Experimental and Simulation Investigation on Ball-Sealer Transport and Diversion Performance Aided by Machine Learning Method

作者：Hai Qu, Ying Liu, Chengying Li, Zhijun Zeng, Xu Liu, Zhelun Li · 发表于：SPE Journal · 年份：2023 · DOI：10.2118/218010-pa · 被引用次数：21 · 研究领域：Hydraulic Fracturing and Reservoir Analysis、Drilling and Well Engineering、Oil and Gas Production Techniques

Summary Ball-sealer diversion has been proven to be an effective and economical way to increase fractures and fracturing volume in multistage hydraulic fracturing and matrix acidizing treatments. However, designing and implementing a successful ball-sealer diversion treatment is still challenging. Typically, operators rely on empirical data to determine diversion parameters and need an understanding of accurate ball transport and diversion behaviors. A model for optimizing operating parameters, including fluid and ball properties, and predicting the diversion performance of ball sealers before treatment is needed for designing the fracturing process. In this work, we systematically investigated ball-sealer diversion using experimental and numerical methods. The resolved model of computational fluid dynamics (CFD) and discrete element method (DEM) is first developed to simulate the transport of a large ball in a horizontal wellbore with side holes. The experimental results validated the numerical model. The effects of the ball position in the pipe, flow ratio of the hole to pipe, injection flow rate, and ball density on the diversion performance were studied under field parameters. The results show that the ball sealer easily misses the heel-side perforation due to the inertial effect and travels to the toe side due to the large inertia and turbulent flow. The ball position and flow rate ratio are crucial for the diversion performance. There is a threshold value of the ball po...