特种油气藏2017，Vol.24Issue(5)：170-174,5.DOI:10.3969/j.issn.1006-6535.2017.05.032
裂缝性油藏压裂井产能敏感因素评价方法研究
Techniques for Assessment of Productivity Sensitive Factors in Wells with fracturing Operations in Fractured Reservoirs
摘要
Abstract
An innovative technique for productivity assessment in fracturing wells has been developed based on BP artificial neural network and with cumulative productivity as the target. With the fractured tight sandstone reservoirs in Block X as examples,models for assessments over productivity sensitive factors in oil producers with fracturing operations have been established. By studying the training errors induced by microscopic interferences,sensitivities of productivity to porosity,permeability,fractures,operation parameters and other factors have been analyzed. In addition,necessary measures to promote productivity have been proposed. Research results show productivities of oil producers in Block X are more sensitive to parameters of fracturing operations. Difficulties in deployment of proppa-nts and low vertical permeability of resulting fractures are the two key restricting factors for performances of fractu-ring operations. On the other hand,horizontal wells with prolonged horizontal intervals may effectively promote com-prehensive development of reservoirs. The innovative assessment technique may provide necessary theoretical foun-dation to optimize operation parameter of fracturing operations and to enhance productivity of oil producers.关键词
裂缝性油藏/压裂/产能评价/神经网络/敏感因素Key words
fractured reservoir/fracturing/productivity assessment/neural network/sensitive factor分类
能源科技引用本文复制引用
刘欣佳,温庆志,张遂安,宋丽娜,Muhammad Haseeb..裂缝性油藏压裂井产能敏感因素评价方法研究[J].特种油气藏,2017,24(5):170-174,5.基金项目
国家"十三五"科技重大专项"临兴-神府地区煤系地层煤层气、致密气、页岩气合采示范工程"(2016ZX05066) （2016ZX05066）
