Data Driven Porosity Measurement for Non-homogeneous Sandstone

Pore structure is a critical factor in evaluating the quality of a reservoir or cap layer, influencing storage capacity, fluid flow efficiency, and reaction rates. Standard approaches, including Mercury Intrusion Porosimetry (MIP), Gas Pycnometry, and Brunauer-Emmett-Teller (BET) analysis, provide essential information; they are limited in their ability to capture pore connectivity and pathway complexity. X-ray Computed Tomography (CT) provides a distinct perspective, enabling three dimensional visualization of pore structures and insights into pore connectivity within 3D images. Accurate porosity analysis using CT, however, depends on careful evaluation of the segmentation process, especially the selection of thresholding methods, which can introduce biases and impact the reliability of the results. To address these challenges, this study introduces a new workflow leveraging grey-level terrain parameters from CT images as a reference index. Interbedded samples of muddy sandstone and siltstone are analyzed, with CT-derived porosity compared to experimental results obtained from an AccuPyc Helium Pycnometer. This comparison assesses the reliability and accuracy of the data-driven approach. By reducing uncertainties associated with porosity thresholding, the proposed workflow aims to establish a robust framework for CT-based pore structure analysis. It highlights the ability of CT imaging to deliver detailed 3D pore analysis, thereby supporting improved predictions of reservoir properties and resource management.