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Title: Joint Hydrological-Geophysical Inversion for Soil StructureIdentification

Abstract

Reliable prediction of subsurface flow and contaminant transport depends on the accuracy with which the values and spatial distribution of process-relevant model parameters can be identified. Successful characterization methods for complex soil systems are based on (1) an adequate parameterization of the subsurface, capable of capturing both random and structured aspects of the heterogeneous system, and (2) site-specific data that are sufficiently sensitive to the processes of interest. We present a stochastic approach where the high-resolution imaging capability of geophysical methods is combined with the process-specific information obtained from the inversion of hydrological data. Geostatistical concepts are employed as a flexible means to describe and characterize subsurface structures. The key features of the proposed approach are (1) the joint inversion of geophysical and hydrological raw data, avoiding the intermediate step of creating a (non-unique and potentially biased) tomogram of geophysical properties, (2) the concurrent estimation of hydrological and petrophysical parameters in addition to (3) the determination of geostatistical parameters from the joint inversion of hydrological and geophysical data; this approach is fundamentally different from inference of geostatistical parameters from an analysis of spatially distributed property data. The approach has been implemented into the iTOUGH2 inversion code and is demonstrated formore » the joint use of synthetic time-lapse ground-penetrating radar (GPR) travel times and hydrological data collected during a simulated ponded infiltration experiment at a highly heterogeneous site.« less

Authors:
;
Publication Date:
Research Org.:
Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA (US)
Sponsoring Org.:
USDOE Laboratory Directed Research andDevelopment
OSTI Identifier:
889811
Report Number(s):
LBNL-60088
R&D Project: 366165; TRN: US200619%%860
DOE Contract Number:
DE-AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: TOUGH Symposium 2006, LBNL, Berkeley, California,May 15-17, 2006
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; ACCURACY; FORECASTING; RADAR; SOILS; SPATIAL DISTRIBUTION; SUBSURFACE STRUCTURES; TRANSPORT; Hydrogeophysics iTOUGH2 Ground Penetrating Radar

Citation Formats

Finsterle, Stefan, and Kowalsky, Michael B. Joint Hydrological-Geophysical Inversion for Soil StructureIdentification. United States: N. p., 2006. Web.
Finsterle, Stefan, & Kowalsky, Michael B. Joint Hydrological-Geophysical Inversion for Soil StructureIdentification. United States.
Finsterle, Stefan, and Kowalsky, Michael B. Mon . "Joint Hydrological-Geophysical Inversion for Soil StructureIdentification". United States. doi:. https://www.osti.gov/servlets/purl/889811.
@article{osti_889811,
title = {Joint Hydrological-Geophysical Inversion for Soil StructureIdentification},
author = {Finsterle, Stefan and Kowalsky, Michael B.},
abstractNote = {Reliable prediction of subsurface flow and contaminant transport depends on the accuracy with which the values and spatial distribution of process-relevant model parameters can be identified. Successful characterization methods for complex soil systems are based on (1) an adequate parameterization of the subsurface, capable of capturing both random and structured aspects of the heterogeneous system, and (2) site-specific data that are sufficiently sensitive to the processes of interest. We present a stochastic approach where the high-resolution imaging capability of geophysical methods is combined with the process-specific information obtained from the inversion of hydrological data. Geostatistical concepts are employed as a flexible means to describe and characterize subsurface structures. The key features of the proposed approach are (1) the joint inversion of geophysical and hydrological raw data, avoiding the intermediate step of creating a (non-unique and potentially biased) tomogram of geophysical properties, (2) the concurrent estimation of hydrological and petrophysical parameters in addition to (3) the determination of geostatistical parameters from the joint inversion of hydrological and geophysical data; this approach is fundamentally different from inference of geostatistical parameters from an analysis of spatially distributed property data. The approach has been implemented into the iTOUGH2 inversion code and is demonstrated for the joint use of synthetic time-lapse ground-penetrating radar (GPR) travel times and hydrological data collected during a simulated ponded infiltration experiment at a highly heterogeneous site.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2006},
month = {Mon May 01 00:00:00 EDT 2006}
}

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  • Understanding fluid distribution and movement in the subsurface is critical for a variety of subsurface applications, such as remediation of environmental contaminants, sequestration of nuclear waste and CO2, intrusion of saline water into fresh water aquifers, and the production of oil and gas. It is well recognized that characterizing the properties that control fluids in the subsurface with the accuracy and spatial coverage needed to parameterize flow and transport models is challenging using conventional borehole data alone. Integration of conventional borehole data with more spatially extensive geophysical data (obtained from the surface, between boreholes, and from surface to boreholes) showsmore » promise for providing quantitative information about subsurface properties and processes. Typically, estimation of subsurface properties involves a two-step procedure in which geophysical data are first inverted and then integrated with direct measurements and petrophysical relationship information to estimate hydrological parameters. However, errors inherent to geophysical data acquisition and inversion approaches and errors associated with petrophysical relationships can decrease the value of geophysical data in the estimation procedure. In this paper, we illustrate using two examples how joint inversion approaches, or simultaneous inversion of geophysical and hydrological data, offer great potential for overcoming some of these limitations.« less
  • A method is described for jointly using time-lapse multiple-offset cross-borehole ground-penetrating radar (GPR) travel time measurements and hydrological measurements to estimate field-scale soil hydraulic parameters and parameters of the petrophysical function, which relates soil porosity and water saturation to the effective dielectric constant. We build upon previous work to take advantage of a wide range of GPR data acquisition configurations and to accommodate uncertainty in the petrophysical function. Within the context of water injection experiments in the vadose zone, we test our inversion methodology with synthetic examples and apply it to field data. The synthetic examples show that while realisticmore » errors in the petrophysical function cause substantial errors in the soil hydraulic parameter estimates,simultaneously estimating petrophysical parameters allows for these errors to be minimized. Additionally, we observe in some cases that inaccuracy in the GPR simulator causes systematic error in simulated travel times, making necessary the simultaneous estimation of a correction parameter. We also apply the method to a three-dimensional field setting using time-lapse GPR and neutron probe (NP) data sets collected during an infiltration experiment at the U.S. Department of Energy (DOE) Hanford site in Washington. We find that inclusion of GPR data in the inversion procedure allows for improved predictions of water content, compared to predictions made using NP data alone.« less
  • A method is described for the joint use of time-lapse ground-penetrating radar (GPR) travel times and hydrological data to estimate field-scale soil hydraulic parameters. We build upon previous work to take advantage of a wide range of cross-borehole GPR data acquisition configurations and to accommodate uncertainty in the petrophysical function, which relates soil porosity and water saturation to the effective dielectric constant. We first test the inversion methodology using synthetic examples of water injection in the vadose zone. Realistic errors in the petrophysical function result in substantial errors in soil hydraulic parameter estimates, but such errors are minimized through simultaneousmore » estimation of petrophysical parameters. In some cases the use of a simplified GPR simulator causes systematic errors in calculated travel times; simultaneous estimation of a single correction parameter sufficiently reduces the impact of these errors. We also apply the method to the U.S. Department of Energy (DOE) Hanford site in Washington, where time-lapse GPR and neutron probe (NP) data sets were collected during an infiltration experiment. We find that inclusion of GPR data in the inversion procedure allows for improved predictions of water content, compared to predictions made using NP data alone. These examples demonstrate that the complimentary information contained in geophysical and hydrological data can be successfully extracted in a joint inversion approach. Moreover, since the generation of tomograms is not required, the amount of GPR data required for analyses is relatively low, and difficulties inherent to tomography methods are alleviated. Finally, the approach provides a means to capture the properties and system state of heterogeneous soil, both of which are crucial for assessing and predicting subsurface flow and contaminant transport.« less
  • The purpose of this project is to develop a computer code for joint inversion of seismic and electrical data, to improve underground imaging for site characterization and remediation monitoring. The computer code developed in this project will invert geophysical data to obtain direct estimates of porosity and saturation underground, rather than inverting for seismic velocity and electrical resistivity or other geophysical properties. This is intended to be a significant improvement in the state-of-the-art of underground imaging, since interpretation of data collected at a contaminated site would become much less subjective. Potential users include DOE scientists and engineers responsible for characterizingmore » contaminated sites and monitoring remediation of contaminated sites. In this three-year project, we use a multi-phase approach consisting of theoretical and numerical code development, laboratory investigations, testing on available laboratory and borehole geophysics data sets, and a controlled field experiment, to develop practical tools for joint electrical and seismic data interpretation.« less