Use of representative models in the integration of risk analysis and production strategy definition

Decision analysis applied to petroleum field development must include the risk associated to several types of uncertainties. During exploration and appraisal phases, uncertainties related to the amount of fluid in place have a major impact on the decision making process, which is usually conducted to the options: to abandon, to produce, to continue the appraisal procedure or to postpone the production waiting for a better scenario. r, in the transition from the appraisal to the development phase, although the level of uncertainty is smaller, the importance of risk associated to the recovery factor (RF) may increase significantly. In such a phase, several critical decisions are required, mainly related to the definition of the production strategy. The process is complex due to (1) high irreversible investments, (2) large number of uncertain variables, (3) strong dependence of the results associated with the production strategy definition, and (4) necessity of accurate reservoir behavior prediction. complexity factors may, in several cases, disturb reliable techniques to assess risks correctly. Therefore, although some assumptions and simplifications are indispensable in practical situations, it is necessary to define an adequate methodology to identify an optimum balance between accuracy and time consumption in order to obtain an acceptable production strategy. Among all necessary assumptions, one of the most important is the way to integrate geological, economic and technological uncertainties with production strategy definition in order to quantify the impact of uncertainties and assess risk level. ing on the type of problem and objectives of the study, the use of some simplifications may yield incorrect decisions that may lead to suboptimal development. Therefore, the objective of this paper is to present a methodology to integrate risk analysis and production strategy definition considering a special treatment of attributes and use of representative models that are selected to characterize geological uncertainties. The alternatives to reduce the amount of information necessary and to speed up the process are applied in a typical offshore field in Brazil. Supplementary tools such as automation and parallel computing are used to reduce the total time of the procedure where reservoir simulation is necessary in the reservoir performance prediction.