Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis

Abstract Reservoir performance prediction is one of the main steps during a field development plan. Due to the complexity and time-consuming aspects of numerical simulators, it is helpful to develop analytical tools for a rapid primary analysis. The capacitance–resistance model (CRM) is a simple tec...

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Autores principales:	Seyed Hamidreza Yousefi, Fariborz Rashidi, Mohammad Sharifi, Mohammad Soroush
Formato:	article
Lenguaje:	EN
Publicado:	KeAi Communications Co., Ltd. 2019
Materias:	Reservoir management Capacitance–resistance model Gas flooding Analytical model Sensitivity analysis Streamline simulation Science Q Petrology QE420-499
Acceso en línea:	https://doaj.org/article/a6b14cedbd334b979a9d9ac081769298
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spelling	oai:doaj.org-article:a6b14cedbd334b979a9d9ac0817692982021-12-02T09:53:53ZPrediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis10.1007/s12182-019-0342-61672-51071995-8226https://doaj.org/article/a6b14cedbd334b979a9d9ac0817692982019-07-01T00:00:00Zhttp://link.springer.com/article/10.1007/s12182-019-0342-6https://doaj.org/toc/1672-5107https://doaj.org/toc/1995-8226Abstract Reservoir performance prediction is one of the main steps during a field development plan. Due to the complexity and time-consuming aspects of numerical simulators, it is helpful to develop analytical tools for a rapid primary analysis. The capacitance–resistance model (CRM) is a simple technique for reservoir management and optimization. This method is an advanced time-dependent material balance equation which is combined with a productivity equation. CRM uses production/injection data and bottom-hole pressure as inputs to build a reliable model, which is then combined with the oil-cut model and converted to a predictive tool. CRM has been studied thoroughly for water flooding projects. In this study, a modified model for gas flooding systems based on gas density and average reservoir pressure is developed. A detailed procedure is described in a synthetic reservoir model using a genetic algorithm. Then, a streamline simulation is implemented for validation of the results. The results show that the proposed model is able to calculate interwell connectivity parameters and oil production rates. Moreover, a sensitivity analysis is carried out to investigate effects of drawdown pressure and gas PVT properties on the new model. Finally, acceptable ranges of input data and limitations of the model are comprehensively discussed.Seyed Hamidreza YousefiFariborz RashidiMohammad SharifiMohammad SoroushKeAi Communications Co., Ltd.articleReservoir managementCapacitance–resistance modelGas floodingAnalytical modelSensitivity analysisStreamline simulationScienceQPetrologyQE420-499ENPetroleum Science, Vol 16, Iss 5, Pp 1086-1104 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Reservoir management Capacitance–resistance model Gas flooding Analytical model Sensitivity analysis Streamline simulation Science Q Petrology QE420-499
spellingShingle	Reservoir management Capacitance–resistance model Gas flooding Analytical model Sensitivity analysis Streamline simulation Science Q Petrology QE420-499 Seyed Hamidreza Yousefi Fariborz Rashidi Mohammad Sharifi Mohammad Soroush Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
description	Abstract Reservoir performance prediction is one of the main steps during a field development plan. Due to the complexity and time-consuming aspects of numerical simulators, it is helpful to develop analytical tools for a rapid primary analysis. The capacitance–resistance model (CRM) is a simple technique for reservoir management and optimization. This method is an advanced time-dependent material balance equation which is combined with a productivity equation. CRM uses production/injection data and bottom-hole pressure as inputs to build a reliable model, which is then combined with the oil-cut model and converted to a predictive tool. CRM has been studied thoroughly for water flooding projects. In this study, a modified model for gas flooding systems based on gas density and average reservoir pressure is developed. A detailed procedure is described in a synthetic reservoir model using a genetic algorithm. Then, a streamline simulation is implemented for validation of the results. The results show that the proposed model is able to calculate interwell connectivity parameters and oil production rates. Moreover, a sensitivity analysis is carried out to investigate effects of drawdown pressure and gas PVT properties on the new model. Finally, acceptable ranges of input data and limitations of the model are comprehensively discussed.
format	article
author	Seyed Hamidreza Yousefi Fariborz Rashidi Mohammad Sharifi Mohammad Soroush
author_facet	Seyed Hamidreza Yousefi Fariborz Rashidi Mohammad Sharifi Mohammad Soroush
author_sort	Seyed Hamidreza Yousefi
title	Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
title_short	Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
title_full	Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
title_fullStr	Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
title_full_unstemmed	Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
title_sort	prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis
publisher	KeAi Communications Co., Ltd.
publishDate	2019
url	https://doaj.org/article/a6b14cedbd334b979a9d9ac081769298
work_keys_str_mv	AT seyedhamidrezayousefi predictionofimmisciblegasfloodingperformanceamodifiedcapacitanceresistancemodelandsensitivityanalysis AT fariborzrashidi predictionofimmisciblegasfloodingperformanceamodifiedcapacitanceresistancemodelandsensitivityanalysis AT mohammadsharifi predictionofimmisciblegasfloodingperformanceamodifiedcapacitanceresistancemodelandsensitivityanalysis AT mohammadsoroush predictionofimmisciblegasfloodingperformanceamodifiedcapacitanceresistancemodelandsensitivityanalysis
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Prediction of immiscible gas flooding performance: a modified capacitance–resistance model and sensitivity analysis

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