论文详情
适用于高温高盐油藏的RX-颗粒堵剂注入参数优化
断块油气田
2019年 26卷 第06期
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Title
Injection parameters optimization of water-plugging agent RX-particle applicable to high temperature and high salinity reservoir
单位
长江大学石油工程学院,湖北 武汉 430100
Organization
School of Petroleum Engineering, Yangtze University, Wuhan 430100, China
摘要
为解决国内某油田生产过程中由于地层非均质性而引发的油井暴性水淹、产量递减严重等问题,选择了一种油藏适应性较强的新型深部堵剂RX-颗粒,并借助玻璃刻蚀模型微观驱替实验以及室内岩心物理模拟驱替实验,完成了RX-颗粒逆向卡封机理研究以及注入参数优化。研究表明,RX-颗粒可在地层条件下,通过粘连 ̄架桥或粘连—堆积—挤压—变形—再运移等重复方式,逐步深入高渗地层,并形成暂堵带,迫使后续水体转向中、低渗地层,从而降低油井含水率,提高油井产量。此外,室内还优化了RX-颗粒堵剂的最佳注入参数,主要包括最佳转注时机、最佳粒径范围(0.5~1.0 mm)、最佳强度(老化24 h)、最佳固液质量比(8%)及最佳携带液GA质量分数(0.3%),对后续堵水作业具有一定的指导意义。
Abstract
To solve the serious production declining for formation heterogeneity of a certain domestic field in China, RX-particle with strong reservoir adaptability was chosen for deep water-plugging. According to the field requirements, the plugging water technology optimization design was completed in laboratory with the microscopic displacement experiment based on glass etching model and the simulation displacement experiment, including the research of particle plugging water mechanism and the optimization of injection parameters. The results show that RX-particle can gradually penetrate into the high-permeability strata in the repeated manners of "adhesion-bridging" or "adhesion-stacking-extrusion-deformation-retransport" under formation conditions to form temporary plugging zones and force the water to turn to the middle and low permeability layers, resulting in reducing water-cut and increasing production. Moreover, the injection parameters of RX-particle plugging agent were optimized, including the optimum injection timing, optimum particle size range(0.5-1.0 mm), optimum strength(aging for 24 h), optimum particle concentration (solid-liquid mass ratio of 8%) and optimum concentration of carrier fluid GA (mass percent of 0.3%), which has a certain guiding significance for the subsequent water plugging operation.
关键词:
深部堵水剂;
堵水机理;
注入参数;
优化;
Keywords:
deep water plugging;
plugging water mechanism;
injection parameters;
optimization;
DOI
10.6056/dkyqt201906023