Predicting well markers from artificial neural-network-predicted lithostratigraphic facies

Abstract

This disclosure generally describes methods and systems, including computer-implemented methods, computer-program products, and computer systems, for predicting well markers. One computer-implemented method includes separating neural-network (NN)-predicted facies output associated with a plurality of wells into two sets, a first set of NN-predicted facies output of training wells and a second set of NN-predicted facies output of target wells, calculating, for each training well of the plurality of wells, a sameness score between zones of NN-predicted facies output and human-identified lithostratigraphic units (finer zones), calculating a mean sameness score for the finer zones for all training wells, identifying finer zones with a mean sameness score greater than a threshold value as dominant facies zones, and iterating over each target well to calculate a top and depth position of each dominant facies zone determined based upon the NN-predicted facies output of the target well.