Geomechanical Multifactor Coupling and Hydraulic Fracture Propagation Evaluation Model for Fracability Based on a Multiplicative Synthesis Method

Accurate evaluation of fracability in unconventional reservoirs is essential for optimizing fracturing intervals and assessing productivity. Traditional fracability models, typically based on linear weighted and geometric average methods, suffer from subjective biases and neglect the correlation of factors. It is difficult to characterize and quantify the fracture network modification and the actual fracturing effect. To address these limitations, a new comprehensive fracability evaluation model was proposed based on multiplicative synthesis, incorporating the coupling effects of rock mineral properties, mechanical characteristics, in situ stress, and natural structural planes. The novelty lies in avoiding the weight calculations of factors, ensuring easy distinction of evaluation grades, continuous and monotonous results, and significant practicality and superiority. Brittle mineral content, elastic modulus, and Poisson's ratio were utilized to characterize the mineral and mechanical brittleness. The degree of natural fracture development was quantified through fractal dimensions and grid coverage methods. True triaxial hydraulic fracturing experiments and finite-element-based numerical simulations were used to analyze the spatial morphology and stimulated reservoir volume of hydraulic fractures influenced by fracability, and the model accuracy was validated with on-site microseismic and electromagnetic monitoring. The method was applied to the continuous fracability grading evaluation and sweet-spot prediction of deep sandstone reservoirs in the Junggar Basin. In addition, a three-dimensional block model of lateral heterogeneous fracability based on the distance power inverse method was established, enabling precise identification of geological sweet spots and optimal perforation intervals. The findings provide critical insights for accurately evaluating unconventional reservoir fracability and optimizing fracturing designs.