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作 者:FANG Xinxin ZHU Guotao YANG Yiming LI Fengling FENG Hong
机构地区:[1]China Coal Research Institute,Beijing 100013,China [2]Xi'an Research Institute of China Coal Research Institute,Xi’an 710077,China [3]Oilfield Technology Service Company of Xinjiang Oilfield Company,PetroChina,Karamay,Xinjiang 834000,China
出 处:《Acta Geologica Sinica(English Edition)》2023年第1期176-189,共14页地质学报(英文版)
基 金:funded by the National Key Research and Development Program(Grant No.2018YFC0807804-2)。
摘 要:Reservoir classification is a key link in reservoir evaluation.However,traditional manual means are inefficient,subjective,and classification standards are not uniform.Therefore,taking the Mishrif Formation of the Western Iraq as an example,a new reservoir classification and discrimination method is established by using the K-means clustering method and the Bayesian discrimination method.These methods are applied to non-cored wells to calculate the discrimination accuracy of the reservoir type,and thus the main reasons for low accuracy of reservoir discrimination are clarified.The results show that the discrimination accuracy of reservoir type based on K-means clustering and Bayesian stepwise discrimination is strongly related to the accuracy of the core data.The discrimination accuracy rate of TypeⅠ,TypeⅡ,and TypeⅤreservoirs is found to be significantly higher than that of TypeⅢand TypeⅣreservoirs using the method of combining K-means clustering and Bayesian theory based on logging data.Although the recognition accuracy of the new methodology for the TypeⅣreservoir is low,with average accuracy the new method has reached more than 82%in the entire study area,which lays a good foundation for rapid and accurate discrimination of reservoir types and the fine evaluation of a reservoir.
关 键 词:UPSTREAM resource exploration reservoir classification CARBONATE K-means clustering Bayesian discrimination CENOMANIAN-TURONIAN Iraq
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