Enhanced-oil-recovery (EOR) evaluations focused on asset acquisition or rejuvenation involve a combination of complex decisions using different data sources. EOR projects traditionally have been associated with high capital and operational expenditures (CAPEX and OPEX, respectively) as well as high financial risk, which tend to limit the number of EOR projects launched. We propose a workflow for EOR evaluations that accounts for different volumes and quality of information. This flexible workflow has been applied successfully to oil-property evaluations and EORfeasibility studies in many oil reservoirs. The method associated with the workflow relies on traditional (e.g., look-up tables, x-y correlations) and more-advanced (data mining for analog-reservoir search and geology indicators) screening methods, emphasizing identification of analogs to support decision making. The screening phase is combined with analytical or simplified numerical simulations to estimate full-field performance with reservoir-data-driven segmentation procedures. This paper illustrates the EOR decision-making workflow by use of field case examples from Asia, Canada, Mexico, South America, and the United States. The assets evaluated include reservoir types ranging from oil sands to condensate reservoirs. Different stages of development and information availability are discussed. Results show the advantage of a flexible decision-making workflow that can be adapted to the volume and quality of information by formulating the correct decision problem and concentrating on projects and/or properties with the highest expected economic merit. An interesting aspect of this approach is the combination of geologic and engineering data, minimizing experts' bias and combining technical and financial figures of merit. The proposed method has proved useful to screen and evaluate projects/properties very rapidly, identifying when upside potential exists.
Enhanced-Oil Recovery (EOR) for asset acquisition or rejuvenation involves intertwined decisions. In this sense, EOR operations are tied to a perception of high investments that demand EOR workflows with screening procedures, simulation and detailed economic evaluations. Procedures have been developed over the years to execute EOR evaluation workflows.We propose strategies for EOR evaluation workflows that account for different levels of available information. These procedures have been successfully applied to oil property evaluations and EOR applicability in a variety of oil reservoirs. The methodology relies on conventional and unconventional screening methods, emphasizing identification of analogues to support decision making. The screening phase is combined with analytical or simplified numerical simulations to estimate full-field performance while maintaining rational reservoir segmentation procedures. This paper fully describes the EOR decision-making procedures using field case examples from Asia, Canada, Mexico, South America and the United States. The type of assets evaluated includes a spectrum of reservoir types, from oil sands to light oil reservoirs. Different stages of development and information availability are discussed. Results show the advantage of flexible decision-making frameworks that adapt to the volume and quality of information by formulating the correct decision problem and concentrate on projects and/or properties with apparent economic merit.Our EOR decision-making approaches integrate several evaluation tools, publicly or commercially available, whose combination depends on availability and quality of data. The decision is laid out using decision-analysis tools coupled with economic models and numerical simulation. This allows integrated teams to collaborate in the decision making process without over-analyzing the available data. One interesting aspect is the combination of geologic and engineering data, minimizing experts' bias and combining technical and financial figures of merit rationally. The proposed methodology has proved useful to screen and evaluate projects/properties very rapidly, identifying whether or not upside potential exists.
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