System and method for facies-guided seismic image super-resolution

Abstract

A facies classification apparatus and method of training the apparatus is provided for seismic image super-resolution. The apparatus includes an input for receiving a low resolution seismic images extracted from a seismic volume and a feature extraction section to extract features from the low resolution images. A non-linear feature mapping section generates feature maps using a self-calibrated block with pixel attention having a plurality of Depthwise Separable Convolution (DSC) layers. A late upsampling section combines at least one DSC layer that upsamples the feature maps to a predetermined dimension. An output provides approximate upsampled super-resolution seismic images that correspond to the low resolution seismic images, with a desired scale of at least two times the low resolution seismic image. A pretrained facies classifier classifies facies in the seismic volume based on the approximate upsampled super-resolution seismic images to obtain class labels.

Dependencies are inferred from the claim text.