Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)

Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)

Provided is a method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science). The method of oil well classification and reservoir zoning based on SPSS can solve the technical problems that the traditional correlation research methods are time-consuming...

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Hauptverfasser: LIU ZHENPING, FENG LIJUAN, ZHU YATING, ZHOU YUHUI, ZOU WEI, ZHANG QIANG, CHENG HONGJIE, LENG RUNXI, QI LISHA, WANG XIAOGUANG, QIAN CHUANCHUAN, CHEN YUKUN, JIANG ZHIBIN, ZHANG JIGANG, SU HAIBIN
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:Provided is a method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science). The method of oil well classification and reservoir zoning based on SPSS can solve the technical problems that the traditional correlation research methods are time-consuming and laborious, and the rationality of the subarea is not verified. The method of oil well classification and reservoir zoning comprises the following steps: step one, principal component analysis is carried out; the principal component analysis is to use the Bartlett sphericity test or KMO method to determine whether the factors are suitable for factor analysis; step two, the principal component factor is extracted and determined by using SPSS software; step three: the oil well is classified according to the determined principal component factor; step four: the principal component factor weights are excavated by using SPSS(statistic package for social science) software, and a subarea coefficient model is establish