Subsurface lithological model with machine learning

A computer-implemented method for generating a subsurface model of a subsurface, the method comprising:

• identifying, with one or more processors, geoscience data associated with one or more particular regions of the subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of the subsurface;
• identifying, with one or more processors, remote sensing data associated with the sub surface;
• correlating, with one or more processors, the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating, with one or more processors, an at least partially global subsurface model of the subsurface comprising one or more data layers, each data layer representing at least one geological characteristic of the subsurface wherein the at least partially global subsurface model comprises a continental subsurface model;
• and
• generating, with one or more processors, a graphical representation of the at least partially global subsurface model for display at a user interface.

A system for generating an at least partially global subsurface model, the system comprising:

• one or more processors;
• one or more tangible, non-transitory computer-readable media operably connectable to the one or processors and storing instructions that, when executed, cause the one or more processors to perform operations comprising:
• identifying geoscience data associated with one or more particular regions of a subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of subsurface;
• identifying remote sensing data associated with the subsurface;
• correlating the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating an at least partially global subsurface model of the subsurface comprising one or more data layers, each data layer representing at least one geological characteristic of the subsurface wherein the at least partially global subsurface model comprises a continental subsurface model;
• and
• generating a graphical representation of the at least partially global subsurface model for display at a user interface.

An apparatus that comprises a non-transitory, computer-readable storage medium that comprises instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• identifying geoscience data associated with one or more particular regions of a subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of the subsurface;
• identifying remote sensing data associated with the subsurface;
• correlating the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating an at least partially global subsurface model of the subsurface comprising a repository of data layers arranged in a hierarchy, comprising at least one of:
• (1) publicly shared user data layers, (2) private user data layers, or (3) historical data layers, each data layer representing at least one geological characteristic of the subsurface comprising:
• identifying one or more user data layers provided by a user;
• and generating a graphical representation of the at least partially global subsurface model for display at a user interface and displaying the user data layers in the user interface with the at least partially global subsurface model.

An apparatus that comprises a non-transitory, computer-readable storage medium that comprises instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• identifying geoscience data associated with one or more particular regions of a subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of the subsurface;
• identifying remote sensing data associated with the subsurface;
• correlating the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating an at least partially global subsurface model of the subsurface comprising one or more data layers, each data layer representing at least one geological characteristic of the subsurface, wherein the one or more data layers can be toggled between an active and an inactive state;
• identifying one or more user data layers provided by a user;
• and
• generating a graphical representation of the at least partially global subsurface model for display at a user interface and displaying the user data layers in the user interface with the at least partially global subsurface model.

An apparatus that comprises a non-transitory, computer-readable storage medium that comprises instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• identifying geoscience data associated with one or more particular regions of a subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of the subsurface;
• identifying remote sensing data associated with the subsurface;
• correlating the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating an at least partially global subsurface model of the subsurface comprising one or more data layers, each data layer representing at least one geological characteristic of the sub surface;
• identifying one or more user data layers provided by a user;
• generating a graphical representation of the at least partially global subsurface model for display at a user interface and displaying the user data layers in the user interface with the at least partially global subsurface model;
• and
• in response to a user request, generating a hybrid data layer, wherein the hybrid data layer comprises a combination of data from one or more data layers, and wherein the hybrid data layer is generated pursuant to a desired configuration indicated in the user request.

An apparatus that comprises a non-transitory, computer-readable storage medium that comprises instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• identifying geoscience data associated with one or more particular regions of a subsurface, the geoscience data comprising information associated with the lithology of the one or more particular regions of the subsurface;
• identifying remote sensing data associated with the subsurface;
• correlating the geoscience data with the remote sensing data using at least one machine learning model to determine inferred data representing lithology of one or more regions of the subsurface associated with the remote sensing data where geoscience data is unavailable;
• generating an at least partially global subsurface model of the subsurface comprising one or more data layers, each data layer representing at least one geological characteristic of the subsurface, wherein the at least partially global subsurface model comprises a global subsurface model;
• and
• generating a graphical representation of the at least partially global subsurface model for display at a user interface.