Abstract: A computer-implemented method is described for automated seismic interpretation that includes receiving, at one or more processors, a pre-stack seismic dataset representative of the subsurface volume of interest; performing, via the one or more processors, a machine learning algorithm on the pre-stack seismic dataset to identify seismic facies based on AVA clusters, wherein the identified seismic facies include cluster sequences in depth for a plurality of spatial x-y locations in the subsurface volume; performing, via the one or more processors, seismic interpretation of the seismic dataset based on the identified seismic facies to generate a digital image of the seismic interpretation; and displaying the digital image of the seismic interpretation on a user interface.

Abstract: A method is described for time-lapse seismic imaging that may include detecting moiré patterns in seismic images generated from time-lapse seismic data and identifying geologic features based on the moiré patterns. The method may be executed by a computer system.

Abstract: A method is described for time-lapse seismic imaging that may include detecting moiré patterns in seismic images generated from time-lapse seismic data and identifying geologic features based on the moiré patterns. The method may be executed by a computer system.

Abstract: A computer-implemented method is described for automated seismic interpretation that includes receiving, at one or more processors, a pre-stack seismic dataset representative of the subsurface volume of interest; performing, via the one or more processors, a machine learning algorithm on the pre-stack seismic dataset to identify seismic facies based on AVA clusters, wherein the identified seismic facies include cluster sequences in depth for a plurality of spatial x-y locations in the subsurface volume; performing, via the one or more processors, seismic interpretation of the seismic dataset based on the identified seismic facies to generate a digital image of the seismic interpretation; and displaying the digital image of the seismic interpretation on a user interface.

Abstract: A method is described for seismic imaging that may include receiving a partially flattened seismic image representative of a subsurface volume of interest; detecting moire patterns in the partially flattened seismic image; quantitatively characterizing the moire patterns; calculating flattening corrections based on the quantitatively characterized moire patterns; applying the flattening corrections to the partially flattened seismic image to generated a new flattened seismic image; and identifying geologic features based on the new flattened seismic image. The method may be executed by a computer system.

Abstract: A method is described for time-lapse seismic imaging that may include detecting moire patterns in seismic images generated from time-lapse seismic data and identifying geologic features based on the moire patterns. The method may be executed by a computer system.