Identifying hydrocarbon reserves of a subterranean region using a reservoir earth model that models characteristics of the region

A system for determining characteristics of an underground formation in a subterranean region of a geological area, the system comprising:

• one or more processing devices and one or more non-transitory machine-readable storage devices storing instructions that are executable by the one or more processing devices to cause performance of operations comprising:
• obtaining a first wavefield represented by seismic data generated from a plurality of sampling sensors, wherein a subset of the sampling sensors are deployed in the subterranean region;
• providing data values of the seismic data that indicate properties of the underground formation as inputs to a machine-learning engine configured to generate one or more models;
• processing the inputs corresponding to data values of the seismic data using the machine-learning engine;
• in response to processing the data values of the seismic data, generating a plurality of predictive models, each predictive model comprising a neural network having interconnected nodes that are configured to determine geological properties of a layer in the underground formation based on a respective analytical rule of the predictive model;
• providing, to each of the predictive models, new data values of seismic data representing a second wavefield obtained using the subset of sampling sensors;
• automatically updating the respective analytical rule of each predictive model in response to processing the new data values of seismic data at the predictive model;
• and
• determining, from the new data values of seismic data, (i) a first geological property of the layer using the updated analytical rule of a first predictive model and (ii) a second, different geological property of the layer using the updated analytical rule of a second, different predictive model.