Decision analysis applied to the development of petroleum fields must take into account the risk associated to several types of uncertainties. In this phase, the importance of risk associated to the recovery factor may increase significantly and numerical simulation is usually required to model the reservoir yielding high computation effort. The process is complex due to (1) high investments (2) large number of uncertain variables (3) strong dependence of the results with the production strategy definition. Therefore, simplifications are usually required to quantify the impact of uncertainties. In previous works, it was shown the impact of several simplifications in the process to be used in the decision making process after the risk assessment. The risk due to geological uncertainty is then separated from the selection of production strategy and other types of uncertainties. In this work, some results are presented and a discussion is made to show the impact of some simplifications in the selection criteria of the geological representative models before and after the integration of the production strategy optimization. The process is applied in an offshore field in Brazil and the results shows that it is possible to improve the performance and reliability of the risk analysis process with less computational effort.
In petroleum exploration and production, a decision has to be taken considering the risk involved in the process. The first step of the process is to quantify the impact of uncertainties on the performance of petroleum fields. The combination of the uncertainties can be used to quantify the risk related to the decision process.
During the exploration phase, uncertainties related to the volumes in place have great impact. In the appraisal and development phases, as more information is obtained, the importance of the uncertainty on recovery factor becomes significant. The process is even more critical because most of the investments are realized during these phases.
The most important uncertainties are due to the geological model, economic conditions and technological developments. To achieve a more reliable and general methodology, geological uncertainties must be integrated with other types of uncertainties, mainly related to economic scenarios, flexibility in the production strategy definition and technological aspects.
Depending on the complexity of the problem, size of the reservoir and importance of the project, it is not possible to include all uncertain parameters and in order to speed up the process, some auxiliary tools and simplifications are necessary. The key point is then to define with simplifications and assumptions can be made to improve performance without sacrifiyng precision.
The methodology to quantify the impact of simplifications criteria in risk analysis process used in this paper was development by Costa and Schiozer (2003). Some aspects of these simplifications such as gradual combination to define the critical attributes, reduction of levels of discretization for each attribute were used in this paper to quantify the impact of geological uncertainties represented by the concept and the selection of geological representative models (GRM). Other authors such as Ligero et al (2003), Santos and Schiozer (2003), perform risk analysis using numerical simulation, automated tools and simplifications procedure to yield viability of the process.
The o objective of this paper is to present a discussion to show the impact of some simplifications in selection criteria of the GRM before and after the integration of the production strategy optimization.