Calibration and validation of reservoir models: the importance of high resolution, quantitative outcrop analogues
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Published:January 01, 2008
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CiteCitation
Richard R. Jones, Kenneth J. W. Mccaffrey, Jonathan Imber, Ruth Wightman, Steven A. F. Smith, Robert E. Holdsworth, Phillip Clegg, Nicola De Paola, David Healy, Robert W. Wilson, 2008. "Calibration and validation of reservoir models: the importance of high resolution, quantitative outcrop analogues", The Future of Geological Modelling in Hydrocarbon Development, A. Robinson, P. Griffiths, J. Price, J. Hegre, A. Muggeridge
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Abstract
Rapidly developing methods of digital acquisition, visualization and analysis allow highly detailed outcrop models to be constructed, and used as analogues to provide quantitative information about sedimentological and structural architectures from reservoir to subseismic scales of observation. Terrestrial laser-scanning (lidar) and high precision Real-Time Kinematic GPS are key survey technologies for data acquisition. 3D visualization facilities are used when analysing the outcrop data. Analysis of laser-scan data involves picking of the point-cloud to derive interpolated stratigraphic and structural surfaces. The resultant data can be used as input for object-based models, or can be cellularized and upscaled for use in...
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The Future of Geological Modelling in Hydrocarbon Development

The 3D geological model is still regarded as one of the newest and most innovative tools for reservoir management purposes. The computer modelling of structures, rock properties and fluid flow in hydrocarbon reservoirs has evolved from a specialist activity to part of the standard desktop toolkit. The application of these techniques has allowed all disciplines of the subsurface team to collaborate in a common workspace. In today’s asset teams, the role of the geological model in hydrocarbon development planning is key and will be for some time ahead.
The challenges that face the geologists and engineers will be to provide more seamless interaction between static and dynamic models. This interaction requires the development of conventional and unconventional modelling algorithms and methodologies in order to provide more risk-assessed scenarios, thus enabling geologists and engineers to better understand and capture inherent uncertainties at each aspect of the geological model’s life.