An Auxiliary Monitoring Method for Well Killing Based on Statistical Data

作     者：Shuang Liang Fangyu Luo Huihui Yu Jian Gao Xiaolin Shu 

作者机构：CNPC Research Institute of Safety&Environment TechnologyBeijingChina Environmental Protection and Technical Supervision Research InstitutePetroChina Southwest Oil&Gas Field CompanyShanghaiChina West East Pipeline Company of PipeChinaShanghaiChina 

出 版 物：《Fluid Dynamics & Materials Processing》 (流体力学与材料加工（英文）)

年 卷 期：2023年第19卷第8期

页      面：2109-2118页

核心收录：

学科分类：08[工学] 0837[工学-安全科学与工程] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 081202[工学-计算机软件与理论] 

基　　金：supported by research on key equipment and supporting technology for Onshore Well Control Emergency CNPC(2021ZZ03-2). 

主　　题：Well-killing Big Data monitoring 

摘      要：In the present study,a large set of data related to well killing is considered.Through a complete exploration of the whole process leading to well-killing,various factors affecting such a process are screened and sorted,and a correlation model is built accordingly in order to introduce an auxiliary method for well-killing monitoring based on statistical information.The available data show obvious differences due to the diverse control parameters related to different well-killing methods.Nevertheless,it is shown that a precise three-fold relationship exists between the reservoir parameters,the elapsed time and the effectiveness of the considered well-killing strategy.The proposed monitoring auxiliary method is intended to support risk assessment and optimization in the context of typical well-killing applications.