Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis
by Srikanta Mishra
English | 2024 | ISBN: 1032074523 | 379 pages | True PDF | 20.85 MB
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy).