A modified Fuzzy C-Means (FCM) Clustering algorithm and its application on carbonate fluid identification

Considering the fact that the fluid distribution in carbonate reservoir is very complicated and the existing fluid prediction methods are not able to produce ideal predicted results, this paper proposes a new fluid identification method in carbonate reservoir based on the modified Fuzzy C-Means (FCM...

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Vydáno v:Journal of applied geophysics Ročník 129; s. 28 - 35
Hlavní autoři: Liu, Lifeng, Sun, Sam Zandong, Yu, Hongyu, Yue, Xingtong, Zhang, Dong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.06.2016
Témata:
Algorithms
Carbonate rock
Carbonates
Chaotic Quantum Particle Swarm Optimization
Clustering
Clusters
Fluid factor
Fluid identification
Fluids
Fuzzy
Fuzzy C-Means Clustering
Geophysics
Reservoirs
China, People's Rep., Xinjiang, Tarim Basin
China, People's Rep
Fuzzy C-Means Clustering
Fluid identification
Fluid factor
Chaotic Quantum Particle Swarm Optimization
Carbonate rock
ISSN:0926-9851, 1879-1859
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Shrnutí:Considering the fact that the fluid distribution in carbonate reservoir is very complicated and the existing fluid prediction methods are not able to produce ideal predicted results, this paper proposes a new fluid identification method in carbonate reservoir based on the modified Fuzzy C-Means (FCM) Clustering algorithm. Both initialization and globally optimum cluster center are produced by Chaotic Quantum Particle Swarm Optimization (CQPSO) algorithm, which can effectively avoid the disadvantage of sensitivity to initial values and easily falling into local convergence in the traditional FCM Clustering algorithm. Then, the modified algorithm is applied to fluid identification in the carbonate X area in Tarim Basin of China, and a mapping relation between fluid properties and pre-stack elastic parameters will be built in multi-dimensional space. It has been proven that this modified algorithm has a good ability of fuzzy cluster and its total coincidence rate of fluid prediction reaches 97.10%. Besides, the membership of different fluids can be accumulated to obtain respective probability, which can evaluate the uncertainty in fluid identification result. •A modified FCM Clustering algorithm named CQPSO-FCM Clustering algorithm is proposed.•The modified algorithm is applied to the carbonate reservoir fluid prediction.•The calculating process and pseudo code is detailed.•The comparison between the new algorithm and the old method is introduced.
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ISSN:0926-9851
1879-1859
DOI:10.1016/j.jappgeo.2016.03.027