Abstract
Multi-stage hydraulic fracturing (HF) is an effective stimulation technique for enhanced hydrocarbon recovery in tight sand reservoirs, and the fracture initiation pressure (FIP) is a key parameter for evaluating the difficulty of HF. Recent studies have shown that the stress shadow caused by pre-existing hydraulic fractures considerably affects fracture initiation. However, few studies have fully analyzed the FIP considering the stress shadow effect. Additionally, factors affecting stress shadow have not been quantitatively evaluated. Therefore, the aim of this study was to establish an efficient model for investigating the impact of stress shadow on the FIP. We developed a comprehensive stress distribution model for the perforated horizontal wellbore and analyzed the fracture initiation mechanism. Subsequently, we applied the displacement discontinuity method (DDM) to simulate the stress shadow generated by hydraulic fractures. Next, we validated the DDM against the analytical solution and analyzed the variation of the FIP along the horizontal wellbore considering the effect of stress shadow. Finally, we evaluated the key parameters affecting the FIP using a well-trained back-propagation artificial neural network. The results showed that stress shadow increased the magnitude of the FIP during the multi-stage HF operation. The fracture net pressure and the offset distance from the pre-existing hydraulic fracture are crucial parameters that affect the FIP. This study provides an efficient approach for calculating the FIP for multi-stage HF and can aid engineers in developing tight sand reservoirs.
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