Fracability analysis and comprehensive evaluation of engineering sweet spot of tight sandstone gas reservoir in T area of Sichuan Basin, China

Natural gas as a viable alternative to reducing dependence on coal and oil in the process of energy restructuring and carbon neutrality goals. The efficient development of tight sandstone gas requires accurate evaluation of reservoir fracability and selection of layers and segments for fracturing. This study takes the tight sandstone in T area of Sichuan Basin, China as the research object. To achieve the fracturing goal of constructing a complex artificial fracture network, the key parameters affecting the comprehensive fracability of the reservoir are selected based on the fusion analysis of geological, logging, seismic, geomechanical, and microseismic monitoring information. In addition, the weights of each influencing factor are also clarified. The evaluation model of reservoir comprehensive fracability index and the grading evaluation standard of engineering sweet spot are constructed. Combined with geological framework, logging data, seismic attributes, and geomechanical 3D models, the longitudinal and spatial distribution characteristics of reservoir fracability and engineering sweet spot are analyzed. The research results show that high brittleness index, low horizontal minimum principal stress, high fracture density, low horizontal stress difference, low elastic modulus, and high Poisson's ratio are the key of "high sweetness value" of engineering sweet spot in the study area. The evaluation model of comprehensive fracability index (FI) of reservoir is established based on these six key indicators. The brittleness index, horizontal minimum principal stress, and fracture density are the three most critical factors identified by grey correlation method. The results of reservoir comprehensive fracability logging prediction and 3D comprehensive fracability field prediction show that the comprehensive fracability of the reservoir in the study area is non-uniform in the longitudinal, transverse, and spatial distribution, which can provide support for the selection of high fracability intervals and engineering sweet spots.