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Conditioning of Stratigraphic Forward Modelling Using Geostatistics
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, EAGE-HAGI 1st Asia Pacific Meeting on Near Surface Geoscience and Engineering, Apr 2018, Volume 2018, p.1 - 5
Abstract
The combination of Stratigraphic Forward Modelling and geostatistical technique can be used to improve the quality and comprehensiveness of the sedimentary reservoir model then reduce the costly data collection procedures to understand the reservoirs. The Stratigraphic forward modelling (SFM) is a process-based method comprising s realistic complexities and heterogeneities of its subsurface sedimentary architecture and may be applied in generating an enhanced model where limited well and seismic data available. The proposed method in this study is to generate a large SFM-basin scale then identify a field-scale location within this and applying some relevant transformation factor that matches the field conceptual deposition. Grainsize distributions may be inferred from well logs and compared against the grain size model in the SFM. Set of differences or residuals can be analyzed spatially and modeled using geostatistical techniques. Adding the modeled residuals to the SFM grain size will ensure that the hard data is honored. It is expected that more reasonable and defendable model characterization can be generated along with the main co-existed uncertainties and risks that can be captured and analyzed. The proposed methodology will incorporate the best advantage of each technique: process-based method for geological realism and Geostatistic methods for data conditioning