Experience with the Quantification of Subsurface Uncertainties

Abstract Now that tools are available for building 3D earth models, and for quantifying uncertainties on parameters associated with the earth model, it is much easier to understand the impact of all subsurface uncertainties on field production. In the last years, we have accumulated a significant experience and know-how addressing this sort of issues in integrated studies. We briefly recall how we address the problems, what tools and methodologies are used for quantifying the joint impact of subsurface uncertainties. We discuss the key points in a study : clearly stressing which operational decision will be supported by the uncertainty study.reformulating the problem in terms of an uncertainty study workflow.listing the key subsurface uncertainties impacting the study.translating these key uncertainties into uncertainties on gross-rock volume, oil-in-place or reserves, using the workflow. Then we illustrate the approach with four field cases. The first example highlights how the joint impact of geometrical, geological and dynamic uncertainties on reserves estimates can be quantified. The second example focusses on the impact of fault sealing on a development decision for an HP-HT field. The third example shows how uncertainty figures can be used to help optimally locate an appraisal well. The last example illustrates how the quantification of structural uncertainties can be used to justify the acquisition or processing of seismic data. We also discuss how new uncertainty quantifications techniques are impacting some of the standard industry workflows. For instance : –scenario approaches can now be run in conjunction with probabilistic approaches.–rather than defining three mini, median and maxi geological models, we prefer to define these models in relation with quantitative parameters of interest, such as OIP and Reserves. We also stress that all our approach merely consists of translating uncertainties on input parameters into uncertainties on parameters of economic interest. The quality of the result obtained depends on the validity of quantified uncertainties on input parameters.