Systems and methods for seismic image generation using deep learning networks

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

• generating a simulated seismic training dataset, wherein the simulated seismic training dataset comprises upgoing signals and downgoing signals, each recorded on hydrophones and geophones;
• training a deep learning network, using the simulated seismic training dataset, to separate the upgoing signals from the downgoing signals;
• obtaining, from a seismic acquisition system comprising hydrophones and geophones, field hydrophone data and field geophone data from a subsurface region of interest, the field hydrophone data and the field geophone data comprising observed upgoing signals and observed downgoing signals;
• wherein the observed downgoing signals are formed in part by reflected downgoing ghost signals;
• separating, using the trained deep learning network, the observed upgoing signals from the observed downgoing signals to yield predicted upgoing signals with the reflected downgoing ghost signals removed;
• generating a seismic image of the subsurface region of interest based, at least in part, on the predicted upgoing signals;
• identifying, using a seismic interpretation workstation, a drilling target based, at least in part, on the seismic image, and
• planning a planned borehole trajectory, using a borehole planning system, based, at least in part, on the drilling target.

A system, comprising:

• a field hydrophone and a field geophone;
• and
• a computer system, configured to:
• generate a simulated seismic training dataset, wherein the simulated seismic training dataset comprises upgoing signals and downgoing signals, each recorded on hydrophones and geophones;
• train a deep learning network, using the simulated seismic training dataset, to separate the upgoing signals from the downgoing signals;
• obtain, from a seismic acquisition system comprising the hydrophone and geophone, field hydrophone data and field geophone data from a subsurface region of interest, the field hydrophone data and the field geophone data comprising observed upgoing signals and observed downgoing signals;
• wherein the observed downgoing signals are formed in part by reflected downgoing ghost signals;
• separate, using the trained deep learning network, the observed upgoing signals from the observed downgoing signals to yield predicted upgoing signals with the reflected downgoing ghost signals removed;
• generate a seismic image of the subsurface region of interest based, at least in part, on the predicted upgoing signals;
• identify, using a seismic interpretation workstation, a drilling target based, at least in part, on the seismic image, and
• plan a planned borehole trajectory, using a borehole planning system, based, at least in part, on the drilling target.