Fei Yang

Geological storage of carbon dioxide in faulted sedimentary basins requires suitability evaluation methods that can address uncertainty, indicator interaction, and limited data availability. This study develops an integrated evaluation framework that combines the Analytic Hierarchy Process, triangular fuzzy numbers, and the Choquet fuzzy integral to assess basin-scale geological carbon dioxide storage suitability. The framework enables structured weight determination, explicit representation of expert uncertainty, and non-additive aggregation of interacting indicators. The evaluation focuses on deep saline aquifers in the Jianghan Basin and is based on seventeen indicators covering geological, structural, hydrogeological, and socio-economic conditions. The assessment integrates seismic interpretation, geological mapping, logging data, and published datasets, and is conducted at the level of tectonic units to support basin-scale screening. The method is applied to the Jianghan Basin using seventeen geological, structural, hydrogeological, and socio-economic indicators. The results indicate that burial depth primarily acts as a threshold condition, whereas caprock sealing capacity, fault system development, and hydrogeological stability dominate suitability differentiation. Interaction analysis reveals pronounced substitution effects among geological indicators, indicating that strong performance in key safety-related factors can compensate for less favorable secondary constraints during early-stage screening. The Qianjiang Sag and Jiangling Sag are identified as the most suitable storage units. The proposed framework provides a transparent and robust tool for basin-scale screening in structurally complex, data-limited sedimentary basins.

The Ya’nan sag has experienced more than 40 years of exploration, but only the Ya 13-1 large gas field has been found. In recent years, no oil or gas field has been found, and exploration work is difficult. To clarify the main controlling factors of the oil and gas reservoirs in Ya’nan Sag, the direction of oil and gas exploration is highlighted. Based on 3D seismic data combined with drilling information, this paper determines the basic geological conditions, clarifies the main controlling factors of reservoir formation, and predicts strong exploration directions. The research revealed the following: ① The source rocks of the Yacheng Formation in the Ya’nan sag are developed, and the types are II2-III, with excellent resource potential. ② In-depth analysis of the drilled wells revealed that high-quality reservoirs, oil-source faults, and caprock conditions are the main controlling factors of hydrocarbon accumulation in Ya’nan sag.

The frequency-dependent amplitude-versus-offset (FAVO) method has become a practical method for fluid detection in sand reservoirs. At present, most FAVO inversions are based on the assumption that reservoirs are isotropy, but the application effect is not satisfactory for fractured reservoirs. Hence, we analyse the frequency variation characteristics of anisotropy parameters in tight sandstone reservoirs based on a new petrophysical model, and propose a stepwise anisotropic FAVO inversion method to extract frequency-dependent attributes from prestack seismic field data. First, we combine the improved Brie's law with the fine-fracture model to analyse frequency-dependent characteristics of velocities and Thomsen anisotropy parameters at different gas saturations and fracture densities. Then, we derive an anisotropic FAVO inversion algorithm based on Rüger's approximation formula and propose a stepwise anisotropic FAVO inversion method to obtain the dispersions of anisotropy parameters. Finally, we propose a method that combines the inversion spectral decomposition with the stepwise anisotropy FAVO inversion and apply it to tight sand reservoirs in the Xinchang area. We use P-wave velocity dispersion and anisotropy parameter ε dispersion to optimise favourable areas. Numerical analysis results show that velocity dispersion of the P-wave is sensitive to fracture density, which can be used for fracture prediction in fractured reservoirs. In contrast, anisotropic parameter dispersion is sensitive to gas saturation and can be used for fluid detection. The seismic data inversion results show that velocity dispersion of the P-wave and anisotropic parameter dispersion are sensitive to fractured reservoirs in the second member of Xujiahe Group, which is consistent with logging interpretation results.

Most frequency-dependent AVO inversions are currently based on an approximate equation derived using an isotropic medium. However, actual reservoirs usually show anisotropy, such as shale reservoirs, tight sandstone reservoirs and fractured reservoirs. We propose a joint frequency-dependent AVO (JFAVO) inversion in an anisotropic medium based on a periodic layered double-porosity medium. This JFAVO will allow us to quantitatively study the influence of fluids on the dispersion of PP- and PS-wave velocities and anisotropic parameters. First, we used a double-porosity medium to analyse the frequency-dependent characteristics of velocities and anisotropy parameters. We found that the anisotropic parameters show obvious dispersions, similar to those of velocities. Then, we derived the JFAVO inversion based on Rüger's equation to extract the dispersion of velocities and anisotropic parameters. Finally, we analysed the stability and applicability of the inversion algorithm, and used three sets of models to analyse the sensitivity of dispersion properties to fluids. The numerical analysis results show that PP-wave velocity dispersion and anisotropic parameter δ dispersion are sensitive to fluids, whereas, the velocity dispersion of the PS-wave is not. When saturation exceeds 80%, the velocity dispersion and anisotropic parameter dispersion properties are not sensitive to fluids.