4D active time constrained resistivity inversion

Karaoulis, M.; Kim, J.-H.; Τσούρλος, Π.

doi:10.1016/j.jappgeo.2010.11.002

Cited by 95 publications

(61 citation statements)

References 33 publications

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“…As outlined at the end of the previous section, this statement holds today, although some of the above controls have been further investigated in laboratory studies over the past 15 years, including mainly textural parameters (e.g., Vanhala 1997; Slater and Lesmes 2002; Scott and Barker 2003; Binley et al 2005; Slater et al 2006; Kruschwitz et al 2010; Weller et al 2010a) and permeability (e.g., Börner et al 1996; Slater and Lesmes 2002; Binley et al 2005; Revil and Florsch 2010; Zisser et al 2010a; Koch et al 2011; Revil et al 2012b). More laboratory measurements are particularly needed regarding the effect of chemistry (e.g., Lesmes and Frye 2001; Vaudelet et al 2011; Weller et al 2011), saturation (e.g., Ulrich and Slater 2004; Jougnot et al 2010; Breede et al 2012), temperature (e.g., Binley et al 2010; Zisser et al 2010b; Martinez et al 2012), multiple fluid phases (e.g., Cassiani et al 2009; Schmutz et al 2010; Revil et al 2011) and in addition effective pressure (e.g., Zisser and Nover 2009), grain‐size distribution (e.g., Revil and Florsch 2010), pH (e.g., Skold et al 2011) and the effect of microbial processes (see Atekwana and Slater 2009 for a recent review). Biogeophysics research has determined that SIP is one of the most promising geophysical techniques for detecting the alteration of mineral‐fluid interfaces and pore geometries resulting from microbial growth and biofilm formation (e.g., Abdel Aal et al 2004; Ntarlagiannis et al 2005a; Davis et al 2006; Abdel Aal et al 2009, 2010a,b) as well as biomineralization (e.g., Ntarlagiannis et al 2005b; Williams et al.…”

Section: Laboratory Measurementsmentioning

confidence: 99%

An overview of the spectral induced polarization method for near‐surface applications

Kemna

Binley

Cassiani

et al. 2012

Near Surface Geophysics

256

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Over the last 15 years significant advancements in induced polarization (IP) research have taken place, particularly with respect to spectral IP (SIP), concerning the understanding of the mechanisms of the IP phenomenon, the conduction of accurate and broadband laboratory measurements, the modelling and inversion of IP data for imaging purposes, and the increasing application of the method in near-surface investigations. We here summarized the current state of the science of the SIP method for near-surface applications and describe which aspects still represent open issues and should be the focus of future research efforts.Significant progress has been made over the last decade in the understanding of the microscopic mechanisms of IP; however, integrated mechanistic models involving the different possible polarization processes at the grain/pore scale are still lacking. A prerequisite for the advances in the mechanistic understanding of IP was the development of improved laboratory instrumentation, which has led to a continuously growing database of SIP measurements on various soil and rock samples. We summarize the experience of numerous experimental studies by formulating key recommendations for reliable SIP laboratory measurements. To make use of the established theoretical and empirical relationships between SIP characteristics and target petrophysical properties at the field scale, sophisticated forward modelling and inversion algorithms are needed. Considerable progress has been made also in this field, in particular with the development of complex resistivity algorithms allowing the modelling and inversion of IP data in the frequency domain. The ultimate goal for the future are algorithms and codes for the integral inversion of 3-D, time-3 lapse and multi-frequency IP data, which defines a 5-D inversion problem involving the dimensions space (for imaging), time (for monitoring) and frequency (for spectroscopy). We also offer guidelines for reliable and accurate measurements of IP spectra, which are essential for improved understanding of IP mechanisms and their links to physical, chemical and biological properties of interest. We believe that the SIP method offers potential for subsurface structure and process characterization, in particular in hydrogeophysical and biogeophysical studies.

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Section: Laboratory Measurementsmentioning

confidence: 99%

An overview of the spectral induced polarization method for near‐surface applications

Kemna

Binley

Cassiani

et al. 2012

Near Surface Geophysics

256

211

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“…As mentioned, ERT surveys were simulated at intervals corresponding to ∼10% reductions of the DNAPL mass. Although difference or 4D inversion routines (e.g., Kim et al, 2009;Karaoulis et al, 2011a) may best take advantage of the differences detected, such optimization of the ERT analysis for DNAPL remediation is the subject of future work. Figure 7a and 7c reveals that, as expected, the DNAPL mass was removed from the source zone in a heterogeneous manner (compare to Figure 6c).…”

Section: Mapping Dnapl Remediationmentioning

confidence: 99%

“…Moreover, this envelope of favorable conditions is likely dependent on the ERT survey design and processing methodology, neither of which have been optimized for DNAPL sites. It is possible that recent advances in ERT imaging (e.g., data acquisition and timelapse monitoring) may be beneficial in this context (e.g., Ogilvy et al, 2009;Karaoulis et al, 2011a;Nenna et al, 2011). The systematic, controlled studies required to explore these questions at the field scale are not available from field trials or laboratory studies.…”

Section: Introductionmentioning

confidence: 99%

A new coupled model for simulating the mapping of dense nonaqueous phase liquids using electrical resistivity tomography

et al. 2013

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Electrical resistivity tomography (ERT) has, for a considerable length of time, been considered promising for subsurface characterization activities at sites contaminated with dense, nonaqueous phase liquids (DNAPLs). The relatively few field studies available exhibit mixed results, and the technique has not yet become a common tool for mapping such contaminants or tracking mass reduction during their remediation. To help address this, a novel, coupled DNAPL-ERT numerical model was developed that can provide a platform for the systematic evaluation of ERT under a wide range of realistic, field-scale subsurface environments. The coupled model integrated a 3D multiphase flow model, which generates realistic DNAPL scenarios, with a 3D ERT forward model to calculate the corresponding resistivity response. Central to the coupling, and a key contribution, was a new linkage between the main hydrogeologic parameters (including hydraulic permeability, porosity, clay content, groundwater salinity and temperature, and air, water, and DNAPL contents evolving with time) and the resulting bulk electrical resistivity by integration of a variety of published relationships. Sensitivity studies conducted for a single node compared well to published correlations and for a fieldscale domain demonstrated that the model is robust and sensitive to heterogeneity in DNAPL distribution and soil structure. A field-scale simulation of a DNAPL release and its subsequent remediation, monitored by ERT surface surveys, demonstrated that ERT is promising for mapping DNAPL mass reduction. The developed model provides a cost-effective avenue to test optimum ERT data acquisition, inversion, and interpretative tools, which should assist in deploying ERT strategically at contaminated sites.

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“…The different inversion scheme takes advantage of the repetition of measurements over time to eliminate the systematic error component of the data (LaBrecque and Yang, 2001;Kemna et al, 2002). The 4D inversion scheme (Kim et al, 2009;Karaoulis et al, 2011) inverts multiple data sets simultaneously including the time dimension in the inversion process. However, deterministic time-lapse inversion schemes still remain dependent on the spatial or spatiotemporal regularization procedure required to overcome the ill-posedness of the ERT inverse problem.…”

Section: Introductionmentioning

confidence: 99%

Covariance-constrained difference inversion of time-lapse electrical resistivity tomography data

2016

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Hydrogeophysics has become a major field of research in the past two decades, and time-lapse electrical resistivity tomography (ERT) is one of the most popular techniques to monitor passive and active processes in shallow subsurface reservoirs. Time-lapse inversion schemes have been developed to refine inversion results, but they mostly still rely on a spatial regularization procedure based on the standard smoothness constraint. We have applied a covariance-based regularization operator to the time-lapse ERT inverse problem. We first evaluated the method for surface and crosshole ERT with two synthetic cases and compared the results with the smoothness-constrained inversion (SCI). These tests showed that the covariance-constrained inversion (CCI) better images the target in terms of shape and amplitude. Although more important in low-sensitivity zones, we have observed improvements everywhere in the tomograms. Those synthetic examples also show that an error made in the range or in the type of the variogram model had a limited impact on the resulting image, which still remained better than SCI. We then applied the method to cross-borehole ERT field data from a heat-tracing experiment, in which the comparison with direct measurements showed a strong improvement of the breakthrough curves retrieved from ERT. This method could be extended to the time dimension, which would allow the use of CCI in 4D inversion schemes.

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4D active time constrained resistivity inversion

Cited by 95 publications

References 33 publications

An overview of the spectral induced polarization method for near‐surface applications

An overview of the spectral induced polarization method for near‐surface applications

A new coupled model for simulating the mapping of dense nonaqueous phase liquids using electrical resistivity tomography

Covariance-constrained difference inversion of time-lapse electrical resistivity tomography data

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