3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm
Liu, Sheng1,2,3; Jin, Shuanggen3,4
AbstractThe geophysical inversion with combining prior information is very important for resource exploration and studies of the Earth's internal structure. Guided fuzzy C-means clustering inversion (FCM) is normally applied for the Tikhonov regularized inversion, but has the shortcoming of uniform model parameter shrinkage, leading to inaccuracy. In this paper, an improved guided fuzzy clustering algorithm is proposed by adding a fuzzy entropy term to the original guided FCM. This method not only enforces the discrete values to a high degree of approximation by guiding the recovered model to cluster tightly around the known petrophysical property values, but also calculates the distributed characteristics of the model parameter set. Based on this method, the shortcoming of uniform shrinkage of the original guided FCM clustering algorithm is improved, and more accurate inversion results are obtained, making the FCM method more efficient and broadly applicable. Furthermore, a new parameter search algorithm is proposed to accelerate the search speed. The results recovered by using this method with three kinds of theoretical gravity anomaly data show more accurate density anomalies compared with the results generated from the original guided FCM clustering inversion and greater efficiency in the parametric search process when using the new parameter search algorithm. The improved FCM clustering algorithm could enable more extensive and efficient use of gravity inversion.
KeywordFuzzy entropy discrete-valued inversion gravity inversion parameter search fuzzy C-means algorithm
WOS Research AreaGeochemistry & Geophysics
WOS SubjectGeochemistry & Geophysics
WOS IDWOS:000511540200025
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Document Type期刊论文
Corresponding AuthorJin, Shuanggen
Affiliation1.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
4.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
Recommended Citation
GB/T 7714
Liu, Sheng,Jin, Shuanggen. 3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm[J]. PURE AND APPLIED GEOPHYSICS,2020,177(2):1005-1027.
APA Liu, Sheng,&Jin, Shuanggen.(2020).3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm.PURE AND APPLIED GEOPHYSICS,177(2),1005-1027.
MLA Liu, Sheng,et al."3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm".PURE AND APPLIED GEOPHYSICS 177.2(2020):1005-1027.
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