Abstract: A method may include obtaining core image data regarding a geological region of interest. The method may further include obtaining well log data regarding the geological region of interest from one or more wells. The method may further include determining a sliding window that corresponds to a predetermined window size. The method may further include determining various quantitative image attributes using the core image data, the well log data, and the sliding window. The quantitative image attributes may be determined in a continuous manner by moving the sliding window along the core image data. The method may further include generating predicted rock data for the geological region of interest using the quantitative image attributes, a machine-learning algorithm, and a machine-learning model.

Abstract: Systems, methods, and apparatus including computer-readable mediums for managing training wells for target wells in machine learning are provided. In one aspect, a method includes: for each training well of a plurality of training wells, building a training network for the training well based on well log data of the training well, predicting a target well log of a target well using the training network built for the training well, determining a relevancy level between the training well and the target well based on the predicted target well log of the target well and a measured target well log of the target well, and selecting relevant training wells among the plurality of training wells based on the relevancy levels associated with the plurality of training wells.

Abstract: A method may include obtaining core image data regarding a geological region of interest. The method may further include obtaining well log data regarding the geological region of interest from one or more wells. The method may further include determining a sliding window that corresponds to a predetermined window size. The method may further include determining various quantitative image attributes using the core image data, the well log data, and the sliding window. The quantitative image attributes may be determined in a continuous manner by moving the sliding window along the core image data. The method may further include generating predicted rock data for the geological region of interest using the quantitative image attributes, a machine-learning algorithm, and a machine-learning model.