Rock facies identification method based on seismic attribute classification using a machine learning network

A system comprising:

• a seismic acquisition system;
• a well logging system;
• a computer system configured to:
• receive a three-dimensional (3D) seismic image of a subterranean region using the seismic acquisition system,
• receive a plurality of well logs recorded in each of a plurality of wellbores within the subterranean region using the well logging system,
• identify a horizon within the subterranean region on the 3D seismic image,
• determine a set of bandlimited 3D seismic images of the subterranean region by applying a filter to the 3D seismic image,
• determine a set of mono-frequency maps of the horizon by applying spectral decomposition to the 3D seismic image, wherein a frequency of each mono-frequency map is selected based, at least in part, on a spectrum of the 3D seismic image and the set of bandlimited 3D seismic images,
• determine a seismic attribute map of the horizon based, at least in part, on the set of mono-frequency maps and a machine learning network,
• identify a set of rock facies based, at least in part, on the plurality of well logs recorded in each of the plurality of wellbores and the set of bandlimited 3D seismic images,
• determine a transformation function that maps a subset of rock facies to values of the seismic attribute map,
• determine a rock facies map of the horizon based, at least in part, on the seismic attribute map and the transformation function,
• identify a hydrocarbon reservoir within the subterranean region based, at least in part, on the rock facies map, and
• plan a wellbore within the subterranean region to recover the hydrocarbon reservoir;
• and
• a drill system configured to drill the wellbore within the subterranean region to recover the hydrocarbon reservoir.