Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman

Laf Schoenicke, Saleh M. Al-Alawi, Ali S. Al-Bemani, Mohammed Z. Kalam, Xavier Le Varlet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An automated facies interpretation technique was developed for the very heterogeneous Permo-Carboniferous glacigenic Al Khlata Formation of south Oman. The technique uses two neural network models based on core- and partially outcrop-calibrated sedimentary facies. The first model predicts a set of six wireline facies based on quantitative analysis of conventional wireline log data. The second can predict all predefined sedimentary facies and facies associations using qualitative information of the internal formation organization and the quantitative data of the first model. The highly robust output can directly be used as input for 3D modeling of reservoir architecture and ultimately in 4D dynamic simulations for optimized field development.

Original languageEnglish
Title of host publicationManaging the Future: Challenges for People, Resources and Technology
Editors Anon
PublisherSoc Pet Eng (SPE)
Pages649-669
Number of pages21
Publication statusPublished - 1999
EventProceedings of the 1999 11th SPE Middle East Oil Show & Conference - Bahrain, India
Duration: Feb 20 1999Feb 23 1999

Other

OtherProceedings of the 1999 11th SPE Middle East Oil Show & Conference
CityBahrain, India
Period2/20/992/23/99

Fingerprint

artificial neural network
Neural networks
quantitative analysis
Computer simulation
Chemical analysis
outcrop
modeling
simulation

ASJC Scopus subject areas

  • Geology
  • Geotechnical Engineering and Engineering Geology

Cite this

Schoenicke, L., Al-Alawi, S. M., Al-Bemani, A. S., Kalam, M. Z., & Varlet, X. L. (1999). Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman. In Anon (Ed.), Managing the Future: Challenges for People, Resources and Technology (pp. 649-669). Soc Pet Eng (SPE).

Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman. / Schoenicke, Laf; Al-Alawi, Saleh M.; Al-Bemani, Ali S.; Kalam, Mohammed Z.; Varlet, Xavier Le.

Managing the Future: Challenges for People, Resources and Technology. ed. / Anon. Soc Pet Eng (SPE), 1999. p. 649-669.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Schoenicke, L, Al-Alawi, SM, Al-Bemani, AS, Kalam, MZ & Varlet, XL 1999, Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman. in Anon (ed.), Managing the Future: Challenges for People, Resources and Technology. Soc Pet Eng (SPE), pp. 649-669, Proceedings of the 1999 11th SPE Middle East Oil Show & Conference, Bahrain, India, 2/20/99.
Schoenicke L, Al-Alawi SM, Al-Bemani AS, Kalam MZ, Varlet XL. Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman. In Anon, editor, Managing the Future: Challenges for People, Resources and Technology. Soc Pet Eng (SPE). 1999. p. 649-669
Schoenicke, Laf ; Al-Alawi, Saleh M. ; Al-Bemani, Ali S. ; Kalam, Mohammed Z. ; Varlet, Xavier Le. / Preliminary studies on using Artificial Neural Networks to predict sedimentary facies of the Permo-Carboniferous glacigenic Al Khlata Formation, Oman. Managing the Future: Challenges for People, Resources and Technology. editor / Anon. Soc Pet Eng (SPE), 1999. pp. 649-669
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