Additionally, the ability to predict fluid flow dynamics within fractured reservoirs with greater precision empowers operators to mitigate operational risks and minimize environmental impacts, promoting sustainable resource extraction practices. This paper offers novel insights by presenting advanced modeling techniques specifically tailored for fractured reservoirs, including scenarios involving hydraulic fractures where applicable. The performance-to-accuracy ratio achieved by this technology supports effective uncertainty and optimization