Leveraging artificial intelligence in the onshore play exploration: A case study from the Macuspana Basin, Mexico

This study focuses on the Macuspana Basin, specifically the Miocene Amate formation, which serves as a key hydrocarbon play. A detailed analysis was conducted using depth-migrated 3D seismic data to evaluate the exploration potential of this prolific onshore play. The methodology incorporated semi-automatic interpretation, where geological horizons were automatically generated using seismic global interpretation (Paguet et al, 2009), streamlining the process of identifying and characterizing subsurface features. The integration of Artificial Intelligence (AI) applications, as the automatic fault detection, in seismic interpretation has allowed for enhanced accuracy and efficiency in delineating reservoir boundaries, providing valuable insights into the subsurface structure and its hydrocarbon potential. This approach represents a significant advancement in exploration strategies for onshore oil and gas basins.