Drilling decision system and method of multimodal lithofacies prediction and decision-making

Abstract

A system and method for drilling decision system based on multimodal lithofacies identification includes an image data collection interface for collecting data from digital photos, remote sensing maps and scanning electron microscope (SEM) images. A first convolutional neural network (CNN) model to extract visual features from digital photos, a second CNN model to extract spatial-structural features from the remote sensing maps and a third CNN model to extract microstructural features from the SEM images. An output feature layer combines the extracted features from the first, second and third CNN models to output combined imaging features, a 1-D CNN model extracts the features from the combined imaging features and performs only 1D convolutions. A Neural Network (NN) classifier takes features from the output of 1-D CNN model to predict lithofacies classes with respective composition percentages. An output device configured to output a decision based on the predicted lithofacies classes.