Geosteering using reconciled subsurface physical parameters

A non-transitory computer-readable memory comprising computer-executable instructions stored thereon that, when executed on a processor, cause the processor to perform the steps of:

• obtaining reconciled physical parameters at each of a plurality of locations within a subsurface;
• training at least one machine learning network to classify the reconciled physical parameters into a rock type based, at least in part, on the reconciled physical parameters;
• classifying the reconciled physical parameters into the rock type with the at least one machine learning network;
• and
• interpreting the rock type to form a subsurface geology model and inform a geosteering decision.

A system, comprising:

• a computer, configured to:
• obtain reconciled physical parameters at each of a plurality of locations within a subsurface,
• train at least one machine learning network to classify the reconciled physical parameters into a rock type based, at least in part, on the reconciled physical parameters,
• classify the reconciled physical parameters into the rock type with the at least one machine learning network, and
• interpret the rock type to form a subsurface geology model;
• and
• a geosteering system, configured to guide a drill bit through the subsurface.