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数据挖掘技术在钻井液优化配方设计中应用
引用本文:张勇斌,梁荣华,罗健生,马玉书.数据挖掘技术在钻井液优化配方设计中应用[J].钻井液与完井液,2002,19(1):36-37,40.
作者姓名:张勇斌  梁荣华  罗健生  马玉书
作者单位:1. 石油大学,北京
2. 中国海洋石油技术服务公司技术发展中心
摘    要:利用数据挖掘技术建立了一套快速预测钻井液优化配方的新方法,验证结果表明,应用该方法预测出的钻井液优化配方与实验室优选出的钻井液配方是一致的,该套数据挖掘工具能快速给出符合要求的钻井液配方,指导用户有针对性地进行配方实验,缩短实验时间,降低实验成本,同时极大地提高实验成功率,其基本步骤为:(1)数据准备,从历史数据中选取数据项和行记录作为进行挖掘的数据集,其中包含钻井液性能指标和配方;(2)根据所选数据特征进行模型训练前的处理;(3)数据集训练,先依据钻井液常规性能进行聚类分析挖掘,再对挖掘结果进行预测分析挖掘;(4)利用数据集中没有参与训练的部分数据集对挖掘进行验证;(5)根据给定的钻井液性能要求,挖掘工具给出相应的钻井液配方。

关 键 词:钻井液  配方  设计  数据挖掘  神经网络  石油钻井

The application of data-mining technology in the optimization of drilling fluid program
ZHANG Yong-bin,LIANG Rong-hua,LUO Jian-sheng,and MA Yu-shu Petroleum University,Changping,Beijing.The application of data-mining technology in the optimization of drilling fluid program[J].Drilling Fluid & Completion Fluid,2002,19(1):36-37,40.
Authors:ZHANG Yong-bin  LIANG Rong-hua  LUO Jian-sheng  and MA Yu-shu Petroleum University  Changping  Beijing
Abstract:A new method for fast predicting of drilling fluid optimization program is established based on the data-mining technology. Tests show that the drilling fluid formulation predicted by this method coincides with that of by laboratory selection. The data-mining tool can provide the required formulation rapidly, and direct the formulation experiment, thus shorten the experiment time and cut down the cost. This method is consisted of the following processes, 1. data preparation, including drilling fluid performance indexes and formulations; 2. pre-processing before model training based on the selected data; 3. data training; 4. verifying of mining using the untrained data; 5. present the suitable drilling fluid formulation, according to the required drilling fluid properties.
Keywords:drilling fluid  drilling fluid formulation  drilling fluid design  data mining  artificial neural network
本文献已被 CNKI 维普 万方数据 等数据库收录!
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