Prediction of organic richness in shale gas reservoirs using a novel organic-inorganic decoupling seismic inversion method

Abstract

Organic richness is associated with total hydrocarbon content and influences gas generation in shale reservoirs. The prediction of organic enrichment using seismic methods provides valuable information for identifying promising shale gas areas. Current seismic methods typically estimate organic richness using empirical relationships between organic matter (OM) content and elastic properties; these may be suitable for specific areas but cannot be generalized for universal applications. Therefore, developing a physics-based method for predicting OM content in shale gas reservoirs is critical. In this study, we proposed a novel organic-inorganic decoupling amplitude variation with offset (AVO) method by integrating the classical AVO equation with solid substitution theory. OM was considered solid pore-fillings saturated in the shale matrix. The proposed decoupling equation was extended to establish a frequency-dependent inversion framework for computing OM-related dispersion attributes, allowing for direct estimations of organic richness. Theoretical analyses suggested that the accuracy of the decoupling equation could be achieved via adjustable parameters determined using the rock physics method. Model tests demonstrated that the OM-related dispersion attributes were more sensitive to variations in OM content than the traditional P-wave velocity dispersion attribute and the commonly used elastic properties. The results of real data applications validated the superiority of our proposed OM-related dispersion attributes for reliable organic richness estimation, with the estimated results agreeing well with gas production in the study area. As a result, several promising shale gas zones were identified for further exploration. Our proposed method extends traditional fluid factors and can deal with the cases of both fluid and solid saturations in hydrocarbon resources, with widespread applications for hydrocarbon identification in various unconventional reservoirs.