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Application of the artificial neural network to multivariate anomaly recognition in geochemical exploration for hydrocarbons

Application of the artificial neural network to multivariate...

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中国科学院地质与地球物理研究所2003学术年会

作者： Liuping Zhang~(1,2) & Guoping Bai~(1,2) 1 Basin(?) Reservoir Research Center,University of Petroleum,Changping,Beijing 102249,P.R.China 2 Key Laboratory for hydrocarbon Accumulation Mechanism of Chinese Ministry of Education,University of Petroleum, Beijing 102249,P.R.China

Traditional methods of multivariate statistical analyses,used to recognize anomalous hydrocarbon signatures in petroleum exploration,have at least four shortcomings:(1) it is difficult to isolate anomalies where the data are not normally distributed;(2) it is difficult to separate distinct anomaly populations corresponding to distinct formation mechanisms while separating anomalies from background;(3) it is not fitting to present illustrations of multivariate anomalies on contour maps;and (4) it is not suitable for preparation for multivariate pattern *** present serious obstacles to the application of exploration geochemistry in hydrocarbon *** study demonstrates that the Back Propagation Artificial Neural Network(BP-ANN) with logic multiplication cluster analysis(a new cluster analysis proposed in this paper) overcomes the difficulties exhibited by traditional multivariate *** logic multiplication cluster analvsis was designed to produce a training set for the *** approach was established on the basis of geochemical characteristics and origin of the various populations in geochemical data,such as background,micro-seepage anomalies and seepage *** topology of the BP-ANN was optimized using the outputs of the BP-ANN and the correct *** order to illustrate the multivariate anomalies recognized using BP-ANN on contour maps,we designed the expression functions for BP-ANN application in this *** traditional methods of anomaly recognition,acid-extractable hydrocarbons in soils have not proven to be efficient indicators for hvdrocarbon potential in East Anan Sag,Inner ***,the BP-ANN has indicated that these indicators are efficient and that areas of East Anan Sag have potential reserves of petroleum.

关键词： multivariate anomalies neural network cluster analysis direct hydrocarbon indicators

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