M2 Hydrogéophysique – 3 décembre 2008 GPR response and FDTD modeling to water and fuel infiltration in a sand box experiment by Maksim Bano

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M2 Hydrogéophysique – 3 décembre 2008 GPR response and FDTD modeling to water and fuel infiltration in a sand box experiment by Maksim Bano Ecole et Observatoire des Sciences de la Terre (EOST), 5 Rue René Descartes, Strasbourg FRANCE

M2 Hydrogéophysique – 3 décembre 2008 Outline Introduction Whats GPR? Effect of the frequency and humidity on the GPR data. Presentation of GPR experiment in the lab Experiment set up, data acquisition, comments on the measurements. Water content estimation Comparison with real water volume injected in the box. Conclusions on Water Contents Influence of the pollution (gasoil) on GPR data Data acquisition, results, evolution of the pollution and FDTD modeling Conclusions and Perspectives on Pollution

M2 Hydrogéophysique – 3 décembre 2008 Introduction

GPR - Ground Penetrating Radar Principe of GPR Lap Top Wheel Central Unity Antennae Time (ns) Amplitude

M2 Hydrogéophysique – 3 décembre 2008 Acquisition. Common Mid-Point Data In a Common Mid-Point (CMP) acquisition, antennae separation is increased about some central point. CMP Acquisition M

M2 Hydrogéophysique – 3 décembre MHz Antenna Snake 250 MHz Shielded Antenna Effect of the frequencies used GPR images obtained with 50 (rough-terrain antenna ; snake) and 250 MHz Antennae, Finneidfjord Northern Norway

M2 Hydrogéophysique – 3 décembre 2008 Effect of the Humidity on GPR data The same profile acquired with 500 MHz antennae. a) in May 2006 and b) in October 2008 a) b) Dry soil Humid soil

M2 Hydrogéophysique – 3 décembre 2008 Some important points Water Content (volumetric):Water Content (volumetric): θ w =V w /V total ; θ w =φ.S w Relative dielectric permittivityRelative dielectric permittivity (dielectric constant) = / 0 with 0 the permittivity of the free space. water =81; dry rocks: = 3-5; humid rocks: = Propagation velocity:Propagation velocity: v = c / 1/2 m/ns. c = 0,3 m/ns is the free space velocity.

M2 Hydrogéophysique – 3 décembre 2008 Presentation of GPR experiment in the lab

M2 Hydrogéophysique – 3 décembre 2008 Experiment set up Sand BoxSand box and injection system 2 m 0,98 m Steel pipe PVC Pipes Steel ball Clay cake

M2 Hydrogéophysique – 3 décembre 2008 Data acquisition Plane view of the sand box with measurement grid and different objects. Cross section of the sand box with the projection of the objects. Frequencies used: 900 and 1200 MHz

M2 Hydrogéophysique – 3 décembre 2008 Four data set of measurements Measurements on dry sand Measurements with water level at 72 cm depth (26 cm thick) Measurements with water level at 48 cm depth (48 cm thick) Measurements after draining 72 cm 48 cm

M2 Hydrogéophysique – 3 décembre 2008 Results (1) Steel P2? Steel APVC EPVC P03 P36 P56 TAT0

M2 Hydrogéophysique – 3 décembre 2008 Results (2) Central Profile (P36) with different saturation states Dry sand Water level at 48 cm depth Water level at 72 cm depth After draining

M2 Hydrogéophysique – 3 décembre 2008 Results (3) CMP and constant offset profiles (P1) with different saturation states Water level at 48 cm depth Dry sand

M2 Hydrogéophysique – 3 décembre 2008 Results (4) 3D GPR data sets a) dry sand and b) the water level at 48 cm depth a) b) B

M2 Hydrogéophysique – 3 décembre 2008 Estimation of water contents

M2 Hydrogéophysique – 3 décembre 2008 Relative dielectric Permittivity The determination of the average dielectric constants, for different depth, is performed from the propagation velocities ( =c²/v²) : DepthDry sand v (m/ns) surface0,144,6 38 cm0,144,6 50 cm0,144,6 68 cm0,144,6 bottom0,1166,7 Water level at 48 cm 6,3 6,8 9,0 ? 16

M2 Hydrogéophysique – 3 décembre 2008 Water contents Relationships between water content and relative dielectric permittivity : Topp Relationship Topp Relationship (Topp et al., 1980) = -5,3 x ,92 x ,5 x ,3 x CRIM Relationship CRIM Relationship (Mavko et al., 1998) Hanai-Bruggemann-Sen Relationship Hanai-Bruggemann-Sen Relationship (Hanai, 1968) et

M2 Hydrogéophysique – 3 décembre 2008 Water Quantities The water quantities (in liters) estimated (in whole box) by using the previous relationships Dry sand72 cm48 cmDrainage Dielectric Constant 6,711,4169,8 Water quantity (liter)

M2 Hydrogéophysique – 3 décembre 2008 Variations of water quantities TOPPCRIMHBSInjected Volume V V Estimates of the amounts of water (in liter) injected in the sand box (for different saturation cases) as obtained using the Topp, CRIM and HBS equations. V1 is the amount of water for the data set with the water table at 72 cm depth, minus that of the dry sand case; V2 is the amount of water for the data set with the water table at 48 cm depth, minus the amount of water for the dry sand case.

M2 Hydrogéophysique – 3 décembre 2008 Variations of water quantities Water Quantity (liter) In each case we underestimated the variation in the amount of water in the sand box using GPR, but the final results are very close to the amount of water injected.

M2 Hydrogéophysique – 3 décembre 2008 Conclusions on Water Contents GPR is an effective method to assess and monitor water in the case of a vadose zone. By repeating the same GPR measurements over a controlled vadose zone (sand box experiment), one can compare and calibrate the water content obtained from GPR measurements with the actual water content present in the soil. The water variations are underestimated (by the three relationships) but the final results were very close to the amount of water injected.

M2 Hydrogéophysique – 3 décembre 2008 Influence of a pollution (gasoil) on GPR data

M2 Hydrogéophysique – 3 décembre 2008 Data acquisition 2nd Experiment: After drainage we let the sand box resting (two months) and performed measurements in April 2004 (this state is considered as dry). Measurements with water level at 72 cm depth (26 cm thick, 240 l) in may 2004 We injected 100 l of fuel (gasoil) and repeated measurements in may 2004 and June Injection point of the gasoil

M2 Hydrogéophysique – 3 décembre 2008 Influence of the gasoil (1) Profile T0 before injection Profile T0 after injection The trace 40

M2 Hydrogéophysique – 3 décembre 2008 B Two CMPs acquired after fuel injection. a) CMP16 above the steel ball P1 and b) CMP56 above the steel ball P2. B indicates the reflections from the bottom. Influence of the gasoil (2) B B

M2 Hydrogéophysique – 3 décembre 2008 Laterally extension of the plume pollution Travel time of the reflections from the bottom of the box. a) Before fuel injection b) After fuel injection a) b)

M2 Hydrogéophysique – 3 décembre 2008 Modeling of GPR data by FDTD 0,98 m 2 m 1,40 m Basement of the sand box (air, wood and sand) Sand saturated with water (h=35 cm) Capillary Fringe (h=32 cm) Dry sand, = 4,6 (h=32 cm) Sand saturated with gasoil, = 3,8 Sand mixted with air and gasoil, = 4 Sand mixted with water and gasoil, = 15 Steel pipe Model used for modeling of profile T0 12 days (in May 2004) after fuel injection.

M2 Hydrogéophysique – 3 décembre 2008 Modeling by FDTD Modeled profile T0 Real profile T0

M2 Hydrogéophysique – 3 décembre 2008 Evolution of the pollution in time Profile T0 May 2004 June 2004 R

M2 Hydrogéophysique – 3 décembre 2008 Evolution of the pollution in time profile P56. May 2004 June 2004 Trace 19 R R

M2 Hydrogéophysique – 3 décembre 2008 Modeling of GPR data by FDTD Model used to follow the evolution of the profile T0 45 days after injection 0,98 m 2 m 1,4 m Level of a saturated sand, = 45

M2 Hydrogéophysique – 3 décembre 2008 Modeling by FDTD Profile T0 modeled Profile T0 real R R R

M2 Hydrogéophysique – 3 décembre 2008 Conclusions and Perspectives The GPR data do not show any clear reflections from the plume pollution, however GPR velocities are extremely affected by the presence of the fuel. The laterally extension of the plume pollution in the vadose zone is shown by plotting the travel times of the reflection from the bottom of the sand box. It seems that pore water has been replaced by the fuel through a lateral flow by creating a high saturated zone far from the fuel injection point. The forward FDTD modeling method gave theoretical support to explain the origin of the observed reflections from the contaminated vadose zone. Perspective: Perspective: To follow the lateral flow of the plume, a joint GPR and lateral flow modeling is necessary.

M2 Hydrogéophysique – 3 décembre 2008 Thank you for your attention