An unsupervised clustering method for nuclear magnetic resonance transverse relaxation spectrums based on the Gaussian mixture model and its application

An unsupervised clustering method for nuclear magnetic resonance transverse relaxation spectrums based on the Gaussian mixture model and its application

To make the quantitative results of nuclear magnetic resonance (NMR) transverse relaxation (T2) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T2 spectrums ba...

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Bibliographic Details
Main Authors: Xinmin GE, Zong’an XUE, Jun ZHOU, Falong HU, Jiangtao LI, Hengrong ZHANG, Shuolong WANG, Shenyuan NIU, Ji’er ZHAO
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2022-04-01
Series:Petroleum Exploration and Development
Subjects:
NMR T2 spectrum
Gaussian mixture model
expectation-maximization algorithm
Akaike information criterion
unsupervised clustering method
quantitative pore structure evaluation
Online Access:http://www.sciencedirect.com/science/article/pii/S1876380422600284

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