Abstract: It is critical for effective implementation of stimulated reservoir volume fracturing in unconventional oil and gas reservoirs to accurately characterize the effective stimulated reservoir volume (ESRV) and clarify the main controlling factors affecting the stimulated volume. However, there is still no effective methods to accurately characterize the effective stimulated reservoir volume, and the analysis on main controlling factors is too simple to meet the demand of practical engineering. In response to this problem, an ESRV characterization method based on unstructured network was proposed to accurately characterize the fracture network system in combination with actual production, followed by the analysis of main controlling factors that affects the stimulated volume by random forests algorithm. The evaluation method is more objective, meeting the field demand. The results of the field application showed that the stimulated volume calculated by the new method was more accurate than that estimated by the traditional method, with an average difference of 16%; the fracturing fracture network was controlled by multiple variables; the influence of fracture construction parameter accounted for 53.8% and that of geological and rock mechanics parameters accounted for 46.2% among the primary main controlling factors affecting the stimulated volume. This method provides a reference for the optimal design of multi-stage fracturing of horizontal wells and the prediction of post-fracturing production.

Key words: SRV fracturing, unconventional oil and gas, fracture network stimulation, primary controlling factors, discrete fractures, numerical simulation