Noninvasive monitoring of DNAPL migration through a saturated porous medium using electrical impedance tomography

Chambers, Jonathan; Loke, M.H.; Ogilvy, R.D.; Meldrum, Philip

doi:10.1016/s0169-7722(03)00142-6

Cited by 113 publications

(82 citation statements)

References 43 publications

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“…For the interpretation, the commercial software Res2Dinv (Loke 1996(Loke -2004) and the so-called robust inversion method were used. The minimization of a mixed L1-norm was done as an iteratively re-weighted least-squares algorithm, similar to that proposed by Farquharson and Oldenburg (1998).…”

Section: Interpretation Of Resistivity Datamentioning

confidence: 99%

“…Such models are often found to represent geological reality better and that is why the ''blocky method'' is often preferred. For estimating the changes between measurements made at two different times, the programme provides different options for the ''time-lapse inversion'', which define the constraints between successive time steps (Loke 1999;Chambers et al 2004). The aim is that the result should be more representative of actual changes in the underground and less affected by noise, due for example to changes in the contact between the electrodes and the ground.…”

Section: Interpretation Of Resistivity Datamentioning

confidence: 99%

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Time-lapse resistivity investigations for imaging saltwater transport in glaciofluvial deposits

Leroux

Dahlin

2005

Environ Geol

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Section: Interpretation Of Resistivity Datamentioning

confidence: 99%

Section: Interpretation Of Resistivity Datamentioning

confidence: 99%

Time-lapse resistivity investigations for imaging saltwater transport in glaciofluvial deposits

Leroux

Dahlin

2005

Environ Geol

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“…The values can be calculated analytically as the potential values have a simple mathematical form. However for a non-infinite or nonhomogeneous medium where the potentials due to a current source do not have a simple mathematical form, the effective geometric factor (and associated sensitivity values) have to be calculated numerically (Chambers et al 2004). To calculate the potentials values, we use the finite-difference method (Dey & Morrison 1979;Loke & Barker 1996).…”

Section: A P P E N D I X : C a L C U L At I O N O F T H E G E O M E Tmentioning

confidence: 99%

Computation of Optimized Arrays for 3-D Electrical Imaging Surveys

Wilkinson¹,

Loke²,

Chambers³

2013

Proceedings

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S U M M A R Y3-D electrical resistivity surveys and inversion models are required to accurately resolve structures in areas with very complex geology where 2-D models might suffer from artefacts. Many 3-D surveys use a grid where the number of electrodes along one direction (x) is much greater than in the perpendicular direction (y). Frequently, due to limitations in the number of independent electrodes in the multi-electrode system, the surveys use a roll-along system with a small number of parallel survey lines aligned along the x-direction. The 'Compare R' array optimization method previously used for 2-D surveys is adapted for such 3-D surveys. Offset versions of the inline arrays used in 2-D surveys are included in the number of possible arrays (the comprehensive data set) to improve the sensitivity to structures in between the lines. The array geometric factor and its relative error are used to filter out potentially unstable arrays in the construction of the comprehensive data set. Comparisons of the conventional (consisting of dipole-dipole and Wenner-Schlumberger arrays) and optimized arrays are made using a synthetic model and experimental measurements in a tank. The tests show that structures located between the lines are better resolved with the optimized arrays. The optimized arrays also have significantly better depth resolution compared to the conventional arrays.

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“…This technique can be carried out through short time periods (several days with readings taken every few hours) to evaluate the migration of contamination plumes (Radulescu et al, 2007), detection and monitoring of concentration of a conductive contaminant within aquifers (Cassiani et al, 2006;Chambers et al, 2004;Oldenborger et al, 2007), quantification of superficial water infiltration rates into the subsurface (Barker and Moore, 1998) and tracer test monitoring (Monego et al, 2010;Ward et al, 2010). Long term time-lapse resistivity surveys have been applied to monitor seasonal variations on seepage rates (Johansson and Dahlin, 1996;Sjödahl et al, 2008), monitoring salinity within aquifers in coastal areas (de Franco et al, 2009;Leroux and Dahlin, 2006;Ogilvy et al, 2009), safety assessment for storage of nuclear waste (Yaramanci, 2000), estimation of subsurface temperature variation (Morard et al, 2008), observing changes in liquid water saturation and temperature in frozen ground (Hauck, 2002) and monitoring permafrost active layer thickness variation (Kneisel, 2006).…”

Section: Introductionmentioning

confidence: 99%

Time-lapse resistivity analysis of Quaternary sediments in the Midlands of Ireland

Pellicer

Zarroca

Gibson

2012

Journal of Applied Geophysics

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a b s t r a c t a r t i c l e i n f oElectrical Resistivity Tomography (ERT) data are influenced by a number of factors associated with the subsurface such as porosity, moisture content and lithology; as well as external factors such as rainfall and temperature. Two time-lapse ERT profiles with 5 m and two with 2 m electrode spacings were acquired over a range of Quaternary sediment types encompassing till, esker gravel, glaciofluvial sand and silt and glaciolacustrine silt/clay. Data were collected on a monthly basis during 2006 at a site located in the Midlands of Ireland in order to evaluate the influence of such conditioning factors on the resistivity of the subsurface. Effective recharge, the depth of investigation, the texture and the internal architecture of the different sediment types and temperature variation are the main factors influencing the resistivity seasonal variation. The shallow subsurface (b 3 m depth) showed a direct relationship between resistivity variation and effective recharge, whereas, an increasing time-lag between effective recharge and resistivity was recorded at increasing depths. As a result of the time-lag, it was possible to determine the rate of movement of the wetting/drying front for the unconsolidated relatively sorted coarse sediments recorded on the site at 7.8 cm/day. Conversely, poorly sorted and fine sediments show little resistivity variation and the velocity of the wetting front could not be estimated. Other factors influencing the electrical response of the subsurface are the electrode spacing used for data collection and the seasonal temperature variation of the subsurface. Two methods for temperature correction of electrical resistivity data were tested in this study -both gave similar results. Resistivity values recorded in the shallow subsurface (b 5 m) show variations of over 15% subsequent to temperature correction. The results illustrate that seasonal temperature changes and their influence on subsurface temperature have to be accounted for in data interpretation and emphasise the potential of this technique for the estimation of the rate of movement of the wetting/drying front in soft sediments.

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Noninvasive monitoring of DNAPL migration through a saturated porous medium using electrical impedance tomography

Cited by 113 publications

References 43 publications

Time-lapse resistivity investigations for imaging saltwater transport in glaciofluvial deposits

Time-lapse resistivity investigations for imaging saltwater transport in glaciofluvial deposits

Computation of Optimized Arrays for 3-D Electrical Imaging Surveys

Time-lapse resistivity analysis of Quaternary sediments in the Midlands of Ireland

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