Predicting total organic carbon (TOC) using a radial basis function (RBF) model and nuclear magnetic resonance (NMR) data

摘要

Systems, methods, and software for predicting total organic carbon (TOC) values are described. A representative method includes obtaining nuclear magnetic resonance (NMR) data and training a radial basis function (RBF) model based on the NMR data and measured total organic carbon (TOC) values. The method also includes obtaining subsequent NMR data and employing the trained RBF model to predict TOC values based at least in part on the subsequent NMR data. The method also includes storing or displaying the predicted TOC values.