Surrogate modelling approach: A solution to oil rim production optimization

Production from thin oil rim reservoirs can be very challenging due to the thin spread of the oil resources, complicated mechanism of production and fluid contact movement. Typically, the recovery from these types of reservoirs is usually low thereby making them economically unattractive. The object...

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Autores principales:	Yetunde M. Aladeitan, Akeem O. Arinkoola, Okhiria D. Udebhulu, David O. Ogbe
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	oil rim surrogate model simulation well placement optimization reservoir development Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/df8e883ca54f4f5ba84723d39900f5c5
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spelling	oai:doaj.org-article:df8e883ca54f4f5ba84723d39900f5c52021-11-04T15:51:56ZSurrogate modelling approach: A solution to oil rim production optimization2331-191610.1080/23311916.2019.1631009https://doaj.org/article/df8e883ca54f4f5ba84723d39900f5c52019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1631009https://doaj.org/toc/2331-1916Production from thin oil rim reservoirs can be very challenging due to the thin spread of the oil resources, complicated mechanism of production and fluid contact movement. Typically, the recovery from these types of reservoirs is usually low thereby making them economically unattractive. The objective of this present study is to evaluate the optimal well design for improved recovery from thin oil rim reservoirs. A surrogate modelling approach was deployed for evaluating three different development strategies. Numerical reservoir simulations were conducted to define the basis for the surrogate modelling. In all these strategies, the rim height, reservoir anisotropy, oil viscosity, horizontal permeability, bottom-hole pressure (BHP) and horizontal well length were considered as uncertainty. The selection of the best strategy was based on cumulative hydrocarbon recovery after 30 years of simulation. Uncertainty quantification was achieved using regular Monte Carlo Simulation. Management of a wide range of subsurface uncertainties was considered. The results showed that placing the well just above the oil-water contact (OWC) allowed more oil recovery compared to other strategies considered in this study. The results derived from surrogate model predictions compared favourably with those observed from the YADD thin oil rim reservoirs located in the Niger Delta. The methodology adopted saves time and is reproducible where oil rim development is desirable.Yetunde M. AladeitanAkeem O. ArinkoolaOkhiria D. UdebhuluDavid O. OgbeTaylor & Francis Grouparticleoil rimsurrogate modelsimulationwell placement optimizationreservoir developmentEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	oil rim surrogate model simulation well placement optimization reservoir development Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	oil rim surrogate model simulation well placement optimization reservoir development Engineering (General). Civil engineering (General) TA1-2040 Yetunde M. Aladeitan Akeem O. Arinkoola Okhiria D. Udebhulu David O. Ogbe Surrogate modelling approach: A solution to oil rim production optimization
description	Production from thin oil rim reservoirs can be very challenging due to the thin spread of the oil resources, complicated mechanism of production and fluid contact movement. Typically, the recovery from these types of reservoirs is usually low thereby making them economically unattractive. The objective of this present study is to evaluate the optimal well design for improved recovery from thin oil rim reservoirs. A surrogate modelling approach was deployed for evaluating three different development strategies. Numerical reservoir simulations were conducted to define the basis for the surrogate modelling. In all these strategies, the rim height, reservoir anisotropy, oil viscosity, horizontal permeability, bottom-hole pressure (BHP) and horizontal well length were considered as uncertainty. The selection of the best strategy was based on cumulative hydrocarbon recovery after 30 years of simulation. Uncertainty quantification was achieved using regular Monte Carlo Simulation. Management of a wide range of subsurface uncertainties was considered. The results showed that placing the well just above the oil-water contact (OWC) allowed more oil recovery compared to other strategies considered in this study. The results derived from surrogate model predictions compared favourably with those observed from the YADD thin oil rim reservoirs located in the Niger Delta. The methodology adopted saves time and is reproducible where oil rim development is desirable.
format	article
author	Yetunde M. Aladeitan Akeem O. Arinkoola Okhiria D. Udebhulu David O. Ogbe
author_facet	Yetunde M. Aladeitan Akeem O. Arinkoola Okhiria D. Udebhulu David O. Ogbe
author_sort	Yetunde M. Aladeitan
title	Surrogate modelling approach: A solution to oil rim production optimization
title_short	Surrogate modelling approach: A solution to oil rim production optimization
title_full	Surrogate modelling approach: A solution to oil rim production optimization
title_fullStr	Surrogate modelling approach: A solution to oil rim production optimization
title_full_unstemmed	Surrogate modelling approach: A solution to oil rim production optimization
title_sort	surrogate modelling approach: a solution to oil rim production optimization
publisher	Taylor & Francis Group
publishDate	2019
url	https://doaj.org/article/df8e883ca54f4f5ba84723d39900f5c5
work_keys_str_mv	AT yetundemaladeitan surrogatemodellingapproachasolutiontooilrimproductionoptimization AT akeemoarinkoola surrogatemodellingapproachasolutiontooilrimproductionoptimization AT okhiriadudebhulu surrogatemodellingapproachasolutiontooilrimproductionoptimization AT davidoogbe surrogatemodellingapproachasolutiontooilrimproductionoptimization
_version_	1718444681946202112

Surrogate modelling approach: A solution to oil rim production optimization

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