Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory

The efficiency of gas hydrate production depends on the success of gas exploration and occurrence evaluation. The existing evaluation models are generally univariate and only applicable to certain geological settings. This study presents a holistic approach to evaluate the likelihood of gas hydrate...

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Main Authors: Pierre Guy Atangana Njock, Shui-Long Shen, Annan Zhou
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Geoscience Frontiers
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1674987122001669
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author Pierre Guy Atangana Njock
Shui-Long Shen
Annan Zhou
author_facet Pierre Guy Atangana Njock
Shui-Long Shen
Annan Zhou
author_sort Pierre Guy Atangana Njock
collection DOAJ
description The efficiency of gas hydrate production depends on the success of gas exploration and occurrence evaluation. The existing evaluation models are generally univariate and only applicable to certain geological settings. This study presents a holistic approach to evaluate the likelihood of gas hydrate occurrence by supplying an index for mapping gas hydrate levels with depth. The approach integrates a generalised TOPSIS method with the fuzzy set theory. An expedition of gas hydrate conducted in the Shenhu area of the South China Sea was adopted as a case study to assess the reliability of the proposed index. As a multivariate model, the proposed approach enables the capture of non-linearity associated with gas hydrates in its entirety. The magnitude of the strength of the influential factor varies substantially from one site to another across the Shenhu area. The results also show that no site achieves the highest likelihood ‘Level V’. These results are consistent with the gas saturation values obtained using Archie’s relationship. For example, at SH4 and SH7, the values of the likelihood index are the highest between 170–185 m and 150–165 m, respectively, and the observed saturation at these locations varies from 20% (SH4) to 43% (SH7). The proposed likelihood index yields a prominent ability to quantify the level of occurrence of gas hydrates with depth at different sites. It appears to be an efficient multicriteria system bound to improve the management of the gas production trial stage.
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spelling doaj.art-a62656c8bc5243919254bb7f57fa07f32023-08-02T07:28:55ZengElsevierGeoscience Frontiers1674-98712023-03-01142101513Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theoryPierre Guy Atangana Njock0Shui-Long Shen1Annan Zhou2MOE Key Laboratory of Intelligent Manufacturing Technology, Department of Civil and Environmental Engineering, College of Engineering, Shantou University, Guangdong 515063, ChinaMOE Key Laboratory of Intelligent Manufacturing Technology, Department of Civil and Environmental Engineering, College of Engineering, Shantou University, Guangdong 515063, China; Corresponding author.Discipline of Civil and Infrastructure Engineering, School of Engineering, Royal Melbourne Institute of Technology, Victoria 3001, AustraliaThe efficiency of gas hydrate production depends on the success of gas exploration and occurrence evaluation. The existing evaluation models are generally univariate and only applicable to certain geological settings. This study presents a holistic approach to evaluate the likelihood of gas hydrate occurrence by supplying an index for mapping gas hydrate levels with depth. The approach integrates a generalised TOPSIS method with the fuzzy set theory. An expedition of gas hydrate conducted in the Shenhu area of the South China Sea was adopted as a case study to assess the reliability of the proposed index. As a multivariate model, the proposed approach enables the capture of non-linearity associated with gas hydrates in its entirety. The magnitude of the strength of the influential factor varies substantially from one site to another across the Shenhu area. The results also show that no site achieves the highest likelihood ‘Level V’. These results are consistent with the gas saturation values obtained using Archie’s relationship. For example, at SH4 and SH7, the values of the likelihood index are the highest between 170–185 m and 150–165 m, respectively, and the observed saturation at these locations varies from 20% (SH4) to 43% (SH7). The proposed likelihood index yields a prominent ability to quantify the level of occurrence of gas hydrates with depth at different sites. It appears to be an efficient multicriteria system bound to improve the management of the gas production trial stage.http://www.sciencedirect.com/science/article/pii/S1674987122001669Gas hydratesSouth China SeaGeologic controlsOccurrence characterizationEnergy resource
spellingShingle Pierre Guy Atangana Njock
Shui-Long Shen
Annan Zhou
Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
Geoscience Frontiers
Gas hydrates
South China Sea
Geologic controls
Occurrence characterization
Energy resource
title Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
title_full Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
title_fullStr Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
title_full_unstemmed Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
title_short Characterisation of likelihood of gas hydrates occurrence in the South China Sea based on Bonferroni mean-based TOPSIS and fuzzy set theory
title_sort characterisation of likelihood of gas hydrates occurrence in the south china sea based on bonferroni mean based topsis and fuzzy set theory
topic Gas hydrates
South China Sea
Geologic controls
Occurrence characterization
Energy resource
url http://www.sciencedirect.com/science/article/pii/S1674987122001669
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