现代电子技术Issue(22)：17-19,23,4.
ARMA建模在神经网络卡钻预测方法中的应用研究
Application of ARMA modeling in neural network prediction method for sticking of drilling rig
摘要
Abstract
In order to accurately predict the accident of drilling rig sticking,a neural network prediction method based on time series for drilling rig sticking was used to combine the time series ARMA modeling with neural network non-linear mode-ling. First of all,the drilling parameters closely related with sticking accident is selected as input item of a neural network to train the neural network by field data,the strongly nonlinearity and adaptive learning ability of the neural network are used to es-tablish the prediction models of sticking accident,and then through the mining function of the time series to the historical data, the implicit rule of each parameter closely related with the sticking accident in the actual drilling process is revealed time-series ARMA model establish and the predicted values of relative parameters at sticking point are deduced. Finally,the predicted va-lues are put into the neural network model for testing training,so as to achieve the effect of predicting the sticking accident. The predictive capability and generalization ability of the method for drilling rig sticking were confirmed with yan’an area actual field data.关键词
卡钻/预测/时间序列/ARMA建模/BP神经网络Key words
sticking of drilling rig/prediction/time series/ARMA modeling/BP neural network分类
信息技术与安全科学引用本文复制引用
刘光星,陶宇龙,朱丹..ARMA建模在神经网络卡钻预测方法中的应用研究[J].现代电子技术,2013,(22):17-19,23,4.基金项目
陕西省自然科学基础研究计划油气田钻井卡钻的预测与诊断技术研究 （）
