Bandwidth extension via deep neural networks trained on synthetic seismic datasets

Abstract

A method to extend the bandwidth of seismic data. The method includes collecting a seismic dataset from a seismic survey conducted over a subterranean region of interest and generating a plurality of synthetic datasets, where each synthetic dataset comprises an input seismic dataset with a first bandwidth and an associated target seismic dataset with a second bandwidth. The second bandwidth is broader than the first bandwidth. Further, each synthetic dataset is generated directly in a time domain and includes an event, where the event includes a geometric shape and a wavelet. The method further includes splitting the plurality of synthetic datasets into a training set, selecting a machine-learned model, training the machine-learned model using the training set, and using the machine-learned model to produce an extended bandwidth seismic dataset from the seismic dataset. The method further includes determining a location of a hydrocarbon reservoir using the extended bandwidth seismic dataset.