基于多录井参数特征同步的溢流事故监测研究  

Study on Overflow Accident Monitoring Based on Synchronous Features of Multiple Well Logging Parameters

作　　者：陈青 黄志强[1,2] 孔祥伟[1,2] 何弦桀 徐洲 安果涛 CHEN Qing;HUANG Zhiqiang;KONG Xiangwei;HE Xianjie;XU Zhou;AN Guotao(Petroleum Engineering College,Yangtze University,Wuhan 430100,P.R.China;National Engineering Research Center for Oil&Gas Drilling and Completion Technology,Yangtze University,Wuhan 430100,P.R.China;Research Institute of Drilling and Production Engineering Technology,CNPC Chuanqing Drilling Engineering Co.,Ltd.,Deyang,Sichuan 618399,P.R.China)

机构地区：[1]长江大学石油工程学院,武汉430100 [2]长江大学油气钻完井技术国家工程研究中心,武汉430100 [3]中国石油集团川庆钻探工程有限公司钻采工程技术研究院,四川德阳618399

出　　处：《应用数学和力学》2025年第2期241-253,共13页Applied Mathematics and Mechanics

基　　金：国家自然科学基金(51904261)。

摘　　要：依据录井参数进行溢流事故的判断十分依赖坐岗人员的经验,且现场采集的综合录井参数信噪严重,参数变化特征不明显,溢流监测准确率低.通过低通滤波处理和局部加权线性回归,去除现场综合录井参数曲线的高频信号和低频信噪,经归一化处理,得到了多参数同步的溢流识别方法,并结合GCN图形匹配和BRNN双向传递的特点,建立了GCN-BRNN相融合的模型,提高了溢流事故监测的准确率.结果表明,通过局部加权线性回归处理后能够使曲线变化特征更加明显,且归一化后的多参数同步监测比单一参数监测的准确率更高;以川西某井的综合录井数据为例进行溢流识别测试,与原先模型相比,结合后的模型溢流识别准确率更高,可达到85%;储层特征会影响录井参数的采集精度,储层分布结构越均匀、性质越稳定,溢流监测的准确率越高.经JT井现场应用,溢流事故识别准确率≥89%,实际溢流风险与模型识别结果一致.该方法能有效处理多源信息间的冲突,提高溢流监测的识别精度,对现场结合录井参数的溢流事故监测方法具有指导意义.Judging overflow accidents based on well logging parameters relies heavily on the experience of on-duty personnel,and the comprehensive well logging parameters collected in-situ have severe noises and unclear parameter change characteristics,resulting in low accuracy of overflow monitoring.A multi-parameter synchronous overflow identification method was obtained through low-pass filtering and locally weighted linear regression to remove the high-frequency signals and low-frequency noises of the in-situ comprehensive well logging parameter curves,and after normalization processing.Combined with the characteristics of the GCN graph matching and the BRNN bidirectional transmission,the GCN-BRNN fusion model was established to improve the accuracy of overflow accident monitoring.The results show that,the local weighted linear regression can make the curve change characteristics more obvious,and the accuracy of the multi-parameter synchronous monitoring after normalization is higher than that of the single-parameter monitoring.With the comprehensive well logging data of a well in western Sichuan as an example,compared with the original model,the combined model has a higher accuracy reaching 85%in overflow identification.The characteristics of the reservoir affect the accuracy of logging parameter collection;the more uniform the reservoir distribution structure is and the more stable the properties are,the higher the accuracy of overflow monitoring will be.After in-situ application in the JT well,the identification accuracy of overflow accidents is≥89%,and the actual overflow risk is consistent with the model identification results.This method can effectively handle conflicts between multiple sources of information,improve the accuracy of overflow monitoring,and provide guidance for in-situ overflow accident monitoring methods combined with well logging parameters.

关 键 词：钻井溢流监测 参数特征 滤波去噪 局部加权线性回归 神经网络 

分 类 号：O368[理学—流体力学] O29[理学—力学]