Improved subsurface property prediction in the Netherlands by integrating stratigraphic forward modelling
Salina Borello, E.
Classic geological reservoir characterisation relies on interpolation of high resolution well data with (at best) low resolution seismic derived data. In order to fill the data gap (e.g. in labyrinthine type fluvial deposits) we present a methodology to integrate basin scale information in reservoir scale static models by calibrating output from a Stratigraphic Forward Model (SFM). This project showcases the applicability of the integrated workflow to improve facies and property prediction at different scales. By calibrating the parameterized data from the SFM to independent constraints such as thicknesses from seismic interpretations and well logs the model greatly improve property prediction. Previous studies showed the application to synthetic datasets, this study aims to apply the methodology to the Holocene Rhine-Meuse fluvial deposits in the shallow subsurface of the Netherlands. The extraordinary level of detail in the model of these deposits and the parameterized fluvial sedimentation routine in the SFM used provide an ideal test case for the workflow proposed. The ultimate application of the workflow is intended to improve the geological and property models at greater depth where data coverage is limited. Â© 2016, European Association of Geoscientists and Engineers, EAGE. All rights reserved.
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AGEA - Advisory Group for Economic Affairs
ELSS - Earth, Life and Social Sciences
Geological Survey Netherlands
Stratigraphic forward models
European Association of Geoscientists and Engineers, EAGE
2nd Conference on Forward Modelling of Sedimentary Systems: From Desert to Deep Marine Depositioned Systems, 87-90