Curve fitting using logarithmic function for sea bed logging data

The aim of this research work is to conduct curve fitting using mathematical equations that relate location of the hydrocarbon (HC) at different depths to different frequencies. COMSOL MultiPhysics software was used to generate models of the seabed logging technique which consists of air, sea water,...

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Main Authors: Daud, H., Razali, R., Zaki, M.R.O., Shafie, A.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.25309 /
Published: American Scientific Publishers 2016
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013676268&doi=10.1166%2fjctn.2016.5738&partnerID=40&md5=8c3647b3d2e98cd4d857c2498b3c0ab3
http://eprints.utp.edu.my/25309/
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spelling utp-eprints.253092021-08-27T12:57:01Z Curve fitting using logarithmic function for sea bed logging data Daud, H. Razali, R. Zaki, M.R.O. Shafie, A. The aim of this research work is to conduct curve fitting using mathematical equations that relate location of the hydrocarbon (HC) at different depths to different frequencies. COMSOL MultiPhysics software was used to generate models of the seabed logging technique which consists of air, sea water, and sediment and HC layer. Seabed Logging (SBL) is a technique to find the resistive layers under seabed by transmitting low frequency of EM waves through sea water and sediment. As HC is known to have high resistivity which is about 30-500 Ωm, EM waves will be guided and reflected back and detected by the receiver that are placed on the seafloor. In SBL, low frequency is used to obtain greater wavelength which allows EM waves to penetrate at longer distance and each frequency used has different skin depth. The frequencies used in this project were 0.5 Hz, 0.25 Hz, 0.125 Hz and 0.0625 Hz and the depths of the HC were varied from 1000 m to 3000 m with increment of 250 m. Data generated from COMSOL software was extracted for the set up with and without HC and trend lines using logarithmic functions were developed and R2 were calculated for each equation and curve. The calculated R2 was compared between data with HC to no HC at each depth and it was found that the calculated R2 values were very well fitted for deeper HC depth. This indicates that as depth of HC is higher, it is difficult to distinguish data with and without HC presence; and perhaps a new technique can be explored. © Copyright 2016 American Scientific Publishers All rights reserved. American Scientific Publishers 2016 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013676268&doi=10.1166%2fjctn.2016.5738&partnerID=40&md5=8c3647b3d2e98cd4d857c2498b3c0ab3 Daud, H. and Razali, R. and Zaki, M.R.O. and Shafie, A. (2016) Curve fitting using logarithmic function for sea bed logging data. Journal of Computational and Theoretical Nanoscience, 13 (10). pp. 7448-7454. http://eprints.utp.edu.my/25309/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The aim of this research work is to conduct curve fitting using mathematical equations that relate location of the hydrocarbon (HC) at different depths to different frequencies. COMSOL MultiPhysics software was used to generate models of the seabed logging technique which consists of air, sea water, and sediment and HC layer. Seabed Logging (SBL) is a technique to find the resistive layers under seabed by transmitting low frequency of EM waves through sea water and sediment. As HC is known to have high resistivity which is about 30-500 Ωm, EM waves will be guided and reflected back and detected by the receiver that are placed on the seafloor. In SBL, low frequency is used to obtain greater wavelength which allows EM waves to penetrate at longer distance and each frequency used has different skin depth. The frequencies used in this project were 0.5 Hz, 0.25 Hz, 0.125 Hz and 0.0625 Hz and the depths of the HC were varied from 1000 m to 3000 m with increment of 250 m. Data generated from COMSOL software was extracted for the set up with and without HC and trend lines using logarithmic functions were developed and R2 were calculated for each equation and curve. The calculated R2 was compared between data with HC to no HC at each depth and it was found that the calculated R2 values were very well fitted for deeper HC depth. This indicates that as depth of HC is higher, it is difficult to distinguish data with and without HC presence; and perhaps a new technique can be explored. © Copyright 2016 American Scientific Publishers All rights reserved.
format Article
author Daud, H.
Razali, R.
Zaki, M.R.O.
Shafie, A.
spellingShingle Daud, H.
Razali, R.
Zaki, M.R.O.
Shafie, A.
Curve fitting using logarithmic function for sea bed logging data
author_sort Daud, H.
title Curve fitting using logarithmic function for sea bed logging data
title_short Curve fitting using logarithmic function for sea bed logging data
title_full Curve fitting using logarithmic function for sea bed logging data
title_fullStr Curve fitting using logarithmic function for sea bed logging data
title_full_unstemmed Curve fitting using logarithmic function for sea bed logging data
title_sort curve fitting using logarithmic function for sea bed logging data
publisher American Scientific Publishers
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013676268&doi=10.1166%2fjctn.2016.5738&partnerID=40&md5=8c3647b3d2e98cd4d857c2498b3c0ab3
http://eprints.utp.edu.my/25309/
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score 11.62408