Presenter
Dr. Wei Yu
Research Associate
Hildebrand Department of Petroleum and Geosystems Engineering
The University of Texas at Austin
Abstract
Conductive fracture networks in conventional reservoirs and recent fracture diagnostics’ results and fracture propagation models in unconventional reservoirs motivate efficient and accurate handling of natural and hydraulic fractures in reservoir simulation studies. In this talk, we will present 10-year development experience of our embedded discrete fracture model (EDFM) and EDFM artificial intelligence (EDFM-AI) technology. EDFM has proven to be the best fracture modeling technology to simulate any type of fracture geometry and orientation in discrete fracture networks. Additionally, EDFM integrates seamlessly into existing industry frameworks to perform studies using realistic fracture models. This technology enhances existing reservoir models, drastically improves production forecasting, and provides optimization and development strategies for both primary and enhanced oil recovery applications. Successful field-scale case studies in naturally and hydraulically fractured reservoirs include water intrusion in carbonate reservoirs, fracture connectivity studies, geothermal modeling, fracture hits assessment, calibration of fracture properties with production data, distributed temperature sensing modeling, geomechanics with complex fractures, and gas huff-n-puff applications in Eagle Ford and Permian Basin. The application of this technology is critical because fractures can dominate results seen in the field and can have a major impact on the development of both conventional and unconventional reservoirs.
