Calibration of random fields by FFTMA-SA

Lauzon, Dany; Marcotte, Denis

doi:10.1016/j.cageo.2019.03.003

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…(8) for the intersection of the shifted and the original field. This statistic could be computed more efficiently in Fourier space by generalizing the approach presented in Marcotte (1996). As shown in Fig.…”

Section: Simulation Session IImentioning

confidence: 99%

“…(see Deutsch and Journel, 1998;Chilès and Delfiner, 2012;Lantuéjoul, 2013, for details). The common goal of these methods is to ensure that the simulated realizations comply with the additional information available (Lauzon and Marcotte, 2019). The additional information could be observed values of the simulated targets, measurements that are related linearly or nonlinearly to the simulated targets, third-or higher-order statistics (Guthke and Bárdossy, 2017;Bárdossy and Hörning, 2017), etc.…”

Section: Introductionmentioning

confidence: 99%

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Conditional simulation of surface rainfall fields using modified phase annealing

Yan

Bàrdossy

Hörning

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. The accuracy of quantitative precipitation estimation (QPE) over a given region and period is of vital importance across multiple domains and disciplines. However, due to the intricate temporospatial variability and the intermittent nature of precipitation, it is challenging to obtain QPE with adequate accuracy. This paper aims to simulate rainfall fields while honoring both the local constraints imposed by the point-wise rain gauge observations and the global constraints imposed by the field measurements obtained from weather radar. The conditional simulation method employed in this study is modified phase annealing (PA), which is practically an evolution from the traditional simulated annealing (SA). Yet unlike SA, which implements perturbations in the spatial field, PA implements perturbations in Fourier space, making it superior to SA in many respects. PA is developed in two ways. First, taking advantage of the global characteristic of PA, the method is only used to deal with global constraints, and the local ones are handed over to residual kriging. Second, except for the system temperature, the number of perturbed phases is also annealed during the simulation process, making the influence of the perturbation more global at initial phases and decreasing the global impact of the perturbation gradually as the number of perturbed phases decreases. The proposed method is used to simulate the rainfall field for a 30 min event using different scenarios: with and without integrating the uncertainty of the radar-indicated rainfall pattern and with different objective functions.

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Section: Simulation Session IImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conditional simulation of surface rainfall fields using modified phase annealing

Yan

Bàrdossy

Hörning

et al. 2020

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Any permissible autocovariance model may be considered and, given that the random and deterministic components of the algorithm are separated in the spatial, rather than in the wavenumber, domain, local re-simulations of specific areas of the model grid are possible. The latter cannot be done with standard power spectral simulation techniques (e.g., Ikelle, 1993) and has led to the common application of FFT-MA for stochastic modeling and inversion (e.g., Le Ravalec-Dupin et al, 2004;Le Ravalec and Mouche, 2012;Liang and Marcotte, 2016;Yang and Zhu, 2017;Lauzon and Marcotte, 2019).…”

Section: Generation Of Conditional Porosity Realizationsmentioning

confidence: 99%

“…We wish to find conditional realizations of subsurface porosity, generated using the technique described above, whose corresponding synthetic GPR reflection data offer a good fit to the field GPR measurements. To this end, we build on previous work (e.g., Tronicke and Holliger, 2005;Dafflon et al, 2009, Lauzon andMarcotte, 2019) and use SA, a directional Monte-Carlo-type approach, to iteratively perform the optimization. The objective function to be minimized is the simple sum-of-squares error…”

Section: Sa Optimizationmentioning

confidence: 99%

“…Here, 𝑖 denotes the SA iteration number, 𝑁 7 is the total number of vector elements, and constant 𝛾 determines the rate at which the size of the model perturbation decreases as the iterations proceed (Lauzon and Marcotte, 2019). In this way, and similar to the effect of the temperature parameter discussed below, exploration of the model space is encouraged in the beginning of the SA algorithm, whereas exploitation is encouraged towards the end.…”

Section: Sa Optimizationmentioning

confidence: 99%

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Conditional stochastic inversion of common-offset ground-penetrating radar reflection data

Irving

Liu

et al. 2020

SEG Technical Program Expanded Abstracts 2020

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We present a stochastic inversion procedure for common-offset ground-penetrating radar (GPR) reflection measurements. Stochastic realizations of subsurface properties that offer an acceptable fit to GPR data are generated via simulated annealing optimization. The realizations are conditioned to borehole porosity measurements available along the GPR profile, or equivalent measurements of another petrophysical property that can be related to the dielectric permittivity, as well as to geostatistical parameters derived from the borehole logs and the processed GPR image. Validation of our inversion procedure is performed on a pertinent synthetic data set and indicates that the proposed method is capable of reliably recovering strongly heterogeneous porosity structures associated with surficial alluvial aquifers. This finding is largely corroborated through application of the methodology to field measurements from the Boise

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The sequential spectral turning band simulator as an alternative to Gibbs sampler in large truncated- or pluri- Gaussian simulations

Lauzon

Marcotte

2020

Stoch Environ Res Risk Assess

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Calibration of random fields by FFTMA-SA

Cited by 10 publications

References 18 publications

Conditional simulation of surface rainfall fields using modified phase annealing

Conditional simulation of surface rainfall fields using modified phase annealing

Conditional stochastic inversion of common-offset ground-penetrating radar reflection data

The sequential spectral turning band simulator as an alternative to Gibbs sampler in large truncated- or pluri- Gaussian simulations

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