摘要
东胜气田前期压裂效果分析方法大多基于单因素定性分析,分析结果相对片面,没有定量化,同时对于影响压裂效果的主控因素尚不明确,不利于压裂设计的针对性优化。结合储层分类评价、有利沉积微相及储层厚度评价优势储集体分布,建立了锦58井区气藏综合分类评价标准。在此基础上,开展地质参数和工程参数影响因素分析,明确影响压裂效果的主控因素,建立了一套适合于锦58井区的压裂效果预测模型。利用该模型开展压裂施工参数优化研究,根据压裂施工参数优化结果,选取2口水平井进行了现场试验,预测无阻流量与实际无阻流量整体符合率为92.2%,无阻流量较邻井平均提高28.4%,取得了较好的增产效果。
Previous analyzing methods of the fracturing effect in Dongsheng Gas Field are mostly based on the single-factor qualitative analysis,the analyzed results are relatively one-sided and not quantitative;At the same time,the dominant controlling factors affecting the fracturing effect are not clear,this is not conducive to the targeted optimization of the fracturing design.Combining the reservoir classification&evaluation,favorable sedimentary microfacies and preferential reservoir distribution by the reservoir thickness evaluation,the comprehensive classifying and evaluating criteria were established for the gas reservoirs in Block Jin-58.On this basis,the influencing factors of the geological and engineering parameters were analyzed,and the main controlling factors affecting the fracturing effect were identified,a set of the suitable predicting model was established for the fractured effect in Block Jin-58.The optimizing study on of the fracturing operation parameters was carried out by this model,according to the optimized results,two horizontal wells were selected for the field test,the overall coincidence rate between the predicted and actual AOFPs was 92.2%,and the AOFP was increased by 28.4%on average compared with the adjacent wells,much better incremental effects were achieved.
作者
李凌川
刘威
张永春
姚昌宇
LI Lingchuan;LIU Wei;ZHANG Yongchu;YAO Changyu(Petro-Engineering Research Institute of Sinopec North China Oil and Gas Branch,Zhengzhou 450006,China)
出处
《大庆石油地质与开发》
CAS
CSCD
北大核心
2020年第2期48-55,共8页
Petroleum Geology & Oilfield Development in Daqing
基金
国家科技重大专项“低丰度致密低渗油气藏开发关键技术”(2016ZX05048)。
关键词
致密砂岩气藏
水平井
分段压裂
主控因素
BP神经网络
参数优化
tight sandstone gas reservoirs
horizontal well
staged fracturing
dominant/main controlling factor
BP neural network
parameter optimization