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Intelligent identification and real-time warning method of diverse complex events in horizontal well fracturing

查看全文 作　　者：YUAN [1]Bin;ZHAO [1]Mingze;MENG [2]Siwei;ZHANG [1]Wei;ZHENG [1]He 高影响力作者 机构地区：[1]School of Petroleum Engineering,China University of Petroleum(East China),Qingdao 266580,China;[2]PetroChina Research Institute of Petroleum Exploration&Development,Beijing 100083,China高影响力机构 出　　处：《Petroleum Exploration and Development》索引2023年第50卷第6期,共10页高影响力期刊 基　　金：Supported by the National Key R&DPlan Project(2022YFE0129900);National Natural Science Foundation of China(52074338). 摘　　要：The existing approaches for identifying events in horizontal well fracturing are difficult, time-consuming, inaccurate, and incapable of real-time warning. Through improvement of data analysis and deep learning algorithm, together with the analysis on data and information of horizontal well fracturing in shale gas reservoirs, this paper presents a method for intelligent identification and real-time warning of diverse complex events in horizontal well fracturing. An identification model for 'point' events in fracturing is established based on the Att-BiLSTM neural network, along with the broad learning system (BLS) and the BP neural network, and it realizes the intelligent identification of the start/end of fracturing, formation breakdown, instantaneous shut-in, and other events, with an accuracy of over 97%. An identification model for 'phase' events in fracturing is established based on enhanced Unet++ network, and it realizes the intelligent identification of pump ball, pre-acid treatment, temporary plugging fracturing, sand plugging, and other events, with an error of less than 0.002. Moreover, a real-time prediction model for fracturing pressure is built based on the Att-BiLSTM neural network, and it realizes the real-time warning of diverse events in fracturing. The proposed method can provide an intelligent, efficient and accurate identification of events in fracturing to support the decision-making. 关 键 词：horizontal well fracturing fracturing events intelligent identification real-time warning deep learning
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