Optimising noise intervened data processes for inverse geoelectrical problem using adaptive neuro fuzzy inference system (ANFIS) | ||
| NRIAG Journal of Astronomy and Geophysics | ||
| Volume 10, Issue 1, January 2021, Pages 138-154 PDF (11.92 M) | ||
| DOI: 10.1080/20909977.2021.1900525 | ||
| Authors | ||
| A. Stanley Raj; D. Hudson Oliver; Y. Srinivas; J. Viswanath | ||
| Abstract | ||
| Geoelectrical inversion has some problems in inverting data due to the heterogeneous behaviour of Earth. One of the major concerns in inverting the data is due to the influence of noises, which comes from the disturbance due to human interventions, atmospheric variations, and electromagnetic disturbance, etc. . In this paper, we have presented a concept of Neuro Fuzzy algorithm which can interpret the noisy data successfully. Moreover, the data were tested with artificially generated random noise, gaussian noise and missing data. Kanyakumari field region having complex geological structures and its performance is validated with a maximum threshold. Kanyakumari field region having complex geological structures is used and the performance is validated with a maximum threshold. Neuro fuzzy technique has the dominant feature of training and testing the data with utmost accuracy. These implications are made to create the specific Graphical User Interface (GUI) for the algorithm and it works well for all types of Vertical Electrical Sounding (VES) data with good performance results. | ||
| Keywords | ||
| Adaptive neuro fuzzy inference system; resistivity inversion; subsurface modelling; noise intervened processing; layer model | ||
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