Based modeling (dbm) workflows in subsurface reservoirs This study aims to advance the application of artificial intelligence (ai) in reservoir modeling by developing and evaluating machine learning (ml) te⦠Sbed (sedimentary bedding) offers a comprehensive and systematic workflow for reservoir modeling, leveraging advanced technology and deep learning to transform traditional practices
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This workflow is designed to provide unparalleled accuracy and insight into subsurface environments.
This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.
This includes reservoir engineers, geologists, geophysicists, petrophysicists, technologists, technical managers and geomodelers.