Geosteering using improved data conditioning

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:

• estimating physical parameters from a training dataset comprising remote sensing data;
• preprocessing the estimated physical parameters to determine a signal-to-noise ratio, quantify an uncertainty, and remove outliers;
• training a first neural network to convert the estimated physical parameters to rock characteristics;
• training a second neural network to convert the rock characteristics to the estimated physical parameters;
• converting the rock characteristics into reconciled physical parameters with the second neural network;
• converting the estimated physical parameters into the rock characteristics with the first neural network;
• training a third neural network to convert the estimated physical parameters to reconciled physical parameters;
• obtaining new remote sensing data;
• estimating new estimated physical parameters from the new remote sensing data;
• and
• converting new estimated physical parameters into new reconciled physical parameters with the third neural network.

A system for reconciling physical parameters, comprising:

• a geosteering system configured to guide a drill bit in a well;
• and
• a computer system configured to:
• estimate physical parameters from a training dataset comprising remote sensing data,
• preprocess the estimated physical parameters to determine a signal-to-noise ratio, quantify an uncertainty, and remove outliers,
• train a first neural network to convert the estimated physical parameters to rock characteristics,
• train a second neural network to convert the rock characteristics to the estimated physical parameters,
• convert the rock characteristics into reconciled physical parameters with the second neural network,
• convert the estimated physical parameters into the rock characteristics with the first neural network,
• train a third neural network to convert the estimated physical parameters to reconciled physical parameters,
• obtain new remote sensing data,
• estimate new estimated physical parameters from the new remote sensing data,
• convert new estimated physical parameters into new reconciled physical parameters with the third neural network, and
• perform geosteering of the well based on a subsurface geology interpreted from the new reconciled physical parameters.