A method for quantifying geological uncertainties in assessing remaining oil targets: a case study from the Glitne Field, North Sea

Abstract

AbstractEvaluating the static volume potential of a field from a single geological reservoir model can be a risky business. Each piece of input data used to build the model carries an uncertainty that is not expressed in a single deterministic realization. In evaluating the technical and economic feasibility of drilling a new production well on the StatoilHydro operated Glitne Field, a quantified assessment of the range in expected volumes was undertaken. A geological uncertainty study was initiated to identify and quantify the input parameters of greatest impact on static volumetric uncertainty in the reservoir model and to identify potential upsides or downsides that would strongly affect the economics of the potential well target areas. For each geological input parameter, a high-case and low-case scenario was established to capture the end members (approximating to P90–P10) in that parameter uncertainty. IRAP RMS was used in combination with an in-house Microsoft Excel macro together with @Risk to produce a quantitative analysis of the uncertainty range in STOIIP and a ranking of the parameters most affecting the uncertainty in this range. This study has contributed to making a better-informed decision for drilling a new production well on the Glitne Field and thus increasing ultimate recovery and field life further. The workflow used has its limitations but this study shows that a geological uncertainty study can be performed relatively simply using only a limited number of software applications. This study also hopes to highlight the importance of having these studies undertaken by company asset teams as part of their reservoir characterization routines.