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The AAPG/Datapages Combined Publications Database

AAPG Special Volumes


P. Boult and J. Kaldi, eds., 2005, Evaluating fault and cap rock seals: AAPG Hedberg Series, no. 2, p. 125-136.


Copyright copy2005 by The American Association of Petroleum Geologists.

Investigating the Effect of Varying Fault Geometry and Transmissibility on Recovery: Using a New Workflow for Structural Uncertainty Modeling in a Clastic Reservoir

Signe Ottesen,1 Chris Townsend,2 Kjersti Marie Oslashverland1

1Statoil, Stavanger, Norway
2Shell EP Europe Nederlanse Aardolie Maatschappij, Assen, The Netherlands


Thanks to geophysicist Marit Moxnes, who classified the faults. Also, thanks to all the great colleagues in the Reservoir and Uncertainty Modeling project in Statoil-Trondheim, in particular, Alfhild Lien Eide, who did the 3-D facies modeling for this project, Jan Ole Aasen, who set up the experimental design, and Guillaume Lescoffit, whose technical support has been invaluable. Thanks also to Kevin Keogh, who helped us with the written language. Thanks to Rock Deformation Research Group, Leeds University for their enthusiastic analysis of the cored faults, giving input on fault permeability and deformation processes, and to the Norwegian Computing Center, Jon Gjerde, Lars Holden, and Knut Hollund, who designed the HAVANA Structural Uncertainty Modeling software to our specifications and made this study a possibility. Also thanks to Statoil for the permission to publish and to the referees K. Hill, D. Graules, and P. Boult, whose valuable comments made the chapter more attractive to the reader.


Assiduous readers may have noticed that the statistical treatment of tectonic heterogeneities in reservoir simulation is not as rigorous as that of their sedimentary counterparts. Indeed, it is common operational practice to carry only one structural model forward to dynamic reservoir simulation. This means that although the uncertainties attached to variations in sedimentary parameters are commonly addressed, those that are caused by structural heterogeneities are neglected, oversimplified, or underrepresented. The main reasons for this are (1) a lack of appreciation of how structural parameter uncertainties may impact predicted reservoir performance; (2) the need for an efficient methodology; and (3) a lack of an easy-to-use, fully integrated software. A new methodology for investigating the effect of structural uncertainty on reservoir production was tested during this study. The method efficiently assesses structural uncertainties by varying description parameters that define structural horizons and faults and then building multiple realizations of the structural model (i.e., a three-dimensional corner-point grid). Fault properties are modeled by combining fault seal algorithms, and representative transmissibility multipliers are calculated for each realization of the reservoir-simulation grid. The parameters that can be varied include alternative horizon interpretation, velocity models for depth conversion, fault density, fault pattern, fault throw, fault length, fault position, fault thickness, and methodology for fault permeability estimation. This chapter describes the methodology and presents the results from a pilot study of fault uncertainty in a Brent Group reservoir gas field from the Southern Viking Graben in the Norwegian sector of the North Sea. The recovery factor for gas shows an absolute difference of 17.5% (i.e., a variation of 23%) between the very best and very worst cases. The study shows that increasing fault density in the model was the single most important factor in field recovery, and that fault density has an effect on recovery even when the faults did not completely seal. This indicates that subseismic faults, if present, could reduce the recovery factor even further. The choice of fault permeability had the second largest effect on recovery. It must be emphasized that the study focused on investigating the effect of intrareservoir faults, and investigation of the uncertainty in the major block-bounding faults was not included. This study is not a full uncertainty study because no probabilities are attached to the different realizations, but it provides a good basis for such a study.

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