System and method for automated seismic interpretation

A system, comprising:

• one or more processors;
• memory;
• and
• one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions that when executed by the one or more processors cause the system to:
• receive a pre-stack seismic dataset representative of a subsurface volume of interest;
• identify seismic facies in the pre-stack seismic dataset based on machine learning, wherein the machine learning identifies the seismic facies based on clustering of amplitude variation with angle (AVA) in the pre-stacked seismic dataset, wherein the seismic facies correspond to AVA clusters and include cluster sequences in depth for a plurality of spatial x-y locations in the subsurface volume of interest;
• generate an ensemble of fluid-related AVA responses for the AVA clusters based on a fluid substitution operation;
• identify, based on the ensemble of fluid-related AVA responses, related seismic facies across faults indicated in the pre-stack seismic dataset, wherein the related seismic facies contain different fluids but similar lithologies than the seismic facies;
• perform seismic interpretation of the pre-stacked seismic dataset based on the seismic facies and the related seismic facies to generate a digital image of the seismic interpretation;
• and
• display the digital image on a user interface.

A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to:

• receive a pre-stack seismic dataset representative of a subsurface volume of interest;
• identify seismic facies in the pre-stack seismic dataset based on machine learning, wherein the machine learning identifies the seismic facies based on clustering of amplitude variation with angle (AVA) in the pre-stacked seismic dataset, wherein the seismic facies correspond to AVA clusters and include cluster sequences in depth for a plurality of spatial x-y locations in the subsurface volume of interest;
• generate an ensemble of fluid-related AVA responses for the AVA clusters based on a fluid substitution operation;
• identify, based on the ensemble of fluid-related AVA responses, related seismic facies across faults indicated in the pre-stack seismic dataset, wherein the related seismic facies contain different fluids but similar lithologies than the seismic facies;
• perform seismic interpretation of the pre-stacked seismic dataset based on the seismic facies and the related seismic facies to generate a digital image of the seismic interpretation;
• and
• display the digital image on a user interface.