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Improved Subsurface Property Prediction in the Netherlands by Integrating Stratigraphic Forward ModellingNormal access

Authors: R.A.F. Dalman, P. Karamitopoulos, Q. Sacchi, G.J. Weltje, H. Verweij and E. Salina Borello
Event name: Second Conference on Forward Modelling of Sedimentary Systems
Session: Terrestrial Deposits
Publication date: 25 April 2016
DOI: 10.3997/2214-4609.201600372
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 1.45Mb )
Price: € 20

Summary:
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.


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