Application of multiple-point geostatistics on modelling groundwater flow and transport in the Brussels Sands

Transcription

1 Application of multiple-point geostatistics on modelling groundwater flow and transport in the Brussels Sands Marijke Huysmans (1) and Alain Dassargues (1,2) (1) Earth and Environmental Sciences, K.U.Leuven, Belgium (2) Université de Liège, Belgium Problem formulation 3 m 1 m 16 m Effect of smallscale sedimentary structures on groundwater flow and transport? 1

2 Methodology Geological heterogeneity of the Brussels Sands Field permeability measurements Multiple-point geostatistics Training image construction Multiple-point geostatistical facies Comparison to variogram based simulations Intrafacies permeability simulation Groundwater flow and transport model Geological heterogeneity Brussels Sands Houthuys (199) Study about sedimentological structures and depositional environment of Brussels Sands field studies and descriptions of approximately 9 outcrops and hundreds of boreholes Filling of rapidly shifting channels by tidal sandbars migrating to the north => 3 scales of geological heterogeneity: Large-scale ( - km scale) related to the geometry and dimensions of the sand body Meso-scale ( 1 m to km scale) related to spatial trends in grain size and permeability within the sand body due to vertical and lateral sedimentary facies changes Small-scale ( 1 mm to 1 m scale) mainly related to crossbedding 2

3 Geological heterogeneity Brussels Sands Small-scale geological heterogeneity Within-facies sedimentary structures Tidal deposit: Important grain size variations Cross-beds ( 1 m thick) Clay-rich bottomsets ( 1 cm thick) with lateral thickness variations ~ neap/spring cycles Foreset lamination thickness of. to 3 cm dip 2-3 to the NNE Asymptotic at base Fine silt and clay-rich mud drapes ~ turning of the tide sometimes wedge out in the upper part of the foresets lateral thickness variations ~ neap/spring cycles not always laterally continuous perpendicular to the flow direction 3 m 1 m Geological heterogeneity Brussels Sands 12 1 Small-scale geological heterogeneity Frequency Bottomset thickness (m) More 11 m Frequency More Foreset bed thickness (m) Frequency Max foreset dip ( ) 36 More 3

4 Geological heterogeneity Brussels Sands Field observations Pictures and geological sketches Subjective distinction between clay-rich bottomsets/distinct mud drapes and sandy zones Determination of lamination angle 16 m Permeability of the Brussels Sands Literature review Pumping tests and piezometer tests: K =.4-29 m/d E-6 3E-4 m/s => k 67 4, mdarcy Field measurements Portable air permeameter: TinyPerm II (NER) Measurement volume = hemisphere with radius of 1 mm 27 air permeability measurements in Brussels Sands 4

5 Permeability of the Brussels Sands 1 m Clay Sand 1 m 1 m Permeability of the Brussels Sands Variogram map of permeability (md) 6 cm 6 cm

6 Permeability of the Brussels Sands 3% 3% 2% 2% 1% 1% % Combination of all 27 air permeability data: Combined histogram: clay rich zones cross-bedded sands y( h ) y( h ) Combined variograms: 4.E+ 3.E+ 3.E+ 2.E+ 2.E+ 1.E+ 1.E+.E+7.E h (m) 3.E+ 2.E+ 2.E+ 1.E+ 1.E+.E+7 Lamina parallel variogram of sand permeability Lamina perpendicular variogram of sand permeability Lamina parallel variogram of clay permeability Lamina perpendicular variogram of clay permeability % E h (m) Air permeability (md) Training images construction Clay/sand training images N4 E N4 W Sand Clay 3 m 6

7 Multiple-point facies and intrafacies permeability simulation 3 example facies out of 1 3 example hydraulic conductivity out of 1 Comparison to variogrambased SGSIM simulations 7

8 Groundwater flow and transport model 1 m by 1 m small-scale and short-term 2D vertical model small grid cells of cm by cm Hydraulic conductivity from Constant head boundary conditions average horizontal gradient = 1 m/km average vertical hydraulic gradient = m/km hypothetical contaminant source Visual Modflow/MT3DMS run 1 times Contaminant source (flow rate = 1 l/day, conc = 1 mg/l Results Calculated hydraulic head contours and contaminant concentrations after 3 days Different plume characteristics for different

9 Results Histograms of output variables Number of simulations (-) SNESIM SGSIM Maximum depth w ith c=1 mg/l (m) Number of simulations (-) SNESIM SGSIM Number of simulations (-) SNESIM SGSIM Maximum simulated concentration at t=3 days (mg/l) Maximum x with c=1 mg/l (m) Conclusions Application of multiple-point geostatistics on real aquifer Training image construction based on geological and hydrogeological outcrop data Significant effect of small-scale sedimentary structures on transport of contaminants 9