Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Journal of Southwest Petroleum University》 2007-03
Add to Favorite Get Latest Update

PREDICTION OF RESERVOIR PRODUCTIVITY BY SUPPORT VECTOR MACHINE

ZHANG Feng(China University of Petroleum, Dongying Shandong 257061,China),ZHANG-Xing,ZHANG Le,et al  
Support vector machine method is based on the principle of structural risk minimization, and suitable for small samples, nonlinearity and local minimun by Kernel function processing technology, it overcomes the limitation of conventional statistical method, avoids dimentionality disaster, compromises the commonality and popurization of the model on the basis of limited samples and solves the problems of learning performance and popularization effectively with higher prediction accuracy. In practical production, there are a lots factors influncing reservoir productivity, and the factors impact each other. In view of comprehensively considering formation factors, well logging productivity prediction parameters are sorted out, the productivity is predicted by support vector machine, the prediction result is correlated and compareed with the result from multi-regression and BP neural network processing. Practice suggests that the support vector machine is better than the latter two methods and is worthyto be popularized.
【Fund】: 国家863课题资助(2006AA09A209)。
【CateGory Index】: P618.13
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
【Citations】
Chinese Journal Full-text Database 8 Hits
1 Xu Yanqing; Li Zhoubo; Lu Jing'an(Changchun University of Science and Technology, Changchun 130026);STUDY ON THE PREDICTION METHODS OF OIL-GASRESERVOIR PERFORMANCE WITH WELL-LOGGING[J];JOURNAL OF CHANGCHUN UNIVERSITY OF SCIENCE AND TECHNOLOGY;1999-02
2 YANG Changbao, NIE Lanshi, SUN Pengyuan(College of GeoExploration Science and Technology, Jilin University, Changchun130026,China);A STUDY OF USING IMPROVED FUZZY NEUAL NETWORK TO FORECAST RESERVOIR PRODUCTIVITY[J];Journal of Changchun University of Science and Technology;2003-01
3 Gu Guoxing Din Jing (Jiangshu Petroleum Exploration Bureau, China);A Method for Forecasing the Productivity of a Oil-Producing Pay by Using Logging Interpretation Data[J];Journal of Jianghan Petroleum Institute;1993-01
4 ZHANG Xuegong (Dept.of Automation,Tsinghua University,Beijing 100084) (State Key Laboratory of Intelligent Technology and Systems of China);INTRODUCTION TO STATISTICAL LEARNING THEORY AND SUPPORT VECTOR MACHINES[J];;2000-01
5 WANG Jinglei1, WU Jingshe1, SUN Jingsheng1,QI Xuebin1(1.Farmland Irrigation Research Institute,MWR,Xinxiang,Henan453003,China);Application of support vector machine method in prediction of groundwater level[J];Journal of Hydraulic Engineering;2003-05
6 ACTA 2000,21(5):58~61. MAO Zhi qiang, et al.(Petroleum University, Beijing 102249,China);METHOD AND MODELS FOR PRODUCTIVITY PREDICTION OF HYDROCARBON RESERVOIRS[J];ACTA PETROLEI SINICA;2000-05
7 ZHANG Xing1, LI Zhao-min1, SUN Ren-yuan1, SU Cheng-xiang2(1.Institute of Petroleum Engineering, China University of Petroleum, Dongying, Shandong 257061, China; 2.Cainan Field Operation District, Xinjiang Oilfield Company, PetroChina, Fukang, Xinjiang 831500, China);The Experimental Study on Rheological Behavior of Polymer[J];Xinjiang Petroleum Geology;2006-02
8 ZHANG Feng1,QIN Ji-shun2,ZHANG Xing1,SUN Ren-yuan1(1.College of Petroleum Engineering,China University of Petroleum,Dongying,Shandong 257061,China;2.Research Institute of Petroleum Exploration and Development,PetroChina,Beijing 100083,China);A Study on Rheology Property of Emulsion of Crude Oil[J];Xinjiang Petroleum Geology;2006-05
【Co-references】
Chinese Journal Full-text Database 6 Hits
1 by Feng Qihong(University of Petroleum);Chen Yaowu,Guo Jinglai;STUDY OF STATISTICAL METHOD FOR RESULT PREDICTION OF PROFILE CONTROL[J];Oil Drilling & Production Technology;2003-06
2 LI Dong~1,WANG Hong-li~2,DU Zhong-xiao~3,WANG Chang-jiang~2,CHEN Bing-lin~4(1.School of Management,Tianjin University,Tianjin 300072,China;2.School of Mechanical Engineering,Tianjin University,Tianjin 300072,China;3.Tianjin Construction Administration Committee,Tianjin 300051,China;4.Tianjin Water Works Company Ltd,Tianjin 300040,China);SVM-Based Prediction of City Municipal and Domestic Water Consumption[J];Journal of Tianjin University(Social Sciences);2006-01
3 Yue Youxi and Yuan Quanshe (Institute of Earth Resources and Information, China University of Petroleum).;APPLICATION OF SVM METHOD TO PREDICTING RESERVOIR PARAMETER[J];Natural Gas Industry;2005-12
4 MEI Jian-xin, DUAN Shan, PAN Ji-bin, QIN Qian-qing (National Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,Wuhan 430079, Hubei, China);The Application of Support Vector Machines in Recognition of Small Sample[J];Wuhan University Journal(Natural Science Edition);2002-06
5 Li Zhaomin,Zhang Xing et al.Zhai Liang,Geological Scientific Research Institute,Shengli Oilfield Company of SINOPEC,Dongying City,Shandong Province,257015,China;Optimization of polymer injection parameters for channeling prevention based on the support vector machine[J];Petroleum Geology and Recovery Efficiency;2007-04
6 Chen Yongyi Yu Xiaoding Gao Xuehao (Training Center of China Meteorological Administration, Beijing 100081) Feng Hanzhong (Chengdu Meteorological Center, Chengdu 610071);A NEW METHOD FOR NON-LINEAR CLASSIFY AND NON-LINEAR REGRESSION Ⅰ: INTRODUCTION TO SUPPORT VECTOR MACHINE[J];Quarterly Journal of Applied Meteorology;2004-03
【Secondary Citations】
Chinese Journal Full-text Database 10 Hits
1 Xu Yanqing; Li Zhoubo; Lu Jing'an(Changchun University of Science and Technology, Changchun 130026);STUDY ON THE PREDICTION METHODS OF OIL-GASRESERVOIR PERFORMANCE WITH WELL-LOGGING[J];JOURNAL OF CHANGCHUN UNIVERSITY OF SCIENCE AND TECHNOLOGY;1999-02
2 Mao Zhiqiang.;A Relative Permeability Model for Productivity Forecast and Fluid Identification in Reservoir Evaluation.[J];WELL LOGGING TECHNOLOGY;1998-05
3 Ding Zhixiong et al.(42);Establishment and Application of Artificial Neural Network for Groundwater Resource System[J];GEOTICHNICAL INVESTIGATION AND SURVEYING;1999-02
4 TIAN Sheng Feng and HUANG Hou Kuan(Department of Computer Science and Technology, Northern Jiaotong University, Beijing 100044);DATABASE LEARNING ALGORITHMS BASED ON SUPPORT VECTOR MACHINE[J];JOURNAL OF COMPUTER RESEARCH AND DEVELOPMENT;2000-01
5 ZHANG Xuegong (Dept.of Automation,Tsinghua University,Beijing 100084) (State Key Laboratory of Intelligent Technology and Systems of China);INTRODUCTION TO STATISTICAL LEARNING THEORY AND SUPPORT VECTOR MACHINES[J];;2000-01
6 MA Yunqian, ZHANG Xuegong (Department of Automation, Tsinghua University, State Key Laboratory of Intelligent Technology and System, Beijing 100084, China);Application of support vector machines function regression in fractal interpolation[J];JOURNAL OF TSINGHUA UNIVERSITY(SCIENCE AND TECHNOLOGY);2000-03
7 Wang Xinhai (Scientific Research Institute of Petroleum Exploration and Development,Beijing);DETERMINATION OF THE MAIN PARAMETERS IN THE NUMERICAL SIMULATION OF POLYMER FLOODING[J];Petroleum Expoloration and Development;1990-03
8 LI Kai,GUO Zi xue(Hebei University,Baoding Hebei 071002,China);A Function Simulation Based on Support Vector Machine[J];Microcomputer Development;2001-03
9 YAN Hui , ZHANG Xue gong , LI Yan da (Dept. of Autonmation State Key Laboratory of Intelligent Technology and Systems of China, Tsinghua University, Beijing100084, China);SUPPORT VECTOR MACHINE METHODS IN PATTERN RECOGNITION OF SEDIMENTARY FACIES[J];COMPUTING TECHNIQUES FOR GIOPHYSICAL AND GEOCHENICAL EXPLORATION;2000-02
10 WU Ming, SHEN Long she, YANG Hui da (Fushun Petroleum Institute, Fushun 113001, Liaoning, China);Experimental Study on Rheological Property of Watered Oil[J];Journal of Xi'an Petroleum Institute;2002-01
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved