A method to predict the resistivity index for tight sandstone reservoirs from nuclear magnetic resonance data

Abstract

<p>The relationship between water saturation and resistivity index in tight sandstone reservoirs cannot be simply expressed using the Archie equation. This makes the saturation exponent difficult to determine and the water saturation estimation significantly challenging. Based on fractal theory and the Archie equation, a theoretical power function relationship is used to predict the resistivity index using the nuclear magnetic resonance (NMR) transverse relaxation time. In this study, 36 core samples, which were recovered from tight gas sands of the Upper Triassic Xujiahe Formation in the central Sichuan Basin, southwestern China, were studied using laboratory NMR and resistivity experiments to verify the reliability of the proposed relationship. The results of this study show that this theoretical relationship is only effective for core samples that contain similar pore structures and physical properties. To precisely predict the resistivity index from NMR data in formations with complicated pore structures, these 36 core samples were classified into three types based on the pore structure and physical properties. For each type of core sample, the parameters used in this relationship were calibrated, along with the relationships between the water saturation and resistivity index and the saturation exponents. Finally, the predicted saturation exponents and the experimental results were compared and validated using two tight sandstone reservoirs located elsewhere in China. Using this proposed method, tight sandstone reservoir saturation exponents were predicted from NMR data. Combining the existing cementation exponent prediction technique, the indispensable input parameters in the Archie equation were acquired, and water saturations were accurately estimated in tight sandstone reservoirs.</p>