Systems and methods for analyzing uncertainty and sensitivity of fault populations

A non-transitory, computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations, the operations comprising:

• receiving seismic data representing a subterranean domain, the subterranean domain includes a plurality of faults;
• generating a plurality of fault volumes based upon the seismic data, each of the fault volumes includes one or more of the faults;
• generating a plurality of fault populations based upon the fault volumes, each of the fault populations includes one or more of the faults, and the fault populations are generated by:
• extracting two or more different fault objects from one of the fault volumes, or
• extracting a first one of the fault objects from a first one of the fault volumes, and
• extracting a second one of the fault objects from a second one of the fault volumes;
• generating quantitative values based upon the fault populations, the quantitative values represent one or more of the fault objects, one or more of the fault populations, or both, and the quantitative values include numeric measures of the fault populations, geometric measures of the fault objects, topologic measures of the fault objects and the fault populations, seismic amplitudes at locations of the fault objects, an image analysis of the seismic amplitudes at the locations of the fault objects, or a combination thereof;
• comparing the quantitative values to determine an uncertainty of a representation of the fault populations, comparing the quantitative values includes generating a visual representation of the quantitative values;
• displaying the visual representation on a display.

A computing system, comprising:

• one or more processors;
• and
• a memory system coupled to the one or more processors and including one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations including:
• receiving seismic data representing a subterranean domain, the subterranean domain includes a plurality of faults;
• generating a plurality of fault volumes based upon the seismic data, each of the fault volumes includes one or more of the faults, and each of the fault volumes is generated using a machine learning (ML) model or using an image analysis technique;
• generating a plurality of fault populations based upon the fault volumes, each of the fault populations includes one or more of the faults, the fault populations are generated by:
• extracting two or more different fault objects from one of the fault volumes, or
• extracting a first one of the fault objects from a first one of the fault volumes, and extracting a second one of the fault objects from a second one of the fault volumes,
• each fault object represents a corresponding one of the faults as a set of points from the fault volume in three dimensions, and
• the fault objects are extracted after varying one or more parameters,
• generating quantitative values based upon the fault populations, the quantitative values represent one or more of the fault objects, one or more of the fault populations, or both, and the quantitative values include numeric measures of the fault populations, geometric measures of the fault objects, topologic measures of the fault objects and the fault populations, seismic amplitudes at locations of the fault objects, image analysis of the seismic amplitudes at the locations of the fault objects, or a combination thereof;
• comparing the quantitative values to determine an uncertainty of a representation of the fault populations, comparing the quantitative values includes generating a visual representation of the quantitative values;
• displaying the visual representation on a display;
• and
• building or updating a model of the subterranean domain based upon the uncertainty.