基于BP神经网络的井壁坍塌预测  

Prediction of well wall collapse based on the BP neural network

作　　者：栾凯伦 高斐[1,2] 楼一珊[1,2] 黄梦婷 LUAN Kailun;GAO Fei;LOU Yishan;HUANG Mengting(Hubei Provincial Key Laboratory of Oil and Gas Drilling and Production Engineering(Yangtze University),Wuhan 430100,Hubei,China;School of Petroleum Engineering,Yangtze University,Wuhan 430100,Hubei,China)

机构地区：[1]油气钻采工程湖北省重点实验室(长江大学),湖北武汉430100 [2]长江大学石油工程学院,湖北武汉430100

出　　处：《矿产勘查》2025年第2期371-379,共9页Mineral Exploration

基　　金：企业创新发展联合基金集成项目“海相深层油气富集机理与关键工程技术基础研究”(U19B6003)资助。

摘　　要：一定合理的井壁坍塌对于缓和井壁稳定与储层保护之间的矛盾具有重要作用。本文通过分析影响井壁坍塌的主控因素,采用BP神经网络算法实现对井壁坍塌程度的预测。相较于依靠传统经验公式预测井壁坍塌程度,该种方法的预测结果更为科学可靠。结果表明:通过BP神经网络模型对井壁坍塌程度的预测结果与现场实测值绝对误差率为0.37%~14.22%,平均误差率为7.54%。预测精度满足工程精度,证明了BP神经网络预测井壁坍塌程度的可行性。Some reasonable wall collapse to ease the contradiction between wall stability and reservoir protec-tion plays an important role.Through the analysis of the main factors affecting the wall collapse.Using the BP neu-ral network algorithm to predict the degree of wall collapse,than the traditional experience formula to predict the de-gree of wall collapse,the prediction result of this method is more scientific and reliable.The results show that the absolute error rate of the prediction result of BP neural network model is 0.37%-14.22%,and the average error rate is 7.54%.The prediction accuracy satisfies the engineering accuracy,proving the feasibility of the BP neural net-work to predict the degree of well wall collapse.

关 键 词：坍塌预测 神经网络 井壁稳定 绥中区块 

分 类 号：TE22[石油与天然气工程—油气井工程]