Generating a velocity model for a subsurface structure using a machine learning model

A method for training a machine learning model selector comprising:

• generating, using obtained seismic data and sonic log data, one or more Time-to-Depth Relationship (TDR) curves;
• generating, using (i) the seismic data and sonic log data and (ii) the one or more TDR curves, a combined set of seismic data and sonic log data;
• selecting, using a selector engine and the combined set of seismic data and sonic log data, one or more seismic reflectors;
• providing the combined set of seismic data and sonic log data to a machine learning model selector;
• in response to providing the combined set of seismic data and sonic log data to the machine learning model selector, generating an output result from the machine learning model selector;
• comparing the one or more seismic reflectors and the output result from the machine learning model selector;
• and
• updating, using the comparison of the one or more seismic reflectors and the output result from the machine learning model selector, the machine learning model selector.

A non-transitory computer-readable medium storing instructions executable by a computer system to perform operations comprising:

• generating, using seismic data and sonic log data from a subterranean surface, one or more Time-to-Depth Relationship (TDR) curves;
• generating, using (i) the seismic data and sonic log data and (ii) the one or more TDR curves, a combined set of seismic data and sonic log data;
• selecting, using:
• (a) one or more of (i) a selector engine or (ii) machine learning model selector, and (b) the combined set of seismic data and sonic log data, one or more seismic reflectors;
• generating, using the one or more seismic reflectors, a velocity model update;
• generating, using the velocity model update and one or more operations of pre-stack depth migration, a candidate final velocity model;
• determining the candidate final velocity model satisfies a matching threshold;
• and
• in response to determining the candidate final velocity model satisfies the matching threshold, providing the final velocity model as output.