SGEMS-UQ: An uncertainty quantification toolkit for SGEMS

Li, Lewis; Boucher, Alexandre; Caers, Jef

doi:10.1016/j.cageo.2013.09.009

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…Pirot et al, 2019) or to reduce the dimensionality of the sampling space, from a high dimensional geological space to a low dimensional latent space (Lochbühler et al, 2013). Although some indicators have been used or developed for specific studies or softwares (Li et al, 2014), to the best of our knowledge, no independent uncertainty analysis tool applicable to both discrete and continuous property fields, combining local and global indicators is available to practitioners.…”

Section: Introductionmentioning

confidence: 99%

loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification

et al. 2022

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Abstract. To support the needs of practitioners regarding 3D geological modelling and uncertainty quantification in the field, in particular from the mining industry, we propose a Python package called loopUI-0.1 that provides a set of local and global indicators to measure uncertainty and features dissimilarities among an ensemble of voxet models. Results are presented of a survey launched among practitioners in the mineral industry, enquiring about their modelling and uncertainty quantification practice and needs. It reveals that practitioners acknowledge the importance of uncertainty quantification even if they do not perform it. A total of four main factors preventing practitioners performing uncertainty quantification were identified: a lack of data uncertainty quantification, (computing) time requirement to generate one model, poor tracking of assumptions and interpretations and relative complexity of uncertainty quantification. The paper reviews and proposes solutions to alleviate these issues. Elements of an answer to these problems are already provided in the special issue hosting this paper and more are expected to come.

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Section: Introductionmentioning

confidence: 99%

loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Pirot et al, 2019) or to reduce the dimensionality of the sampling space, from a high dimensional geological space to a low dimensional latent space (Lochbühler et al, 2013). Though some indicators have been used or developed for specific studies or softwares (Li et al, 2014), to the best of our knowledge, no independent uncertainty analysis tool applicable to both discrete and continuous property fields, combining local and global indicators is available to practitioners.…”

Section: Introductionmentioning

confidence: 99%

loopUI-0.1: uncertainty indicators to support needs and practices in 3D geological modelling uncertainty quantification

Pirot

Joshi

Giraud

et al. 2022

Preprint

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Abstract. To support the needs of practitioners regarding 3D geological modelling and uncertainty quantification in the field, in particular from the mining industry, we propose a Python package called loopUI-0.1 that provides a set of local and global indicators to measure uncertainty and features dissimilarities among an ensemble of voxet models. Results are presented of a survey launched among practitioners in the mineral industry, enquiring about their modelling and uncertainty quantification practice and needs. It reveals that practitioners acknowledge the importance of uncertainty quantification even if they do not perform it. Four main factors preventing practitioners to perform uncertainty quantification were identified: lack of data uncertainty quantification, (computing) time requirement to generate one model, poor tracking of assumptions and interpretations, relative complexity of uncertainty quantification. The paper reviews and proposes solutions to alleviate these issues. Elements of an answer to these problems are already provided in the special issue hosting this paper and more are expected to come.

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“…As a basis for constructing the surfaces of the top and the base of each model layer, a geological model created in the SGeMS software [31,32] was used. The filling of the 3D geological model was based on the information on 1,504 wells from the database obtained in the course of engineering geological and hydrogeological surveys in the study area.…”

mentioning

confidence: 99%

Forecast of radionuclide migration in groundwater of the zone affected by construction drainage at the Leningrad NPP-2

Erzova

Rumynin

Nikulenkov

et al. 2022

PMI

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The distribution of natural (at the level of global background) and technogenic radionuclides in groundwater of the industrial zone in Sosnovy Bor town, where several nuclear power facilities are operating, was analyzed. The main technogenic radionuclides recorded in groundwater samples are cesium (137Cs), strontium (90Sr), and tritium isotopes. The first two aquifers from the surface are subject to contamination: the Quaternary and the upper zone of the Lomonosov aquifer. Based on extensive material on the engineering and geological studies of the work area, a 3D geological model and hydrodynamic and geomigration models of the industrial zone were constructed. By means of modeling, the extent and nature of changes in hydrogeological conditions of area resulting from the construction and operational drainage of the new stage of the Leningrad Nuclear Power Plant (LNPP-2) were determined. The “historical” halo of radioactive contamination of groundwater forming (1970-1990) at the site adjacent to the NPP, where the storage facility of low- and medium-level radioactive waste is located, falls into the zone of influence. Interpretation of monitoring data allowed obtaining the migration parameters for predictive estimates. Modeling has shown that during the time of the LNPP-2 operation there is was no intake of contaminated water by the drainage system of the new power plant.

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SGEMS-UQ: An uncertainty quantification toolkit for SGEMS

Cited by 6 publications

References 15 publications

loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification

loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification

loopUI-0.1: uncertainty indicators to support needs and practices in 3D geological modelling uncertainty quantification

Forecast of radionuclide migration in groundwater of the zone affected by construction drainage at the Leningrad NPP-2

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