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Production forecast for niger delta oil rim synthetic reservoirs
The data sets in this article are related to a Placket Burman (PB) design of experiment (DOE) made on a wider range of uncertainties such as: reservoir, operational and reservoir architecture parameters that affect oil rim productivities. The design was based on a 2 level PB-DOE to create oil rim mo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141438/ https://www.ncbi.nlm.nih.gov/pubmed/30229097 http://dx.doi.org/10.1016/j.dib.2018.06.115 |
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author | Olabode, Oluwasanmi A. Egeonu, Gerald I. Temiloluwa, Ojo I. Tomiwa, Oguntade Oreofeoluwa, Bamigboye |
author_facet | Olabode, Oluwasanmi A. Egeonu, Gerald I. Temiloluwa, Ojo I. Tomiwa, Oguntade Oreofeoluwa, Bamigboye |
author_sort | Olabode, Oluwasanmi A. |
collection | PubMed |
description | The data sets in this article are related to a Placket Burman (PB) design of experiment (DOE) made on a wider range of uncertainties such as: reservoir, operational and reservoir architecture parameters that affect oil rim productivities. The design was based on a 2 level PB-DOE to create oil rim models which were developed into reservoir models using the Eclipse software and configured under the best depletion strategy of concurrent oil and gas production. Approximate solutions to the models was developed to forecast oil production using the least square method. The Monte-Carlo simulation approach was used in estimating 3 production forecasts for the oil rim reservoirs. This will help to create a probabilistic variety of forecasts that can further be used in making decisions. |
format | Online Article Text |
id | pubmed-6141438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61414382018-09-18 Production forecast for niger delta oil rim synthetic reservoirs Olabode, Oluwasanmi A. Egeonu, Gerald I. Temiloluwa, Ojo I. Tomiwa, Oguntade Oreofeoluwa, Bamigboye Data Brief Engineering The data sets in this article are related to a Placket Burman (PB) design of experiment (DOE) made on a wider range of uncertainties such as: reservoir, operational and reservoir architecture parameters that affect oil rim productivities. The design was based on a 2 level PB-DOE to create oil rim models which were developed into reservoir models using the Eclipse software and configured under the best depletion strategy of concurrent oil and gas production. Approximate solutions to the models was developed to forecast oil production using the least square method. The Monte-Carlo simulation approach was used in estimating 3 production forecasts for the oil rim reservoirs. This will help to create a probabilistic variety of forecasts that can further be used in making decisions. Elsevier 2018-07-04 /pmc/articles/PMC6141438/ /pubmed/30229097 http://dx.doi.org/10.1016/j.dib.2018.06.115 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Engineering Olabode, Oluwasanmi A. Egeonu, Gerald I. Temiloluwa, Ojo I. Tomiwa, Oguntade Oreofeoluwa, Bamigboye Production forecast for niger delta oil rim synthetic reservoirs |
title | Production forecast for niger delta oil rim synthetic reservoirs |
title_full | Production forecast for niger delta oil rim synthetic reservoirs |
title_fullStr | Production forecast for niger delta oil rim synthetic reservoirs |
title_full_unstemmed | Production forecast for niger delta oil rim synthetic reservoirs |
title_short | Production forecast for niger delta oil rim synthetic reservoirs |
title_sort | production forecast for niger delta oil rim synthetic reservoirs |
topic | Engineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141438/ https://www.ncbi.nlm.nih.gov/pubmed/30229097 http://dx.doi.org/10.1016/j.dib.2018.06.115 |
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