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Geoelectrical Data Inversion by Clustering Techniques of Fuzzy Logic to Estimate the Subsurface Layer Model
Joint Authors
Raj, A. Stanley
Oliver, D. Hudson
Srinivas, Y.
Source
International Journal of Geophysics
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Soft computing based geoelectrical data inversion differs from conventional computing in fixing the uncertainty problems.
It is tractable, robust, efficient, and inexpensive.
In this paper, fuzzy logic clustering methods are used in the inversion of geoelectrical resistivity data.
In order to characterize the subsurface features of the earth one should rely on the true field oriented data validation.
This paper supports the field data obtained from the published results and also plays a crucial role in making an interdisciplinary approach to solve complex problems.
Three clustering algorithms of fuzzy logic, namely, fuzzy C-means clustering, fuzzy K-means clustering, and fuzzy subtractive clustering, were analyzed with the help of fuzzy inference system (FIS) training on synthetic data.
Here in this approach, graphical user interface (GUI) was developed with the integration of three algorithms and the input data (AB/2 and apparent resistivity), while importing will process each algorithm and interpret the layer model parameters (true resistivity and depth).
A complete overview on the three above said algorithms is presented in the text.
It is understood from the results that fuzzy logic subtractive clustering algorithm gives more reliable results and shows efficacy of soft computing tools in the inversion of geoelectrical resistivity data.
American Psychological Association (APA)
Raj, A. Stanley& Oliver, D. Hudson& Srinivas, Y.. 2015. Geoelectrical Data Inversion by Clustering Techniques of Fuzzy Logic to Estimate the Subsurface Layer Model. International Journal of Geophysics،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1066052
Modern Language Association (MLA)
Raj, A. Stanley…[et al.]. Geoelectrical Data Inversion by Clustering Techniques of Fuzzy Logic to Estimate the Subsurface Layer Model. International Journal of Geophysics No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1066052
American Medical Association (AMA)
Raj, A. Stanley& Oliver, D. Hudson& Srinivas, Y.. Geoelectrical Data Inversion by Clustering Techniques of Fuzzy Logic to Estimate the Subsurface Layer Model. International Journal of Geophysics. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1066052
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1066052