Transcript MODFLOW - Rice University

Soil Vapor Extraction
Contamination in the Vadose Zone
•
•
The vadose (unsaturated) zone acts as a “buffer zone” for protecting the quality
of the underlying ground water.
When contaminated, however, it acts as a source zone for ground water
pollutants and gaseous emissions.
Tank
Vadose Zone
Residual
Capillary Fringe
Vapors
Separate Fluid Phase
Water Table
Dissolved in Ground Water
Ground Water Flow
Saturated Zone
Soil Vapor Extraction (SVE)
•
•
•
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Targets the removals
of VOCs from the
vadose zone by
volatilization
Shown to be effective
at removing NAPL,
aqueous, and sorbed
phases
Encourages aerobic
biodegradation
Proven technology
with some design
guidance (rule-ofthumb).
Pressure
Gauge
Vapor/ Vacuum
Flow Liquid Pump Treatment
Meter Separator
Unit
To GW Treatment
Monit. GW
Well Well
SVE
Well
airflow
pat hs
Groundwater
Case Study: JP-4 Spill
at Hill AFB, Utah
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A JP-4 fuel spill site at Hill, AFB , Utah was selected to be modeled using
VENT3D.
•
This is probably the most comprehensive data set collected from a field
application of SVE.
•
Several pilot studies, and a full scale soil vapor extraction (SVE) operation
under a variety of flow conditions were conducted at the site.
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Data for gas concentrations, contaminant concentrations, mass removals and
vacuum pre- and during-operation were provided by the researchers.
VENT3D Description
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•
VENT3D solves the 3-D vapor phase advection-dispersion equation for a mixture of
compounds. It computes the 4-phase distribution for each compound between vapor
moving periods, assuming equilibrium partitioning between phases.
The model domain is discretized into blocks.
parameters common to domain
contaminant conmposition, foc,x, y,  b.
parameters unique to cell volume
permeability, contaminant concentration,
injected air humidity, Qi,j,k.
parameters unique to layer
permeability anisotropy,
z, porosity,
moisture content.
Boundary Conditions
- ground surface open or closed to atmosphere.
- lateral boundaries at amospheric pressure.
- lateral boundaries: no flux or known flux
-bottom surface represents water table:no flux.
Qi,j,k
z,k
y ,j
x,i
layers
1000
VENT3D Flow Algorithm
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The model solves the 3-D steady-state gas flow equation using finitedifference.
2
2
2


 

P


P


P
2 WRT



k



ky

kz

x
x  x  y  y  z  z  dxdy dz MW
v x, y, z
k x, y, zPx, y, z

 x, y,z
 
k  k  
n 
3
*
where k= soil vapor permeability tensor (L2), P= soil-gas pressure (M/LT2),  = soil-gas viscosity (M/LT),W=
vapor mass flux source/sink (M/T), R= universal gas constant (ML2/T2 mole oK), T= temperature (oK), MW=
molecular weight of soil-gas (M/mole), k*= intrinsic permeability (L2),
= air filled porosity (dimensionless), v= interblock gas flow (L/T).
VENT3D Transport Algorithm
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Knowing the 3-dimensional interblock flows, the 3-D advection-dispersion
equation is solved by finite-difference for each chemical compound.
Mn
 Fn    DnCn  qCn 
t
qx qy
Dn  Dm I   xy z
q
Dm  Do
 3.3
n
2
where Mn = total molar concentration of compound n in mixture (mole/L3), Cn =molar concentration of compound
n (mole/L3), q = vapor discharge vector (L/T), Fn=volumetric molar loss/addition rate of compound n (mole/L3T),
Dn= the dispersion tensor (L2/T) , Dm= molecular diffusion coefficient (L2/T), Do= free air diffusion coefficient
(L2/T), I = identity vector,  xyz= vapor dispersivity values (L), qx,qy= vapor flow in x,y,z, direction (L/T), q =
magnitude of the discharge vector (L/T).
Phase Partitioning
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Equilibrium partitioning is assumed between the different phases for each compound.
Equilibrium is re-calculated at the end of each time step. The total molar concentration of
each compound is expressed as a function of the vapor concentration and the sum of the
molar concentrations in the 4 phases:
 MHC RT MH2 O RT Kdn  RT H2 O 
Mn  Cn  


V
V
V
Pn
 n Pn
 n Pn MWH2 O 


#compounds

n1
Cn RT
1
v
Pn
where MHC=molar concentration of NAPL phase in soil (mole/L3), Pv= compound vapor pressure (atm), MH2O=
molar concentration of dissolved phase (mole/L3),n=activity coefficient of compound in water (dimensionless), Kdn=
distribution coefficient of compound (dimensionless), = soil density (M/L3), MWH2O= molecular weight of water (18
gm/mole), H2O= soil moisture flag=1 if present, 0 if not present.
Site History
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27,000 gallons (76,500 kg) of JP-4 jet fuel spilled in January 1985.
Contaminated area west of spill area = 160 ft * 120 ft *50 ft.
A field study of soil venting was performed at the site in 1988-1989.
Pilot & Full-Scale Tests
Date
Activity
Pilot Tes ts
January 18, 1988
Extraction from Vent 7 at 62 ft3 /min for 2 hours
January 19,1988
Extraction from Vent7 at 127 ft3 /min for 2 hours
Extraction from Vent7 at 202 ft3 /min for 2 hours
January 20,1988
Extraction from Vent7 at 172 ft3 /min for 4 hours
Extraction from Vent7 at 209 ft3 /min for 8 hours
Full-s cale Operation
December 18-March 11, 1988
Extraction from Vent 7 at 250 ft3 /min with
occasional system shutdown
March 11-April 2, 1989
Extraction from Vent 10 at 250 ft3 /min
April 2-April 22, 1989
Extraction from Vent 9,10,11 at 350 ft3 /min.
Performed several flow tests
May 15-May 26, 1989
Extraction from Vent 5,6,7,8,9,10,11 at 500
ft3 /min, followed by 14 days shutdown
June 10-August 15, 1989
Extraction from Vent 5,6,7,8,9,10,11 at
918 ft3 /min
August 15-October 7, 1989
Extraction from Vent 9,11 at 650 ft3 /min.
Heat injection from Vent 10 at 93 ft3 /min
VENT3D Vertical Layers
g ro un d s urface
0 ft
3 .7 5 ft
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The contaminated
soil volume is
divided into 11
layers, each
having different
initial contaminant
concentrations in
soil.
lay er 11
3 .7 5 ft
3 ft
lay er 10
6 .7 5 ft
3 ft
lay er 9
3 ft
lay er 8
4 ft
lay er 7
5 ft
lay er 6
5 ft
lay er 5
5 ft
lay er 4
5 ft
la ye r 3
5 ft
lay er 2
8 .2 5ft
lay er 1
s oi l
s amp les
9 .7 5 ft
1 2.75 ft
1 6.75 ft
2 1.75 ft
2 6.75 ft
3 1.75 ft
3 6.75 ft
4 1.75 ft
5 0 ft
VENT3D Horizontal Grid
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Each layer is
divided into a 16 *
12 orthogonal
grid, each grid cell
is 10 ft wide *10
ft. long. The grid
shows the
subareas to which
the vertical vent
area was divided.
Each subarea is
presented by a soil
boring V1,
V2........V15.
JP-4 Composition
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Reported and estimated standard weight fractions for JP-4 components.
W ei ght Fracti ons from O RNL GC Analysis
# Carbon Atoms
W ei ght Fracti on %
C5-C6
0
C6-C7
0
C7-C8
0.166
C8-C9
0.223
C9-C10
0.16
C10-C 11
0.116
C11-C 12
0.131
C12-C 13
0.105
C13-C 14
0.053
C14-C 15
0.029
C15-C 16
0.016
C16-C 17
0.001
JP-4 Mass Fractions Estimate d from G C
Analysis at Southe rn Pe trole um Lab
#Carbon Atoms
mass fracti on %
C5
0.005
C6
0.05
C7
0.15
C8
0.225
C9
0.145
C10
0.11
C11
0.12
C12+C13
0.16
C14
0.025
C15
0.01
Determining Site Permeability
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The horizontal and vertical permeabilities at the site were estimated using
GASSOLVE, a computer program developed by Falta (1996).
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GASSOLVE uses analytical solutions to the steady-state gas flow equation for
different boundary and initial conditions.
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The permeability is found by fitting the analytical solution to pressure data
collected from air permeability tests.
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GASSOLVE adjusts the permeability until it reaches a minimum residual sum
of squares between the calculated and observed pressures.
GASSOLVE Results
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Pressure data from four pilot tests were used by GASSOLVE to determine the
air permeability of the formation.
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Results indicated:
–
–
horizontal permeability = 40 darcys.
vertical permeability = 1 darcy.
hl permeability
vl permeability
Res. Sum Sq.
Open ground Surface
test1
test2
test3
35
40
42.7
1
1.3
1.1
2.10E-05
4.70E-05
7.10E-05
test4
42.4
1.02
1.00E-04
Flow Calibration &Validation
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Five pilot tests were simulated by VENT3D using GASSOLVE estimated
permeabilities.
Three of the full-scale operation flow tests were simulated by VENT3D.
20
Calculated Vacuum (in H2O)
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15
10
5
pilot tests
flow tests
0
0
5
10
15
20
Measured Vacuum (in H2O)
Vacuum Adjustment
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VENT3D calculated pressure was adjusted at extraction wells using the
equation adapted from Anderson and Woessner, 1992.
Pw 

Q g
r 
2
Pi, j  w
ln e 
k
rw 

where Pw is the well pressure, P i,j is the calculated pressure, Qw is the pumping/injection rate, k is the
permeability,  is the fluid viscosity,  is the fluid density, g is the gravitational acceleration, re is the
effective well block radius and rw is the well radius.
Vacuum Adjustment Results
Q (m3/s ec)
Obs erved Vacuum VEN T3D Vacuum
(in H2O)
(in H2O)
Adjus ted Vacuum
(in H2O)
Pilot Tests
0. 029
5.4
4.0
4.1
0. 059
10.9
8.1
8.4
0. 080
16.0
11.2
11.6
0. 094
20.0
13.1
13.6
Flow Tests
0. 029
8.3
4.4
4.5
0. 080
22.0
14.7
15.1
0. 080
22.5
14.9
15.2
0. 074
15.7
13.3
13.6
0. 0505
16.0
11.6
11.8
0. 048
16.5
9.9
10.1
Transport Calibration
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The total initial contaminant mass was adjusted until the measured mass
removals from the pilot tests and calculated mass removals from VENT3D
matched within less than 20% error.
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The initial total mass was estimated to be as high as 76,000 kg based on the
spill volume.
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Five pilot tests were simulated and mass removals were compared.
Transport Calibration Using Pilot
Tests

Data from pilot tests were not successful in the calibration step due to some
discrepancy in reported data.
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Transport Calibration Using Full
Scale Operation
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Mass removals recorded at the beginning of the full-scale operation were used to
verify the calibration process.
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Transport Validation
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Mass removals from simulations representing the whole operation were
compared with the measured values.
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Initial & Final Soil and Gas
Concentrations
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Average Extraction Rates

To evaluate whether the detail of the flow history was necessary,the
25 flow tests conducted during the full-scale study were represented
by one simulation.
Q (ft3/s)
500
different Qs for flow tests
400
Q average
300
200
100
0
Average Extraction Rates
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VENT3D estimated a 2% difference in removals.
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Predicting System Behavior
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VENT3D was used to predict the extent of contamination if SVE was not
carried out at the site.
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Predicting System Behavior
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Conclusions
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The design and performance of remediation systems can be greatly improved
through the use of mathematical models.
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VENT3D proved successful in representing site characteristics with respect to
subsurface air flow and for simulating the performance of a vapor extraction
study conducted at a JP-4 jet fuel spill site at Hill AFB.
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Air permeability was appropriately estimated using GASSOLVE.
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VENT3D helped in determining the initial total contaminant mass at the site.
Conclusions (cont.)
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3-D modeling provided a closer match to field measurements than 2-D
modeling.
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The loss of accuracy in 2-D modeling was small from a design standpoint and
was accompanied by considerable savings in computer time.
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JP-4 could be represented with a mass-equivalent 10-compound mixture, and
even a single component representing the mixture.
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The gain in accuracy provided from modeling the multi-component mixture
also came at the cost of extra computational effort.
Conclusions (cont.)
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The slight improvement in accuracy by using 3-D modeling and detailed multicomponent representation of the jet fuel does not justify the increased
computational effort.
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We therefore propose that for similar applications, one can represent the
mixture by a smaller number of compounds and use a two-dimensional model
without considerable loss of accuracy.
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VENT3D was useful in demonstrating the changes in JP-4 composition during
SVE .
Conclusions (cont.)
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In this case, a surface seal was predicted to have minimal effect on cumulative
mass removals.
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If a model was to be used for design purposes, it would be more convenient to
be able to use average (constant) flow conditions instead of going through a
lengthy, complicated process of running a large number of simulations.
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Data from long-term studies give a better description of site conditions and
system behavior than data from pilot tests.
Limitations
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VENT3D calculated soil gas concentrations did not match well with observed
concentrations due to the following:
–
mass distribution from soil cores was not accurate.
–
VENT3D does not allow for specifying different mass fractions at different locations.
–
VENT3D does not account for mass transfer limitations.
–
The site domain was modeled as a homogeneous formation.