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We propose an efficient method for detecting and extracting fault surfaces in 3D-seismic volumes. The seismic data are transformed into a volume of local-fault-extraction ͑LFE͒ estimates that represents the likelihood that a given point lies on a fault surface. We partition the fault surfaces into relatively small linear portions, which are identified by analyzing tilted and rotated subvolumes throughout the region of interest. Directional filtering and thresholding further enhance the seismicdoi:10.1190/1.2215357 fatcat:nsl6ptzgcvfopowaxj24pjl6cq