Stochastic soil property modeling via deep neural networks

A processing system, comprising:

• a memory comprising computer-executable instructions;
• and
• a processor configured to execute the computer-executable instructions and cause the processing system to:
• receive seismic data associated with a subsurface region;
• incorporate noise into the seismic data to create modified seismic data;
• input the modified seismic data into a machine-learning model configured to output a predicted subsurface property;
• obtain from the machine-learning model, the predicted subsurface property, wherein the predicted subsurface property is based on the modified seismic data;
• and
• derive an associated measure of uncertainty for the predicted subsurface property, wherein the predicted subsurface property is associated with the subsurface region.

A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of a computer system, cause the computing system to perform operations for estimating subsurface properties, the operations comprising:

• receiving seismic data associated with a subsurface region;
• incorporating noise into the seismic data to create modified seismic data;
• inputting the modified seismic data into a machine-learning model configured to output a predicted subsurface property;
• obtaining from the machine-learning model, the predicted subsurface property, wherein the predicted subsurface property is based on the modified seismic data;
• and
• deriving an associated measure of uncertainty for the predicted subsurface property, wherein the predicted subsurface property is associated with the subsurface region.