Print Email Facebook Twitter Improved lithology prediction in channelized reservoirs by integrating stratigraphic forward modelling: Towards improved model calibration in a case study of the Holocene Rhine-Meuse fluvio-deltaic system Title Improved lithology prediction in channelized reservoirs by integrating stratigraphic forward modelling: Towards improved model calibration in a case study of the Holocene Rhine-Meuse fluvio-deltaic system Author Peter, C. Borello, E. Salina Dalman, R.A.F. Karamitopoulos, P. Busschers, F. Sacchi, Q. Verga, F. Publication year 2020 Abstract Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability simulated with a basin-scale advection-diffusion SFM to a data-rich real-world setting, i.e. the Holocene Rhine-Meuse fluvio-deltaic system in the Netherlands. SFM model calibration to real-world data in general has proven non-trivial. This study focuses on a novel inversion process constrained by the top surface and the sand proportion observed at specific pseudo-wells in the study area. Goodness-of-fit expressed by a new fitness function gives the error calculated as the average of two calibration constraints. Computational efficiency was increased significantly by implementing a new optimization process in two hierarchical steps: a) optimization in terms of sediment load and discharge, which are the most influential parameters having the largest uncertainty and b) optimization with respect to the remaining uncertain parameters, these being sediment transport parameters. The calibration process described allows for the most optimal combination of achieving acceptable levels of goodness-of-fit, feasible runtimes and multiple (non-unique) solutions to obtain synthetic stratigraphic output best matching real-world datasets. By removing model realizations which are geologically unrealistic, calibrated SFM models provide a multiscale stratigraphic framework for reconstructing static models of reservoirs which are consistent with the palaeogeographic layout, basin-fill history and external drivers (e.g. sea level, sediment supply). The static reservoir models that are matched with highest certainty therefore contain the highest geological realism and may be used to improve deep subsurface reservoir or aquifer property prediction. The new methodology was applied to the well-established Holocene Rhine-Meuse dataset, which allows a rigorous testing of the optimization; the calibrated SFM allows investigation of controls of the Holocene development on the sedimentary system. © 2020 Elsevier Ltd Subject Geological Survey Netherlands2015 EnergyBasin modelingFluvio-deltaicInverse algorithmModel calibrationStratigraphic forward modeling To reference this document use: http://resolver.tudelft.nl/uuid:b6ec054c-0224-45cd-b56d-573d03dbdc32 DOI https://doi.org/10.1016/j.cageo.2020.104517 TNO identifier 877429 Publisher Elsevier Ltd ISSN 0098-3004 Source Computers and Geosciences, 141, 1-12 Article number 104517 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.