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 eval-uation. 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 like-lihood 'Level V'. These results are consistent with the gas saturation values obtained using Archie's rela-tionship. 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.(c) 2022 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).