Integrated Global Optimization of Displacement Efficiency in Hydrocarbon Reservoirs

Integrated Global Optimization of Displacement Efficiency in Hydrocarbon Reservoirs Daoyong Yang; Daoyong Yang University of Regina Search for other works by this author on: This Site Google Scholar Qi Zhang; Qi Zhang University of Petroleum, China Search for other works by this author on: This Site Google Scholar Yongan Gu; Yongan Gu University of Regina Search for other works by this author on: This Site Google Scholar Luhua Li Luhua Li TUHA Petroleum Exploration & Development Corporation, China Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. Paper Number: SPE-81035-MS https://doi.org/10.2118/81035-MS Published: April 27 2003 Connected Content Related to: EOR/IOR: Displacement Optimization in Hydrocarbon Reservoirs Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Yang, Daoyong, Zhang, Qi, Gu, Yongan, and Luhua Li. "Integrated Global Optimization of Displacement Efficiency in Hydrocarbon Reservoirs." Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. doi: https://doi.org/10.2118/81035-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Latin America and Caribbean Petroleum Engineering Conference Search Advanced Search AbstractIn this paper, an integrated numerical technique is presented to implement global optimization of displacement efficiency in hydrocarbon reservoirs. This technique chooses the net present value (NPV) as an objective function, which accounts for production- and injection- performance as well as reservoir performance. The flowing and various artificial lifting methods are incorporated into the production performance models, which have been successfully applied in more than forty oil fields. Meanwhile, the reservoir geological model is improved by continuous monitoring and surveillance. Then the objective function is maximized to generate the optimum field production-injection strategies at different development stages using a hybrid genetic algorithm (GA). Such an integrated technique can maximize the displacement efficiency in a fixed well pattern and/or an oil field under different practical constraints. This technique is applied in a water-alternating-gas (WAG) miscible flooding reservoir, and the field performance has shown that the displacement efficiency is significantly improved and the production-injection rates are well controlled. The field water-cut remains low and stable, though the gas-oil ratio is slightly higher than the original ratio. This method can be applied to develop the optimum production- and injection- strategies in a hydrocarbon reservoir so that the displacement efficiency is maximized and the reservoir life is extended.IntroductionThe main objective of modern reservoir management is to achieve maximum displacement efficiency when a displacing agent is injected to displace the residual oil in a reservoir. Such a displacement process can be controlled properly by allocating the injected fluids to the injectors and by adjusting the produced fluids from the producers1. After being put into production, an oil field will be transformed from a static system into a dynamic one. Thus a challenging task is to integrate the production- and injection- subsystem with the reservoir subsystem so as to obtain the optimum production- and injection- strategies at the field-wide level2. Furthermore, an underground reservoir can be treated as a black box to which the injected fluids are considered as the inputs and from which the produced fluids are regarded as the outputs. Accordingly, it is necessary to incorporate the performance of different lifting methods into the integrated simulation so that the field displacement efficiency can be optimized.The optimum control of fluid movement in a reservoir is essential to development of petroleum resources3–6. In practice, the injection and production rates can be adjusted in individual wells for a given production-injection operation system (PIOS). The optimal control theory has been applied to determine the optimal injection profile for enhanced oil recovery (EOR)7–10. These applications focused on computing the best way of injecting an EOR fluid into a reservoir formation to maximize the amount of oil recovered at the minimum cost. Recently, Sudaryanto and Yortsos 1 applied rate control among the injectors to improve the displacement efficiency in porous media. However, no systematic methods are available for optimizing the displacement efficiency by adjusting the injection and/or production rates at a field-scale level.Economic optimization of the displacement efficiency for the PIOS is an ultimate goal of the reservoir management. This means that three subsystems, i.e., injection subsystem, reservoir subsystem and production subsystem, should be considered as a whole in such an optimization process. In fact, it is impossible to arrange all the possible groups in a proper way, given the fact that many decision-making variables can be chosen even for each subsystem. Several methods have been developed to optimize the PIOS, such as two-explanatory variable methods11,12, three- or more-explanatory variable methods13,14, data integration based methods15,16, and multivariate nonlinear methods17–22. Nevertheless, some do not take account of different production operation methods (POMs) or the economic factor, whereas the others either simplify or do not consider the reservoir model. In addition, the reservoir geological model is usually kept unchanged during the process of optimization, though the actual field development is essentially a dynamic process. Keywords: displacement efficiency, performance model, waterflooding, production performance model, saturation contour, algorithm, development scheme, global optimization, artificial intelligence, reservoir Subjects: Reservoir Fluid Dynamics, Improved and Enhanced Recovery, Flow in porous media, Waterflooding This content is only available via PDF. 2003. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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