Uninterpreted Seismic profiles, slices and maps: study from NE India

This study evaluates unsupervised machine learning (ML) models for seismic facies mapping within the Barail group from the Amguri region, Upper Assam basin, northeast India. Utilizing high-quality three-dimensional seismic data, a comprehensive set of seismic attributes is extracted, optimally selected, and integrated using two unsupervised models: the self-organizing map (SOM) and generative topographic mapping (GTM). The models are compared to identify the most effective approach for discerning seismic facies patterns within the Barail-Coal-Shale (BCS) and Barail-Main-Sand (BMS) units