3D geological modeling of the Kasserine Aquifer System, Central Tunisia: New insights into aquifer-geometry and interconnections for a better assessment of groundwater resources

Hassen, Imen; Gibson, Helen; Hamzaoui‐Azaza, Fadoua; Negro, F.; Rachid, Khanfir; Bouhlila, Rachida

doi:10.1016/j.jhydrol.2016.05.034

Cited by 65 publications

(43 citation statements)

References 27 publications

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“…The surface-based geometric modelling is the most commonly used for representing the shape of geological factors, such as topography, geological formations, intrusions, alteration zones, faults and orebodies [70][71][72]. Due to its efficiency in data storage and ability to accommodate irregularly spaced boundary points, the TIN method is increasingly popular for surface-based modelling.…”

Section: Tin and Dsi Methods For Modeling Geological Factorsmentioning

confidence: 99%

Quantitative 3D Association of Geological Factors and Geophysical Fields with Mineralization and Its Significance for Ore Prediction: An Example from Anqing Orefield, China

Qin

Liu

2018

Minerals

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Quantitative 3D spatial association of geological factors and geophysical fields with orebodies is critical for ore prediction. The Anqing orefield, a principal Cu-Fe orefield in China, is closely associated with the Yueshan intrusion. By compiling the data from drilling and tunnelling exploration, Controlled Source Audiofrequency Magnetotelluric (CSAMT) surveying and the computational modelling of magmatic intrusion's cooling process, we constructed models of the Yueshan intrusion, ore-favourable carbonate formation, orebodies, resistivity field and volume strain field. These models are used as evidential factors to analyse their spatial association with mineralization by the weights-of-evidence (WofE) method. The location of orebodies is closely related to the shape of the contact zone of the Yueshan intrusion. The spaces with the distance ≤200 m to the concaves that were selected by minimum principal curvature (|K min | ≥ 0.0025) from contact zones, are very favourable for localization of orebodies. Most orebodies are not located in the spaces of the lowest resistivity, suggesting that the lowest resistivity cannot be used as an indicator for mineralization. The spaces with higher positive volumetric strain have higher positive weights with orebodies, implying that the mineralization is positively related to the positive volumetric strain. The spaces of all evidential factors that had positive correlation with mineralization were integrated to create a 3D prospectivity map by calculating posterior probability. Five areas with higher posterior probability, indicating higher prospectivity potential, are selected as targets for future exploration.

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Section: Tin and Dsi Methods For Modeling Geological Factorsmentioning

confidence: 99%

Quantitative 3D Association of Geological Factors and Geophysical Fields with Mineralization and Its Significance for Ore Prediction: An Example from Anqing Orefield, China

Qin

Liu

2018

Minerals

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“…greyscale relief images) with distinct illumination angles (0-360 • illumination azimuth with 45 • steps constant at a 30 • altitude angle) were calculated, resulting in eight hillshade images and illuminating different parts of the investigation area. On a pixel-based map, the possible strike angle of a line depends on the number of pixels of the raster matrix in which the line is enclosed (Heilbronner and Barrett, 2014). Our approach requires an angular resolution < 10 • , and thus a minimum length of 10 pixels for a specific lineament was necessary to fulfil this criterion.…”

Section: Extrapolation Workflowmentioning

confidence: 99%

“…With increasingly available computer power, 3-D modelling or geometrical visualizations have become widespread, as they can be performed on a desktop computer (e.g. Bistacchi et al, 2008;Caumon et al, 2009;Hassen et al, 2016;Sausse et al, 2010;Stephens et al, 2015). 3-D models widely serve as a basis for subsequent investigations, such as stress modelling or fluid flow modelling (e.g.…”

Section: Introductionmentioning

confidence: 99%

Methods and uncertainty-estimations of 3D structural modelling in crystalline rocks: A case study

Schneeberger¹,

Varga²,

Egli³

et al. 2017

Preprint

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Section: Introductionmentioning

confidence: 99%

“…3-D models widely serve as a basis for subsequent investigations, such as stress modelling or fluid flow modelling (e.g. Hassen et al, 2016;Stephens et al, 2015). Explicit structural modelling can further be subdivided into stochastic and deterministic methods.…”

Section: Introductionmentioning

confidence: 99%

Methods and uncertainty estimations of 3-D structural modelling in crystalline rocks: a case study

et al. 2017

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Abstract. Exhumed basement rocks are often dissected by faults, the latter controlling physical parameters such as rock strength, porosity, or permeability. Knowledge on the threedimensional (3-D) geometry of the fault pattern and its continuation with depth is therefore of paramount importance for applied geology projects (e.g. tunnelling, nuclear waste disposal) in crystalline bedrock. The central Aar massif (Central Switzerland) serves as a study area where we investigate the 3-D geometry of the Alpine fault pattern by means of both surface (fieldwork and remote sensing) and underground ground (mapping of the Grimsel Test Site) information. The fault zone pattern consists of planar steep major faults (kilometre scale) interconnected with secondary relay faults (hectometre scale). Starting with surface data, we present a workflow for structural 3-D modelling of the primary faults based on a comparison of three extrapolation approaches based on (a) field data, (b) Delaunay triangulation, and (c) a best-fitting moment of inertia analysis. The quality of these surface-data-based 3-D models is then tested with respect to the fit of the predictions with the underground appearance of faults. All three extrapolation approaches result in a close fit ( > 10 %) when compared with underground rock laboratory mapping. Subsequently, we performed a statistical interpolation based on Bayesian inference in order to validate and further constrain the uncertainty of the extrapolation approaches. This comparison indicates that fieldwork at the surface is key for accurately constraining the geometry of the fault pattern and enabling a proper extrapolation of major faults towards depth. Considerable uncertainties, however, persist with respect to smaller-sized secondary structures because of their limited spatial extensions and unknown reoccurrence intervals.

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3D geological modeling of the Kasserine Aquifer System, Central Tunisia: New insights into aquifer-geometry and interconnections for a better assessment of groundwater resources

Cited by 65 publications

References 27 publications

Quantitative 3D Association of Geological Factors and Geophysical Fields with Mineralization and Its Significance for Ore Prediction: An Example from Anqing Orefield, China

Quantitative 3D Association of Geological Factors and Geophysical Fields with Mineralization and Its Significance for Ore Prediction: An Example from Anqing Orefield, China

Methods and uncertainty-estimations of 3D structural modelling in crystalline rocks: A case study

Methods and uncertainty estimations of 3-D structural modelling in crystalline rocks: a case study

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