--> Abstract: Quantifying Geological Uncertainties for Assessing Remaining Oil Targets: A Case Study from the Glitne Field, North Sea, by Kevin J. Keogh, Frode K. Berg, and Glitne Asset Team; #90039 (2005)

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Quantifying Geological Uncertainties for Assessing Remaining Oil Targets: A Case Study from the Glitne Field, North Sea

Kevin J. Keogh, Frode K. Berg, and Glitne Asset Team
Statoil ASA, Stavanger, Norway

A sixth production well on the Glitne Field would target remaining oil in two areas on the flanks of the field where little data was available to fully understand the uncertainty and potentials risks that are required for making such a decision. A geological sensitivity/uncertainty study, based around the deterministic base-case reservoir model, was initiated to quantify the factors most contributing to the static volumetric uncertainty in the various field segments to identify potential upsides or downsides that will strongly affect the economics of the potential areas.

The study has identified key geological factors that all contribute to the overall uncertainty in estimating static volumes in the defined segments of the field that are not captured in the base case geomodel. For each factor a best-case and worst-case scenario is established to capture the end members (approximating to p90-p10) in that factor uncertainty. IRAP RMS is used in combination with an in-house ProReg Excel macro together with @Risk to produce a full range in possible STOIIP outcomes for each of the geological factors and scenarios, a ranking of the importance of the factors and scenarios and the effects of the interaction of dependent factors.

The results have provided an invaluable quantitative resource that have been used to better asses the feasibility for drilling a sixth production well on the Glitne Field and increasing ultimate recovery and field life further. The workflow used has its, but this study shows that a geological sensitivity study can be set up and performed relatively simply using IRAP RMS. Furthermore, the combination of this tool with a Monte Carlo simulation package gives a simple and quick yet powerful statistical and visual assessment of the potential range in STOIIP and which geological factors are contributing the most to the overall geological uncertainty in the reservoir.

AAPG Search and Discovery Article #90039©2005 AAPG Calgary, Alberta, June 16-19, 2005