This paper presents a rigorous statistical methodology for fully optimizing a production scheme development accounting for the main reservoir uncertainties.
Based on the experimental design methodology, this innovative approach allows to model the production recovery as a function of the main reservoir uncertainties, such as petrophysical and production parameters. Note that the method could also be applied to compute probabilistic distribution of the net present field value, as a function of both reservoir and economic uncertainties.
The method was successfully applied on the PUNQ case, which is derived from a North Sea real field case. The optimization of the field development with one platform and six production wells is presented in this paper. The objective was to quantify the impact of the major reservoir uncertainties on the cumulative oil production and to optimize the field development scheme in a risk analysis approach. The uncertainties were mainly on petrophysical data and aquifer strength. The study was performed in the following steps:
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Sensitivity study. The most influential uncertain parameters were identified and their possible interactions with future well locations were highlighted.
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Well location optimization. Some specific experimental designs were used to determine the optimal location of the six production wells, taking into account the influential uncertainties determined previously.
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Risk analysis.
Finally, probabilistic cumulative oil production, corresponding to optimal well locations, was obtained by combining response surface methodology with Monte-Carlo technique.
Results show that this methodology successfully enables to quantify the risk associated with the main reservoir uncertainties and to optimize a production development scheme of an offshore field case study in a risk-prone environment.
Thanks to growing measurement and computational facilities, reservoir modeling is getting more and more complex. Hence more and more prior uncertain parameters can be introduced in reservoir studies. The difficulty is then to identify the ones that are influential on production recovery and on economic field profitability and to quantify their impact.
To deal with those uncertainties, reservoir and production engineers commonly perform many reservoir simulations for different values of the uncertain parameters. This approach gives a BLOCK 1 - - FORUM 4 393
qualitative idea of the influence of each uncertain parameter on the production and economic responses. However this method can quickly become very expensive when the number of unce