Abstract

Abstract Well performance prediction is a key Petroleum Engineering task. However, large discrepancies between Petroleum Engineering models and reality still frequently occur; despite the continuous increase in the complexity and predictive quality of reservoir models. To-day's field development decisions are still made with a high level of uncertainty in the underlying data and its economic impact. The degree of data uncertainty is greatest during the exploration stage, but decreases as the reservoir development plan is executed and production data is obtained. Standard, probabilistic workflows have been developed to quantify this uncertainty. These workflows are usually framed by the reservoir scale development plan and end prior to the well's detailed completion design. This is despite the fact that expensive, advanced completions have become common during recent years and the additional investment in such completions can only be justified if it is shown to be paid-back by improved overall project economics which is subject to a significant level of uncertainty. This paper illustrates the quantification of the long-term benefits of advanced completions using the probabilistic approach. It will be shown how choice of the optimum advanced completion design will reduce the impact of geostatistical uncertainty on the production forecast. Geostatistical realisations of a benchmark reservoir model were generated with a suitable level of data uncertainty. The reservoir was developed by a single horizontal well in a fixed location. The well could be equipped with a variety of completions – an Open Hole with a sand control screen or a perforated pipe, Inflow Control Devices (ICDs) and Interval Control Valves (ICVs). The probabilistic (P10, P50, P90) oil-recovery distribution was then used to identify the optimum completion design. This completion not only achieved the largest recovery, but also showed the least uncertainty in this value.

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