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Hybrid Iterative Ensemble Smoother for History Matching of Hierarchical Models
The choice of a prior model can have a large impact on the ability to assimilate data. In standard applications of ensemble-based data assimilation,...
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Data assimilation with soft constraints (DASC) through a generalized iterative ensemble smoother
This work investigates an ensemble-based workflow to simultaneously handle generic, nonlinear equality and inequality constraints in reservoir data...
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Calibration and uncertainty analysis of integrated SWAT-MODFLOW model based on iterative ensemble smoother method for watershed scale river-aquifer interactions assessment
River-aquifer interaction is a key component of the hydrological cycle that affects water resources and quality. Recently, the application of...
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Importance Weighting in Hybrid Iterative Ensemble Smoothers for Data Assimilation
Because it is generally impossible to completely characterize the uncertainty in complex model variables after assimilation of data, it is common to...
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Marginalized iterative ensemble smoothers for data assimilation
Data assimilation is an important tool in many geophysical applications. One of many key elements of data assimilation algorithms is the measurement...
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Experimental sandbox tracer tests to characterize a two-facies aquifer via an ensemble smoother
Estimating aquifer properties and their spatial variability is the most challenging part of groundwater flow and transport simulations. In this work,...
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Batch seismic inversion using the iterative ensemble Kalman smoother
An ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main...
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Constrained iterative ensemble smoother for multi solution search assisted history matching
History matching algorithms usually converge to the most prominent solution in the hypercube of parameter space defined by bound values. Here, we...
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Flexible iterative ensemble smoother for calibration of perfect and imperfect models
Iterative ensemble smoothers have been widely used for calibrating simulators of various physical systems due to the relatively low computational...
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Evaluating parameter inversion efficiency in Heterogeneous Groundwater models using Karhunen-Loève expansion: a comparative study of genetic algorithm, ensemble smoother, and MCMC
Groundwater modeling is essential for effective water resource management. However, the heterogeneous distribution of hydrogeological parameters,...
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Improving Numerical Dispersion Modelling in Built Environments with Data Assimilation Using the Iterative Ensemble Kalman Smoother
Air-pollution modelling at the local scale requires accurate meteorological inputs such as from the velocity field. These meteorological fields are...
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Iterative multilevel assimilation of inverted seismic data
In ensemble-based data assimilation (DA), the ensemble size is usually limited to around one hundred. Straightforward application of ensemble-based...
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Ensemble Smoother with Multiple Data Assimilation as a Tool for Curve Fitting and Parameter Uncertainty Characterization: Example Applications to Fit Nonlinear Sorption Isotherms
The ensemble smoother with multiple data assimilation (ES-MDA) coupled to a normal-score transformation is used to fit a Langmuir isotherm curve to...
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Ensemble-based history matching of the Edvard Grieg field using 4D seismic data
The Edvard Grieg field is a highly complex and heterogeneous reservoir with an extensive fault structure and a mixture of sandstone, conglomerate,...
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Recent developments combining ensemble smoother and deep generative networks for facies history matching
Ensemble smoothers are among the most successful and efficient techniques currently available for history matching. However, because these methods...
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Novel iterative ensemble smoothers derived from a class of generalized cost functions
Iterative ensemble smoothers (IES) are among the state-of-the-art approaches to solving history matching problems. From an optimization-theoretic...
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Iterative geostatistical electrical resistivity tomography inversion
Electrical resistivity tomography (ERT) is a geophysical method used to create an image of the subsurface due to its sensitivity to porosity, water...
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Data-space inversion with ensemble smoother
Reservoir engineers use large-scale numerical models to predict the production performance in oil and gas fields. However, these models are...
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Low-Rank Ensemble Methods
This chapter willError covariance matrix introduce another approximation where we represent all state error covariances using a finite ensemble of...
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Deterministic ensemble Kalman filter based on two localization techniques for mitigating sampling errors with a quasi-geostrophic model
In the ensemble Kalman filter (EnKF) framework for data assimilation, a limited ensemble size results in a spurious sampling error and...
