Methods for characterizing subsurface volatile contaminants using in-situ sensors

• US 7,003,405 B1
• Filed: 10/25/2002
• Issued: 02/21/2006
• Est. Priority Date: 10/25/2001
• Status: Active Grant

• Current Assignee: National Technology & Engineering Solutions Of Sandia LLC (Honeywell International Inc.)
• Original Assignee: Sandia Corporation (Martin Marietta Corporation)
• Inventors: Ho, Clifford K.
• Primary Examiner(s): Sines, Brian J.
• Application Number:
  US10/280,258
• Time in Patent Office: 1,215 Days
• Field of Search: 436/43, 436/139, 436/140, 436/141, 700/266, 702/1, 702/2, 702/6, 702/9, 702/13, 702/22, 702/23, 702/24, 702/25, 702/30, 702/31, 702/32, 422/83, 422/68.1, 73/10.1, 73/10.2, 73/232
• US Class Current: 702/32
• CPC Class Codes: G01V 9/007 by detecting gases or particles representative of underground layers at or near the surface analysing earth materials G01N33/24; analysing gases per se G01N
• CPC Class Codes: Y10T 436/11 Automated chemical analysis
• CPC Class Codes: Y10T 436/21 Hydrocarbon
• CPC Class Codes: Y10T 436/212 Aromatic
• CPC Class Codes: Y10T 436/214 Acyclic [e.g., methane, octane, isoparaffin, etc.]

Abstract

An inverse analysis method for characterizing diffusion of vapor from an underground source of volatile contaminant using data taken by an in-situ sensor. The method uses one-dimensional solutions to the diffusion equation in Cartesian, cylindrical, or spherical coordinates for isotropic and homogenous media. If the effective vapor diffusion coefficient is known, then the distance from the source to the in-situ sensor can be estimated by comparing the shape of the predicted time-dependent vapor concentration response curve to the measured response curve. Alternatively, if the source distance is known, then the effective vapor diffusion coefficient can be estimated using the same inverse analysis method. A triangulation technique can be used with multiple sensors to locate the source in two or three dimensions. The in-situ sensor can contain one or more chemiresistor elements housed in a waterproof enclosure with a gas permeable membrane.

Claims

1. A method of estimating the distance from an underground source of volatile contaminant to an in-situ sensor, comprising:

a) measuring a time-varying concentration of vapor from an underground source of volatile contaminant using an in-situ sensor located underground;

b) generating a time-dependent response curve from the measured concentrations;

c) providing an effective vapor diffusion coefficient, D;

d) estimating the distance, L, between the in-situ sensor and the contaminant source;

e) predicting the time-varying concentration C′

using the effective vapor diffusion coefficient, D, calculated in step c), and using the estimated distance, L, estimated in step d), by using a one-dimensional analytical solution for diffusion of vapor from a fixed source in an isotropic and homogenous porous media;

f) generating a time-dependent response curve based from the predicted concentrations;

g) normalizing both the predicted and measured response curves;

h) comparing the normalized predicted and measured response curves; and

i) repeating steps d) through h) as many times as necessary, each time adjusting the estimated distance, L, until the shape of the normalized predicted response curve matches sufficiently well the shape of the normalized measured response curve;

j) whereby the estimated distance L is finally estimated upon a sufficient match between the normalized predicted response and measured response curves.

2. The method of claim 1, wherein the effective vapor diffusion coefficient, D, is calculated by using the following equation:

$D={{\mathrm{\varphi <br><br>}}_a^{4/3}<br><br>\left(\frac{{\mathrm{\varphi <br><br>}}_a}{{\mathrm{\varphi <br><br>}}_t}\right)}^2<br><br>D^o={\left(1-S_l\right)}^{10/3}<br><br>{\mathrm{\varphi <br><br>}}_t^{4/3}<br><br>D^o$

where φ

_a is the air-filled porosity, φ

_t is the total porosity, S_l is the liquid saturation, and D^o is the binary gas-phase diffusion coefficient in air.

3. The method of claim 1, wherein using the one-dimensional analytical solution in step e) comprises using the following equation for a semi-infinite domain:

$C^{\mathrm{\prime <br><br>}}=\mathrm{erfc}<br><br>\left(\frac{L}{2<br><br>\sqrt{\mathrm{Dt}}}\right).$

4. The method of claim 1, wherein using the one-dimensional analytical solution in step e) comprises using a coordinate system selected from the group consisting of Cartesian, cylindrical, and spherical coordinates.

5. The method of claim 1, further comprising using a least-squares regression statistical analysis to estimate the source distance, L.

6. The method of claim 1, further comprising using a triangulation method with at least two in-situ sensors located underground to more accurately determine the source location.

7. The method of claim 1, wherein the in-situ sensor comprises a waterproof housing with a gas permeable membrane.

8. The method of claim 7, wherein the in-situ sensor comprises a chemiresistor sensing element.

9. The method of claim 1, further comprising communicating data from the in-situ sensor to a data logging and processing unit located on the surface.

10. The method of claim 9, further comprising wirelessly transmitting measured and processed data from the data logging and processing unit to a receiving station.

11. The method of claim 1, wherein the in-situ sensor is disposed underground at a position selected from the group consisting of inside of a monitoring well, inside of an extraction well, inside of an injection well, inside of a cone penetrometer, inside of a probe, and buried directly underground.

12. The method of claim 1, wherein the analysis begins after a remediation system has reduced the vapor concentration to below a pre-selected threshold level and the remediation system has been turned off, at which point the vapor concentration rebounds.

13. A method of estimating an effective vapor diffusion coefficient, D, which characterizes the diffusion of a vapor from an underground source of volatile contaminant located at a known distance, L, from an in-sift sensor, comprising:

a) measuring a time-varying concentration of vapor from an underground source of volatile contaminant using an in-situ sensor located underground at a known distance, L, from the source of volatile contaminant;

b) generating a time-dependent response curve from the measured concentrations;

c) estimating the effective vapor diffusion coefficient, D;

d) predicting the time-varying concentration C′

using the estimated effective vapor diffusion coefficient, D, estimated in step c), and using the known distance, L, by using a one-dimensional analytical solution for diffusion of vapor from a fixed source in an isotropic and homogenous porous media;

e) generating a time-dependent response curve from the predicted concentrations;

f) normalizing both the predicted and measured response curves;

g) comparing the normalized predicted and measured response curves; and

h) repeating steps d) through h) as many times as necessary, each time adjusting the estimated effective vapor diffusion coefficient, D, until the shape of the normalized predicted response curve matches sufficiently well the shape of the normalized measured response curve;

i) whereby the effective vapor diffusion coefficient, D, is estimated.

14. The method of claim 13, wherein using the one-dimensional analytical solution in step e) comprises using the following equation for a semi-infinite domain:

$C^{\mathrm{\prime <br><br>}}=\mathrm{erfc}<br><br>\left(\frac{L}{2<br><br>\sqrt{\mathrm{Dt}}}\right).$

15. The method of claim 13, wherein using the one-dimensional analytical solution in step e) comprises using a coordinate system selected from the group consisting of Cartesian, cylindrical, and spherical coordinates.

16. The method of claim 13, further comprising using a least-squares regression statistical analysis to estimate the effective vapor diffusion coefficient, D.

17. The method of claim 13, further comprising using at least two in-situ sensors located underground at known positions relative to the source location to more accurately estimate the effective vapor diffusion coefficient, D.

18. The method of claim 13, wherein the in-situ sensor comprises a waterproof housing with a gas permeable membrane.

19. The method of claim 18, wherein the in-situ sensor comprises a chemiresistor sensing element.

20. The method of claim 13, further comprising communicating data from the in-situ sensor to a data logging and processing unit located on the surface.

21. The method of claim 20, further comprising wirelessly transmitting data processed by the data logging and processing unit to a receiving station.

22. The method of claim 13, wherein the in-situ sensor is disposed underground at a position selected from the group consisting of inside of a monitoring well, inside of an extraction well, inside of an injection well, inside of a cone penetrometer, inside of a probe, and buried directly underground.

23. The method of claim 13, wherein the analysis begins after a remediation system has reduced the vapor concentration to below a pre-selected threshold level and the remediation system has been turned off, at which point the vapor concentration rebounds.