Browsing SINTEF Open by Author "Krogstad, Stein"
Now showing items 1-10 of 10
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Comparison of two different types of reduced graph-based reservoir models: Interwell networks (GPSNet) versus aggregated coarse-grid networks (CGNet)
Lie, Knut-Andreas; Krogstad, Stein (Peer reviewed; Journal article, 2022)Computerized solutions for field management optimization often require reduced-order models to be computationally tractable. The purpose of this paper is to compare two different graph-based approaches for building such ... -
Data-driven modelling with coarse-grid network models
Lie, Knut-Andreas; Krogstad, Stein (Peer reviewed; Journal article, 2023)We propose to use a conventional simulator, formulated on the topology of a coarse volumetric 3D grid, as a data-driven network model that seeks to reproduce observed and predict future well responses. The conceptual ... -
Efficient adjoint-based well-placement optimization using flow diagnostics proxies
Krogstad, Stein; Nilsen, Halvor Møll (Peer reviewed; Journal article, 2021)Model-based optimization of placement and trajectories of wells in petroleum reservoirs by the means of reservoir simulation forecasts is computationally demanding due to the high number of simulations typically required ... -
Efficient flow diagnostics proxies for polymer flooding
Krogstad, Stein; Lie, Knut-Andreas; Nilsen, Halvor Møll; Berg, Carl Fredrik; Kippe, Vegard (Journal article; Peer reviewed, 2017)Flow diagnostics refers to a family of numerical methods that within a few seconds can compute visually intuitive quantities illuminating flow patterns and well connections for full 3D reservoir models. The starting point ... -
Multiscale Mixed Methods on Corner-Point grids: Mimetic versus Mixed Subgrid Solvers
Aarnes, Jørg; Krogstad, Stein; Lie, Knut-Andreas (Research report, 2006)Multiscale simulation is a promising approach to facilitate direct simulation of large and complex grid-models for highly heterogeneous petroleum reservoirs. Unlike traditional simulation approaches based on ... -
The application of flow diagnostics for reservoir management
Møyner, Olav; Krogstad, Stein; Lie, Knut-Andreas (Journal article; Peer reviewed, 2014)Flow diagnostics, as referred to herein, are computational tools derived from controlled numerical flow experiments that yield quantitative information regarding the flow behavior of a reservoir model in settings much ... -
The use of flow diagnostics to rank model ensembles
Watson, Francesca; Krogstad, Stein; Lie, Knut-Andreas (Peer reviewed; Journal article, 2021)Ensembles of geomodels provide an opportunity to investigate a range of parameters and possible operational outcomes for a reservoir. Full-featured dynamic modelling of all ensemble members is often computationally unfeasible, ... -
User Guide to Flow Diagnostics in MRST - Flow Diagnostics Preprocessors for Model Ensembles
Lie, Knut-Andreas; Krogstad, Stein; Watson, Francesca; Borregales Reveron, Manuel Antonio (SINTEF rapport;2020:01131, Research report, 2020)Flow diagnostics are simple quantities that can be derived from basic flow simulations to probe a reservoir model, establish connections and basic volume estimates, and measure heterogeneity in flow paths. This user guide ... -
User Guide to Flow Diagnostics Postprocessing - Simulations in MRST and ECLIPSE Output Format
Lie, Knut-Andreas; Krogstad, Stein; Watson, Francesca (SINTEF rapport;2020:01136, Research report, 2020)Flow diagnostics are simple and controlled numerical flow experiments run to probe a reservoir model, establish connections and basic volume estimates, and measure heterogeneity in flow paths. All these quantities are quick ... -
Using sensitivities and vertical-equilibrium models for parameter estimation of CO2 injection models with application to Sleipner data
Nilsen, Halvor Møll; Krogstad, Stein; Andersen, Odd; Allen, Rebecca; Lie, Knut-Andreas (Journal article; Peer reviewed, 2017)A key part of planning CO2 storage sites is to devise a monitoring strategy with proper modelling support. Herein, we show how a simulation framework that incorporates adjoint-based sensitivities can be combined with ...