Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen

Arafat Mohammed Bin Mohammed; Akram Javed; Mohammed Sultan Alshayef

doi:doi:10.11648/j.ajrs.20170501.11

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Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen

Arafat Mohammed Bin Mohammed, Akram Javed, Mohammed Sultan Alshayef

Published in American Journal of Remote Sensing (Volume 5, Issue 1)

Received: 12 February 2017 Accepted: 6 March 2017 Published: 21 March 2017

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Abstract

GIS Provides spatial and analytical support to assess multicriteria (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum. This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 9 subcriteria combined to produce a favorability map of potential exploration areas. A case study applied to Sayun Almasilah Basin East Yemen. We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.

Published in	American Journal of Remote Sensing (Volume 5, Issue 1)
DOI	10.11648/j.ajrs.20170501.11
Page(s)	1-9
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Petroleum Exploration, Spatial Modeling, MCE, Fuzzy Logic, Favorability Zones

References

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APA Style

Arafat Mohammed Bin Mohammed, Akram Javed, Mohammed Sultan Alshayef. (2017). Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. American Journal of Remote Sensing, 5(1), 1-9. https://doi.org/10.11648/j.ajrs.20170501.11

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ACS Style

Arafat Mohammed Bin Mohammed; Akram Javed; Mohammed Sultan Alshayef. Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. Am. J. Remote Sens. 2017, 5(1), 1-9. doi: 10.11648/j.ajrs.20170501.11

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AMA Style

Arafat Mohammed Bin Mohammed, Akram Javed, Mohammed Sultan Alshayef. Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. Am J Remote Sens. 2017;5(1):1-9. doi: 10.11648/j.ajrs.20170501.11

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@article{10.11648/j.ajrs.20170501.11,
  author = {Arafat Mohammed Bin Mohammed and Akram Javed and Mohammed Sultan Alshayef},
  title = {Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen},
  journal = {American Journal of Remote Sensing},
  volume = {5},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.ajrs.20170501.11},
  url = {https://doi.org/10.11648/j.ajrs.20170501.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20170501.11},
  abstract = {GIS Provides spatial and analytical support to assess multicriteria (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum. This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 9 subcriteria combined to produce a favorability map of potential exploration areas. A case study applied to Sayun Almasilah Basin East Yemen. We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.},
 year = {2017}
}

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TY  - JOUR
T1  - Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen
AU  - Arafat Mohammed Bin Mohammed
AU  - Akram Javed
AU  - Mohammed Sultan Alshayef
Y1  - 2017/03/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ajrs.20170501.11
DO  - 10.11648/j.ajrs.20170501.11
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20170501.11
AB  - GIS Provides spatial and analytical support to assess multicriteria (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum. This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 9 subcriteria combined to produce a favorability map of potential exploration areas. A case study applied to Sayun Almasilah Basin East Yemen. We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.
VL  - 5
IS  - 1
ER  -

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Author Information

Arafat Mohammed Bin Mohammed

Department of Oil & Gas, Faculty of Oil and Minerals, Aden University, Shabwa, Yemen
Akram Javed

Department of Geology, Faculty of Science, Aligarh Muslim University, Aligarh, India
Mohammed Sultan Alshayef

Department of Geology, Faculty of Science, Aligarh Muslim University, Aligarh, India

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APA Style

Arafat Mohammed Bin Mohammed, Akram Javed, Mohammed Sultan Alshayef. (2017). Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. American Journal of Remote Sensing, 5(1), 1-9. https://doi.org/10.11648/j.ajrs.20170501.11

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ACS Style

Arafat Mohammed Bin Mohammed; Akram Javed; Mohammed Sultan Alshayef. Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. Am. J. Remote Sens. 2017, 5(1), 1-9. doi: 10.11648/j.ajrs.20170501.11

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AMA Style

Arafat Mohammed Bin Mohammed, Akram Javed, Mohammed Sultan Alshayef. Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen. Am J Remote Sens. 2017;5(1):1-9. doi: 10.11648/j.ajrs.20170501.11

Copy | Download

@article{10.11648/j.ajrs.20170501.11,
  author = {Arafat Mohammed Bin Mohammed and Akram Javed and Mohammed Sultan Alshayef},
  title = {Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen},
  journal = {American Journal of Remote Sensing},
  volume = {5},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.ajrs.20170501.11},
  url = {https://doi.org/10.11648/j.ajrs.20170501.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20170501.11},
  abstract = {GIS Provides spatial and analytical support to assess multicriteria (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum. This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 9 subcriteria combined to produce a favorability map of potential exploration areas. A case study applied to Sayun Almasilah Basin East Yemen. We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Spatial Data Modeling Based MCE Fuzzy Logic for Petroleum Exploration in Part of Say'un-Masilah Basin of Yemen
AU  - Arafat Mohammed Bin Mohammed
AU  - Akram Javed
AU  - Mohammed Sultan Alshayef
Y1  - 2017/03/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ajrs.20170501.11
DO  - 10.11648/j.ajrs.20170501.11
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20170501.11
AB  - GIS Provides spatial and analytical support to assess multicriteria (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum. This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 9 subcriteria combined to produce a favorability map of potential exploration areas. A case study applied to Sayun Almasilah Basin East Yemen. We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.
VL  - 5
IS  - 1
ER  -

Copy | Download