摘要
微地震是评价致密砂岩裂缝性油气藏缝网压裂裂缝形态及几何尺寸的有效方法和手段,但其适用条件受限,且成本较高。为此,需要一种快速的、经济适用的方法来评价缝网压裂裂缝复杂程度。基于压裂泵停泵后的压降数据,利用视均质型、线性裂缝型、复杂裂缝型致密砂岩裂缝性储层渗流方程分析储层渗流模式,利用G函数分析储层裂缝形态,从而综合评价缝网压裂裂缝复杂程度,形成一种快速评价缝网压裂裂缝复杂程度的方法。微地震测试成果证明了该方法的可靠性。研究成果可为致密砂岩裂缝性气藏缝网压裂效果评估及产能预测提供技术支持。
Microseism is an effective method and means to evaluate the fracture morphology and geometry formed by fracture network fracturing in fractured tight sandstone oil and gas reservoirs,but constrained by its applicability conditions and high cost.Therefore,a rapid,economical and applicable method is needed to evaluate the fracture complexity in fracture network fracturing.Based on the pressure drop data after fracture pump shutdown,the reservoir seepage model was analyzed by seepage equation which was established for tight sandstone fractured reservoirs with apparent homogeneity,linear fracture and complex fracture,and the reservoir fracture morphology was analyzed with G function,so as to comprehensively evaluate the fracture complexity in the network fracturing and develop a method to quickly evaluate the fracture complexity of the network fracturing.The microseismic test results proved that this method was reliable.The study results can technically provide support for the network fracturing effect evaluation and productivity prediction of tight sandstone fractured gas reservoirs.
作者
肖阳
刘守昱
何永志
李志刚
王家豪
杨金元
马中慧
Xiao Yang;Liu Shouyu;He Yongzhi;Li Zhigang;Wang Jiahao;Yang Jinyuan;Ma Zhonghui(Chengdu University of Technology,Chengdu,Sichuan 610059,China;Sunshine Energy Technology Co.,Ltd.of Chengdu University of Technology,Chengdu,Sichuan 610059,China;PetroChina Huabei Oilfield Company,Xinji,Hebei 052360,China)
出处
《特种油气藏》
CAS
CSCD
北大核心
2022年第2期157-163,共7页
Special Oil & Gas Reservoirs
基金
国家自然科学基金青年科学基金“多尺度多场应力耦合致密砂岩体积改造裂缝评价模型研究”(51504042)
国家科技重大专项“鄂南致密低渗油藏水力压裂裂缝起裂及扩展规律”(2016ZX05048-001-04-LH)
四川省教育厅基金重点项目“自流注水关键节点仿真及流动耦合计算模型研究”(18ZA0063)。
关键词
致密砂岩
裂缝性气藏
缝网压裂
缝网复杂程度
停泵压降数据
G函数
tight sandstone
fractured gas reservoir
fracture network fracturing
fracture network complexity
pump-off pressure drop data
G function
