System and method for seismic facies identification using machine learning

Abstract

A method is described for seismic facies identification including receiving a seismic dataset representative of a subsurface volume of interest; performing a machine learning algorithm on the seismicdataset to identify seismic facies and generate a classified seismic image; and identifying geologic features based on the classified seismic image. The method may be executed by a computer system.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of priority to U.S. Provisional Application Serial No. 62 / 408188, filed October 14, 2016, the entire contents of which are incorporated herein by reference. [0003] Statement Regarding Federally Sponsored Research or Development [0004] Not applicable. technical field [0005] The disclosed embodiments relate generally to techniques for identifying facies in subterranean reservoirs, and in particular to methods of identifying facies from seismic data by machine learning. Background technique [0006] Seismic exploration involves surveying subsurface geological media for hydrocarbon deposition. Surveying typically involves deploying seismic sources and sensors at predetermined locations. Seismic sources generate seismic waves that propagate into the geological medium, producing pressure changes and vibrations. Changes in the physical properties of the geological medium cause cha...

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Problems solved by technology

Moreover, these track-by-track methods are time-consuming and create bottlenecks in characterizing the subsurface

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