Synthetic subterranean source

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

• inducing an acoustic energy in a first object that extends into one or more subterranean formations from at or near a terranean surface, the first object comprising an infrastructure object, the acoustic energy propagating from the first object to a second object, the second object enclosed within the one or more subterranean formations;
• recording, using an array of transducers, reflected acoustic energy that propagates from the second object to the array of transducers;
• providing the recorded, reflected acoustic energy as an input to a machine learning algorithm to generate image data associated with the second object;
• generating, with the machine learning algorithm, a subsurface model that comprises the generated image data associated with the second object for presentation in a graphical user interface;
• determining that a condition of the second object is poor based on the subsurface model;
• and
• identifying an excavation location associated with the second object.

A system for generating a global subsurface model, the system comprising:

• one or more processors;
• one or more tangible, non-transitory media operably connectable to the one or processors and storing instructions that, when executed, cause the one or more processors to perform operations comprising:
• inducing an acoustic energy in a first object that extends into one or more subterranean formations from at or near a terranean surface, the first object comprising an infrastructure object, the acoustic energy propagating from the first object to a second object, the second object enclosed within the one or more subterranean formations;
• recording, using an array of transducers, reflected acoustic energy that propagates from the second object to the array of transducers;
• providing the recorded, reflected acoustic energy as an input to a machine learning algorithm to generate image data associated with the second object;
• generating, with the machine learning algorithm, a subsurface model that comprises the generated image data associated with the second object for presentation in a graphical user interface;
• determining that a condition of the second object is poor based on the subsurface model;
• and
• identifying an excavation location associated with the second object.