基于BP神经网络的调剖效果预测模型分析  

Prediction model of conformance control effect based on BP neural network

作　　者：刘宁[1] 刘士梦 李明[2] 

机构地区：[1]中国石化河南油田分公司勘探开发研究院,河南郑州450000 [2]中国石化河南石油工程有限公司钻井公司,河南南阳473132

出　　处：《复杂油气藏》2014年第2期51-53,共3页Complex Hydrocarbon Reservoirs

摘　　要：产油量预测是调剖方案实施以后效果预测或评价的关键,基于BP神经网络理论,通过分析影响调剖效果的因素,利用Matlab神经网络工具箱函数,建立了调剖神经网络预测模型,经过模型预测效果分析及实际运用,认为利用BP神经网络预测产油量与实际值较为吻合,误差相对较小,可靠性高,可运用此模型预测调剖产油量。The oil production prediction is a key to prediction or evaluation of conformance control effect after the scheme implementation. Based on the theory of BP neural network, by analyzing the influencing factors of conformance con- trol effect, the neural network prediction model for conformance control was established by employing the toolbox functions in the Matlab neural network. Through the analysis of the model forecast effect and practical application,it was considered that the oil production predicted by the BP neural network was consistent with the actual one, which had smaller relative error and high reliable. The model can be used to predict the conformance control production.

关 键 词：油田开发 调剖 BP神经网络 模型 预测 

分 类 号：TE323[石油与天然气工程—油气田开发工程]