Automated fault surfaces extraction from 3D fault imaging volume
Nam V. Nguyen, Alejandro Jaramillo · 2022
A new method leverages network analysis data science technique to automatically extract fault surfaces from 3D fault imaging volume by applying a three-step process: (1) determine fault samples with primary attributes of depth, amplitude, and vertical thickness for each trace location from an input volume; (2) compute additional attributes dip and azimuth for each fault sample; and (3) extract fault surfaces by applying network analysis to connect nearby fault samples with similar fault attributes. The extracted fault surfaces can be integrated into a geological model for identification of hydrocarbon bearing formations, improving structural trapping definition, and preventing drilling hazards.