Searched for: author%3A%22Heemink%2C+A.%22
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Xiao, C. (author), Lin, H.-X. (author), Leeuwenburgh, O. (author), Heemink, A. (author)
History matching can play a key role in improving geological characterization and reducing the uncertainty of reservoir model predictions. Application of reservoir history matching is restricted by the huge computational cost by amongst others the many runs of the full model. Surrogate models with a reduced complexity are therefore used to...
article 2022
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Vijn, A. (author), Peet, B.J. (author), Schaaphok, M. (author), Lepelaars, E. (author), Heemink, A. (author)
This paper presents a hybrid model to estimate the magnetic behaviour of a ferromagnetic structure. The mathematical-physical model has been developed using the Method of Moments combined with a hysteresis model. The mathematical model was derived by a linearisation of the hysteresis curve. The initial magnetic state of a ferromagnetic object is...
article 2022
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Xiao, C. (author), Leeuwenburgh, O. (author), Lin, H.X. (author), Heemink, A. (author)
A reduced order modeling algorithm for the estimation of space varying parameter patterns in numerical models is proposed. In this approach domain decomposition is applied to construct separate approximations to the numerical model in every subdomain. We introduce a new local parameterization that decouples the computational cost of the...
article 2021
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Jin, J. (author), Segers, A. (author), Lin, H.X. (author), Henzing, B. (author), Wang, X. (author), Heemink, A. (author), Liao, H. (author)
When calibrating simulations of dust clouds, both the intensity and the position are important. Intensity er rors arise mainly from uncertain emission and sedimenta tion strengths, while position errors are attributed either to imperfect emission timing or to uncertainties in the trans port. Though many studies have been conducted on the cal...
article 2021
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Xiao, C. (author), Heemink, A. (author), Lin, H. (author), Leeuwenburgh, O. (author)
Seismic history matching can play a key role in geological characterization and uncertainty quantification. However, challenges related to intensive computational demands and complexity restricts its application in many practical cases. This paper presents a conceptual deep-learning-based framework fully deployed in the popular Pytorch...
conference paper 2020
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Jin, J. (author), Segers, A.J. (author), Liao, H. (author), Heemink, A. (author), Kranenburg, R. (author), Liu, H.X. (author)
Emission inversion using data assimilation fundamentally relies on having the correct assumptions about the emission background error covariance. A perfect covariance accounts for the uncertainty based on prior knowledge and is able to explain differences between model simulations and observations. In practice, emission uncertainties are...
article 2020
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Vijn, A.R.P.J. (author), Lepelaars, E.S.A.M. (author), Dubbeldam, J. (author), van Gijzen, M. (author), Heemink, A. (author)
This paper presents a parameter estimation method to determine the linear behavior of an object constructed of thin plates. Based on the magnetostatic field equations, an integral equation is derived that fully determines the induced magnetization, whenever the spatial magnetic susceptibility distribution is known. This forward problem is used...
article 2019
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Jin, J. (author), Segers, A.J. (author), Heemink, A. (author), Yoshida, M. (author), Han, W. (author), Lin, H.X. (author)
Aerosol optical depths (AODs) from the new Himawari-8 satellite instrument have been assimilated in a dust simulation model over East Asia. This advanced geostationary instrument is capable of monitoring the East Asian dust storms which usually have great spatial and temporal variability. The quality of the data has been verified through a...
article 2019
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Jin, J. (author), xiang Lin, H. (author), Segers, A. (author), Xie, Y. (author), Heemink, A. (author)
Data assimilation algorithms rely on a basic assumption of an unbiased observation error. However, the presence of inconsistent measurements with nontrivial biases or inseparable baselines is unavoidable in practice. Assimilation analysis might diverge from reality since the data assimilation itself cannot distinguish whether the differences...
article 2019
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Xiao, C. (author), Leeuwenburgh, O. (author), Lin, H.X. (author), Heemink, A. (author)
article 2019
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Jin, J. (author), Lin, H.X. (author), Heemink, A. (author), Segers, A. (author)
In previous studies, a number of model-based dust forecasts and early warning systems have been developed for the prevention of environmental impacts due to dusts. However, the accuracy of the model is limited by imperfect identification of dust emissions, in particular by the friction velocity threshold parameterization in the emission process....
article 2018
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Fu, G. (author), Xiang Lin, H. (author), Heemink, A. (author), Lu, S. (author), Segers, A. (author), van Velzen, N. (author), Lu, T. (author), Xu, S. (author)
In this study, we investigate a strategy to accelerate the data assimilation (DA) algorithm. Based on evaluations of the computational time, the analysis step of the assimilation turns out to be the most expensive part. After a study of the characteristics of the ensemble ash state, we propose a mask-state algorithm which records the sparsity...
article 2017
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Lu, S. (author), Heemink, A. (author), Lin, H.X. (author), Segers, A. (author), Fu, G. (author)
Remote sensing, as a powerful tool for monitoring atmospheric phenomena, has been playing an increasingly important role in inverse modeling. Remote sensing instruments measure quantities that often combine several state variables as one. This creates very strong correlations between the state variables that share the same observation variable....
article 2017
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Manders, A.M.M. (author), Builtjes, P.J.H. (author), Curier, L. (author), Denier van der Gon, H.A.C. (author), Hendriks, C. (author), Jonkers, S. (author), Kranenburg, R. (author), Kuenen, J.J.P. (author), Segers, A.J. (author), Timmermans, R.M.A. (author), Visschedijk, A.J.H. (author), Wichink Kruit, R.J. (author), van Pul, W.A.J. (author), Sauter, F.J. (author), van der Swaluw, E. (author), Swart, D.P.J. (author), Douros, J. (author), Eskes, H. (author), van Meijgaard, E. (author), van Ulft, B. (author), van Velthoven, P. (author), Banzhaf, S. (author), Mues, A.C. (author), Stern, R. (author), Fu, G. (author), Lu, S. (author), Heemink, A. (author), van Velzen, N. (author), Schaap, M. (author)
The development and application of chemistry transpor tmodels has a long tradition. Within the Netherlands the LOTOS–EUROS model has been developed by a consortium of institutes, after combining its independently developed predecessors in 2005. Recently, version 2.0 of the model was released as an open-source version. This paper presents the...
article 2017
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Fu, G. (author), Prata, F. (author), Xiang Lin, H. (author), Heemink, A. (author), Segers, A. (author), Lu, S. (author)
Using data assimilation (DA) to improve model forecast accuracy is a powerful approach that requires available observations. Infrared satellite measurements of volcanic ash mass loadings are often used as input observations for the assimilation scheme. However, because these primary satellite-retrieved data are often two-dimensional (2-D) and...
article 2017
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Lu, S. (author), Lin, H.X. (author), Heemink, A. (author), Segers, A. (author), . Fu, G. (author)
In this paper, we reconstruct the vertical profile of volcanic ash emissions by assimilating satellite data and ground-based observations using a modified trajectory-based 4D-Var (Trj4DVar) approach. In our previous work, we found that the lack of vertical resolution in satellite ash column data can result in a poor estimation of the injection...
article 2016
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Fu, G. (author), Heemink, A. (author), Lu, S. (author), Segers, A. (author), Weber, K. (author), Lin, H.X. (author)
The forecast accuracy of distal volcanic ash clouds is important for providing valid aviation advice during volcanic ash eruption. However, because the distal part of volcanic ash plume is far from the volcano, the influence of eruption information on this part becomes rather indirect and uncertain, resulting in inaccurate volcanic ash forecasts...
article 2016
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Sebacher, B. (author), Hanea, R.G. (author), Heemink, A. (author)
In the past years, many applications of historymatching methods in general and ensemble Kalman filter in particular have been proposed, especially in order to estimate fields that provide uncertainty in the stochastic process defined by the dynamical system of hydrocarbon recovery. Such fields can be permeability fields or porosity fields, but...
article 2013
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TNO Bouw en Ondergrond (author), Lawniczak, W. (author), Hanea, R.G. (author), Heemink, A. (author), McLaughlin, D. (author)
Reservoir management requires periodic updates of the simulation models using the production data available over time. Traditionally, validation of reservoir models with production data is done using a history matching process. Uncertainties in the data, as well as in the model, lead to a nonunique history matching inverse problem. It has been...
article 2009
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