Application of Neurofuzzy pattern recognition method in borehole geophysics

Geophysical data are specific physical responses of geological formations distributed over an area. These data are normally the physical parameters such as density, velocity, resistivity, susceptibility etc. of geological sources and hence bring a pattern of geological structures. It is conceived ac...

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Published in:Acta Geodaetica et Geophysica Hungarica
Main Authors: Singh, U., Singh, D., Singh, H.
Format: Article in Journal/Newspaper
Language:Hungarian
Published: Akadémiai Kiadó 2010
Subjects:
Online Access:http://real.mtak.hu/82260/
http://real.mtak.hu/82260/1/ageod.45.2010.4.2.pdf
https://doi.org/10.1556/AGeod.45.2010.4.2
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spelling ftmtak:oai:real.mtak.hu:82260 2023-05-15T13:46:16+02:00 Application of Neurofuzzy pattern recognition method in borehole geophysics Singh, U. Singh, D. Singh, H. 2010 text http://real.mtak.hu/82260/ http://real.mtak.hu/82260/1/ageod.45.2010.4.2.pdf https://doi.org/10.1556/AGeod.45.2010.4.2 hu hun Akadémiai Kiadó http://real.mtak.hu/82260/1/ageod.45.2010.4.2.pdf Singh, U. and Singh, D. and Singh, H. (2010) Application of Neurofuzzy pattern recognition method in borehole geophysics. Acta Geodaetica et Geophysica Hungarica, 45 (4). pp. 417-425. ISSN 1217-8977 QE01 Geophysics / geofizika Article PeerReviewed info:eu-repo/semantics/article 2010 ftmtak https://doi.org/10.1556/AGeod.45.2010.4.2 2018-09-12T23:05:09Z Geophysical data are specific physical responses of geological formations distributed over an area. These data are normally the physical parameters such as density, velocity, resistivity, susceptibility etc. of geological sources and hence bring a pattern of geological structures. It is conceived accordingly that this pattern recognition of such geophysical data will throw light on the spatial distribution and physical attributes of their geological sources. The well logging method considered as one of the geophysical method for the exploration of hydrocarbon, coal and base-metals, also has a strong role in finding the location and evaluation of geological resources.A novel approach known as Adaptive Neurofuzzy Inference System technique (ANFIS) is made to identify stratigraphy of Prydz Bay basin, east Antarctica. A geological stratum in terms of 1D model is made using datasets obtained from this area. The 1D model deduced as an ANFIS result is able to make geological sense of even additional thin sand sandwiched between clayey silt strata seams which unable to be resolved by other conventional methods. The analysed ANFIS results deduced to map horizons for hydrocarbon prospecting is verified with known coring datasets. These results are encouraging and provide stable and consistent solutions. Article in Journal/Newspaper Antarc* Antarctica East Antarctica Prydz Bay MTAK: REAL (Library and Information Centre of the Hungarian Academy of Sciences East Antarctica Prydz Bay Acta Geodaetica et Geophysica Hungarica 45 4 417 425
institution Open Polar
collection MTAK: REAL (Library and Information Centre of the Hungarian Academy of Sciences
op_collection_id ftmtak
language Hungarian
topic QE01 Geophysics / geofizika
spellingShingle QE01 Geophysics / geofizika
Singh, U.
Singh, D.
Singh, H.
Application of Neurofuzzy pattern recognition method in borehole geophysics
topic_facet QE01 Geophysics / geofizika
description Geophysical data are specific physical responses of geological formations distributed over an area. These data are normally the physical parameters such as density, velocity, resistivity, susceptibility etc. of geological sources and hence bring a pattern of geological structures. It is conceived accordingly that this pattern recognition of such geophysical data will throw light on the spatial distribution and physical attributes of their geological sources. The well logging method considered as one of the geophysical method for the exploration of hydrocarbon, coal and base-metals, also has a strong role in finding the location and evaluation of geological resources.A novel approach known as Adaptive Neurofuzzy Inference System technique (ANFIS) is made to identify stratigraphy of Prydz Bay basin, east Antarctica. A geological stratum in terms of 1D model is made using datasets obtained from this area. The 1D model deduced as an ANFIS result is able to make geological sense of even additional thin sand sandwiched between clayey silt strata seams which unable to be resolved by other conventional methods. The analysed ANFIS results deduced to map horizons for hydrocarbon prospecting is verified with known coring datasets. These results are encouraging and provide stable and consistent solutions.
format Article in Journal/Newspaper
author Singh, U.
Singh, D.
Singh, H.
author_facet Singh, U.
Singh, D.
Singh, H.
author_sort Singh, U.
title Application of Neurofuzzy pattern recognition method in borehole geophysics
title_short Application of Neurofuzzy pattern recognition method in borehole geophysics
title_full Application of Neurofuzzy pattern recognition method in borehole geophysics
title_fullStr Application of Neurofuzzy pattern recognition method in borehole geophysics
title_full_unstemmed Application of Neurofuzzy pattern recognition method in borehole geophysics
title_sort application of neurofuzzy pattern recognition method in borehole geophysics
publisher Akadémiai Kiadó
publishDate 2010
url http://real.mtak.hu/82260/
http://real.mtak.hu/82260/1/ageod.45.2010.4.2.pdf
https://doi.org/10.1556/AGeod.45.2010.4.2
geographic East Antarctica
Prydz Bay
geographic_facet East Antarctica
Prydz Bay
genre Antarc*
Antarctica
East Antarctica
Prydz Bay
genre_facet Antarc*
Antarctica
East Antarctica
Prydz Bay
op_relation http://real.mtak.hu/82260/1/ageod.45.2010.4.2.pdf
Singh, U. and Singh, D. and Singh, H. (2010) Application of Neurofuzzy pattern recognition method in borehole geophysics. Acta Geodaetica et Geophysica Hungarica, 45 (4). pp. 417-425. ISSN 1217-8977
op_doi https://doi.org/10.1556/AGeod.45.2010.4.2
container_title Acta Geodaetica et Geophysica Hungarica
container_volume 45
container_issue 4
container_start_page 417
op_container_end_page 425
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