Triangular Grid-Based Fuzzy Cross-Update Inversion of Gravity Data: Case Studies from Mineral Exploration
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In mineral exploration, geophysical inversion is a common mathematical tool to obtain reliable information on subsurface density properties based on gravity measurements. Many inversion algorithms were developed to obtain the density distribution in the Earth’s subsurface. Recovered density values are usually lower/higher than the actual density as a consequence of inversion algorithm. This paper presents the use of a fuzzy cross-update inversion (FCUI) procedure to improve the subsurface density model based on a triangular grid. The algorithm is written in MATLAB and uses fuzzy c means clustering to improve the density modeling result per iteration. Two additional input parameters are added, namely the number of geologic units in the model (i.e., number of clusters) and the cluster center values of the geologic units (mean density value of each geologic unit). Inversion results from the FCUI are presented and compared with conventional inversion. The effectiveness of the developed technique is tested for the interpretation of synthetic data and two sets of field data. The FCUI approach shows improvement over conventional inversion approaches in differentiating geologic units. Further, FCUI was performed to reduce ambiguity of interpretation for the delineation of chromite and uranium deposits as the first and second case studies, respectively. We integrated favorable information and show the efficacy of FCUI over conventional inversion for the field datasets.
KeywordsFuzzy cross-update inversion Conventional inversion Fuzzy c means clustering Gravity data Triangular grid Mineral exploration
The author is thankful to the Prof. John Carranza (Editor-in-Chief), Prof. Colin Farquharson, and anonymous reviewers for the reviews and numerous suggestions which greatly improved the paper. The author is also thankful to Dr. Shuang Liu, China University of Geosciences (Wuhan), for his 2D-CDTGMI code to compare the results. The author is extremely grateful to the IRCC-IITB for the financial support to carry out this study in the form of a Seed Grant Project (Project code- RD/0518-IRCCSH0-022).
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