Oil & Gas Geology ›› 2018, Vol. 39 ›› Issue (4): 759-765.doi: 10.11743/ogg20180413

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Identification of igneous reservoir lithology based on empirical mode decomposition and energy entropy classification: A case study of Carboniferous igneous reservoir in Chunfeng oilfield

Han Yujiao1, Yuan Chao1, Fan Yiren2, Ge Xinmin2, Fan Zhuoying3, Yang Wenchao4   

  1. 1. Department of Well Logging and Remote Sensing Technology, PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100080, China;
    2. School of Geosciences, China University of Petroleum(East China), Qingdao, Shandong 266580, China;
    3. College of Geosciences, China University of Petroleum(Beijing), Beijing 102249, China;
    4. Shengli Well Logging Co. Ltd., SINOPEC, Dongying, Shandong 257096, China
  • Received:2017-08-29 Revised:2018-06-25 Online:2018-08-28 Published:2018-07-23

Abstract: Igneous reservoirs are characterized by diversity of eruption patterns and lithology geneses,and variation in mineralogy assemblage.It is really difficult to identify lithology in details,which in turn will greatly hinder the correct calculation of reservoir parameters,as well as subsequent hydrocarbon development strategies.Therefore,the study took a case study of the carboniferous igneous reservoirs in Chunfeng oilfield,Junggar Basin.The lithological categories of the reservoirs are basalt,basaltic andesite,andesite,tuff and volcanic breccias.A combination of core,thin section and other tests' data were used in the study.Then the logging response characteristics of different lithologies were clarified.The tuff and volcanic breccia were identified with the cross plot technique and "progressive stripping" concept.For the hard-to-identify volcanic lava,we used the empirical mode decomposition algorithm to convert the conventional logging data into multiple band sets of intrinsic mode functions,and attained the energy entropy of empirical mode function of various logging parameters for lavas.Then the precise identification of igneous lithologies was realized by using the discriminant algorithm.In applying the method to the block, we found that the overall matching rate of the proposed method is 93.7%, which has greatly improved the accuracy of lithological identification.

Key words: empirical mode decomposition, energy entropy, lithology identification, igneous rock, Chunfeng oilfield

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