Abstract
Accurate determination of fluid saturation and organic matter content is essential for the characterization and assessment of organic-rich source rock reserves. However, few advanced techniques are available to precisely identify fluid-porous systems and define prospective deposits throughout various stages of field exploration. This paper explores the combined application of two widely utilized methods - low-field nuclear magnetic resonance relaxometry (NMR) and Rock-Eval pyrolysis - using an expanded suite of rock samples. The primary objective of this study is to establish optimized workflows that offer a more comprehensive quantification of liquid saturation with heavy to mobile hydrocarbons compared to standard industry practices and help to identify the fluid volumetric model of the target formation. Main findings demonstrate correlations between NMR-obtained data, mineral composition of the rock and organic matter components by Rock-Eval pyrolysis. The detailed analysis and comparison of experimental results is performed using the manual interpretation of NMR T(1)-T(2) maps and Mutual Information regression approach that processed the NMR T(2) spectrum. The research lays the groundwork for NMR-based Machine Learning-assisted in situ characterization of mineral components (quartz and clays), crude oil maturity and volume for shale deposits, along with determining the ratio between bound and mobile oil components.