Relationships between hydraulic conductivity distribution and synsedimentary faults, Rharb-Mamora basin, Morocco; Hydrogeological, geostatistical and modeling approaches

2004 ◽  
Vol 12 (5) ◽  
pp. 591-600 ◽  
Author(s):  
Lahcen Zouhri ◽  
Christian Gorini ◽  
Benoit Deffontaines ◽  
Jacky Mania
Keyword(s):  
Hydraulic Conductivity ◽  
Conductivity Distribution ◽  
Modeling Approaches

scholarly journals Assessment of the heterogeneity of hydraulic properties in gravelly outwash plains: a regionally scaled sedimentological analysis in the Munich gravel plain, Germany

2020 ◽  
Vol 28 (8) ◽  
pp. 2657-2674
Author(s):  
Markus Theel ◽  
Peter Huggenberger ◽  
Kai Zosseder
Keyword(s):  
Spatial Distribution ◽  
Hydraulic Conductivity ◽  
Large Scale ◽  
Regional Scale ◽  
Pumping Test ◽  
Small Scale ◽  
Significant Heterogeneity ◽  
Conductivity Distribution ◽  
Braided Rivers ◽  
Sedimentary Deposits

AbstractThe favorable overall conditions for the utilization of groundwater in fluvioglacial aquifers are impacted by significant heterogeneity in the hydraulic conductivity, which is related to small-scale facies changes. Knowledge of the spatial distribution of hydraulically relevant hydrofacies types (HF-types), derived by sedimentological analysis, helps to determine the hydraulic conductivity distribution and thus contribute to understanding the hydraulic dynamics in fluvioglacial aquifers. In particular, the HF-type “open framework gravel (OW)”, which occurs with the HF-type “bimodal gravel (BM)” in BM/OW couplings, has an intrinsically high hydraulic conductivity and significantly impacts hydrogeological challenges such as planning excavation-pit drainage or the prognosis of plumes. The present study investigates the properties and spatial occurrence of HF-types in fluvioglacial deposits at regional scale to derive spatial distribution trends of HF-types, by analyzing 12 gravel pits in the Munich gravel plain (southern Germany) as analogues for outwash plains. The results are compared to the reevaluation of 542 pumping tests. Analysis of the HF-types and the pumping test data shows similar small-scale heterogeneities of the hydraulic conductivity, superimposing large-scale trends. High-permeability BM/OW couples and their dependence on recognizable discharge types in the sedimentary deposits explain sharp-bounded small-scale heterogeneities in the hydraulic conductivity distribution from 9.1 × 10−3 to 2.2 × 10−4 m/s. It is also shown that high values of hydraulic conductivity can be interpolated on shorter distance compared to lower values. While the results of the HF-analysis can be transferred to other fluvioglacial settings (e.g. braided rivers), regional trends must be examined with respect to the surrounding topography.

Seismic induced variation of hydraulic conductivity distribution in a large tank

2015 ◽  
Vol 35 ◽  
pp. 78-80
Author(s):  
Nicoló Colombani ◽  
Micól Mastrocicco ◽  
Enzo Salemi
Keyword(s):  
Hydraulic Conductivity ◽  
Conductivity Distribution ◽  
Large Tank ◽  
Induced Variation

Twin Lake Tracer Tests: Setting, methodology, and hydraulic conductivity distribution

1988 ◽  
Vol 24 (10) ◽  
pp. 1585-1612 ◽  
Author(s):  
R. W. D. Killey ◽  
G. L. Moltyaner
Keyword(s):  
Hydraulic Conductivity ◽  
Tracer Tests ◽  
Conductivity Distribution

The Wellenberg K-Model: A Geostatistical Description of Hydraulic Conductivity Distribution in the Host Rock for Site Characterization and Performance Assessment Purposes

1997 ◽  
Vol 506 ◽  
Author(s):  
P. Marschall ◽  
S. Vomvoris ◽  
O. Jaquet ◽  
G.W. Lanyon ◽  
P. Vinard
Keyword(s):  
Hydraulic Conductivity ◽  
Performance Assessment ◽  
Host Rock ◽  
Conditional Simulation ◽  
Fracture Network ◽  
Expected Value ◽  
Simulation Methods ◽  
Network Modelling ◽  
Conductivity Distribution ◽  
And Performance

ABSTRACTThe Wellenberg K-model describes the distribution of the hydraulic conductivity of the host rock at Nagra's proposed site for a LLW/ILW repository. The description takes the form of the expected value of hydraulic conductivity at a location and the uncertainty around this expected value. The development of the K-model is based on geostatistical concepts and, in particular, on kriging and conditional simulation methods. The model is built of cubes with sides of 100 m. Upscaling of the transmissivity profiles at the borehole locations to effective K-values on the 100 m scale is realised by fracture network modelling. The K-model accounts explicitly for the hydraulic conductivities estimated at each borehole. It is consistent with the hydrogeological conceptualization of the host rock and generates realistic hydraulic conductivity distributions with a degree of variability similar to that observed in the data.

scholarly journals Modeling of 3D Isotropic Distribution of Hydraulic Conductivity using Neural Network

2017 ◽  
Author(s):  
Hafidz Mabruri ◽  
Tedy Agung Cahyadi ◽  
Lilik Eko Widodo ◽  
Irwan Iskandar
Keyword(s):  
Neural Network ◽  
Hydraulic Conductivity ◽  
Joint Distribution ◽  
Cross Validation ◽  
Sedimentary Rocks ◽  
Rock Joint ◽  
Three Dimensional ◽  
Flow Modeling ◽  
Conductivity Distribution ◽  
Isotropic Distribution

In most natural condition, hydraulic conductivity distribution is heterogeneous and anisotropic that is affected by local lithological condition, such as rock porosity and rock joint distribution. Therefore, the more porous of lithology the more hydraulic conductivity number it gets. In the previous study, spatial hydraulic conductivity distribution is modeled using Kriging with the aid of SeGMS software. Three dimensional (3D) hydraulic conductivity distributions in sedimentary rocks, which are isotropic and heterogeneous, can be used for groundwater flow modeling. This paper discusses the modeling 3D hydraulic conductivity distribution using Neural Network (NN). The hydraulic conductivity as a target value is trained segmentally from its position in x, y, z coordinate using NN. Numbers of nodes and hidden layers will be affected by complexity of the data. Geological validation and cross validation show that NN can be applied for modeling the spatial hydraulic conductivity distribution

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