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Summary Developed oil fields often present challenges for further exploitation owing to existing production facilities. Frequently with a long production history, new wells cannot be drilled as freely when compared to earlier phases. As more knowledge is acquired along the course of field development, there is less room for changes, with a potential end point for data acquisition. This paper is based on a workflow originally conceived for quantifying the chance of success (CoS) of a four-dimensional (4D) seismic project for an oil field at the beginning of the development phase, when a complete infrastructure must be defined. Here, we apply this workflow to a developed oil field combined with an assisted production strategy optimization process proposed to optimize large-scale problems using a multilevel approach, allowing to estimate CoS, within a global and integrated decision analysis framework The optimization process is composed of steps to define and optimize decision variables of an oil production strategy, involving a given set of uncertain reservoir models, within a viable number of simulation runs through the use of automatic methods and reservoir engineering analyses. The information provided by 4D seismic data can be used to identify the most-likely reservoir model and, combined with numerical reservoir simulation, to optimize the control and field revitalization variables of the production strategy. This work compares the chance of success and the expected value of information (EVoI) methodologies. We use representative models selected from an ensemble of reservoir models based on cross plots of technical and economic objective functions, the associated risk curves and the probability distribution function of the uncertain attributes. The use of representative models makes the production strategy optimization and CoS and EVOI quantification processes practical, considering all the uncertainties and decision variables involved in the same run, where limiting computational costs is essential. We also analyze the influence of the number of representative models on these estimates. The results of this study showed that, although this oil field presented limited room for changes because of the late stage of development, 4D seismic information effectively impacted decisions regarding production strategy. Besides, our methodology showed that the expected economic gains from improved decisions are higher than the acquisition and processing costs related to information acquisition. |
