Hydraulic Tomography for Detecting Fracture Zone Connectivity

Hao, Yonghong; Yeh, Tian Chyi Jim; Xiang, Jianwei; Illman, Walter A.; Ando, Kenichi; Hsu, Kuo Chin; Lee, Cheng Haw

doi:10.1111/j.1745-6584.2007.00388.x

Cited by 83 publications

(67 citation statements)

References 66 publications

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“…These tests are useful but not flawless (Wu et al, 2005) because they depend on strong assumptions such as Theis' homogeneous aquifer assumption (Fetter, 2001). Pumping tests evolved into hydraulic tomography which allows obtaining high resolution images of the hydraulic conductivity distribution (Yeh and Liu, 2000;Liu et al, 2002;Zhu and Yeh, 2005;Illman and Tartakovsky, 2006;Zhu and Yeh, 2006;Hao et al, 2008;Illman et al, 2008;Yin and Illman, 2009). However, this method requires several wells and prior knowledge about the location of fractures.…”

Section: Introductionmentioning

confidence: 99%

A salt tracer test monitored with surface ERT to detect preferential flow and transport paths in fractured/karstified limestones

et al. 2012

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In hard-rock aquifers, fractured zones constitute adequate drinking water exploitation areas but also potential contamination paths. One critical issue in hydrogeological research is to identify, characterize, and monitor such fractured zones at a representative scale. A tracer test monitored with surface electrical resistivity tomography (ERT) could help by delineating such preferential flow paths and estimating dynamic properties of the aquifer. However, multiple challenges exist including the lower resolution of surface ERT compared with crosshole ERT, the finite time that is needed to complete an entire data acquisition, and the strong dilution effects. We conducted a natural gradient salt tracer test in fractured limestones. To account for the high transport velocity, we injected the salt tracer continuously for four hours at a depth of 18 m. We monitored its propagation with two parallel ERT profiles perpendicular to the groundwater flow direction. Concerning the data acquisition, we always focused on data quality over temporal resolution. We performed the experiment twice to prove its reproducibility by increasing the salt concentration in the injected solution (from 38 to [Formula: see text]). Our research focused on how we faced every challenge to delineate a preferential flow and solute transport path in a typical calcareous valley of southern Belgium and on the estimation of the transport velocity (more than [Formula: see text]). In this complex environment, we imaged a clear tracer arrival in both ERT profiles and for both tests. Applying filters (with a cutoff on the relative sensitivity matrix and on the background-resistivity changes) was helpful to isolate the preferential flow path from artifacts. Regarding our findings, our approach could be improved to perform a more quantitative experiment. With a higher temporal resolution, the estimated value of the transport velocity could be narrowed, allowing estimation of the percentage of tracer recovery.

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Section: Introductionmentioning

confidence: 99%

A salt tracer test monitored with surface ERT to detect preferential flow and transport paths in fractured/karstified limestones

et al. 2012

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“…Solving Eq. (27) gives both the minimum travel time from a point x to its nearest known neighbor x k , tðxÞ and the nearest neighbor interpolant of this point pðxÞ which has the value f k (corresponding to x k ). The metric tensor field DðxÞ derived from the guiding image allows computing the nearest neighbor interpolant pðxÞ.…”

Section: Image-guided Interpolationmentioning

confidence: 99%

“…Over the past two decades, several numerical and field studies have demonstrated how steadystate hydraulic tests can be used to image hydraulic conductivity or transmissivity (e.g., [12,21,40,59]). Transient pumping tests can also be used to estimate both of the specific storage and hydraulic conductivity fields (e.g., [3,27,64]). Hydraulic conductivity tomography can also be combined with the temporal moments method to reconstruct the hydraulic parameters heterogeneities (e.g.…”

Section: Introductionmentioning

confidence: 99%

Image-guided inversion in steady-state hydraulic tomography

Ahmed

Zhou

Jardani

et al. 2015

Advances in Water Resources

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a b s t r a c tIn steady-state hydraulic tomography, the head data recorded during a series of pumping or/and injection tests can be inverted to determine the transmissivity distributions of an aquifer. This inverse problem is usually under-determined and ill-posed. We propose to use structural information inferred from a guiding image to constrain the inversion process. The guiding image can be drawn from soft data sets such as seismic and ground penetrating radar sections or from geological cross-sections inferred from the wells and some geological expertise. The structural information is extracted from the guiding image through some digital image analysis techniques. Then, it is introduced into the inversion process of the head data as a weighted four direction smoothing matrix used in the regularizer. Such smoothing matrix allows applying the smoothing along the structural features. This helps preserving eventual drops in the hydraulic properties. In addition, we apply a procedure called image-guided interpolation. This technique starts with the tomogram obtained from the image-guided inversion and focus this tomogram. These new approaches are applied on four synthetic toy problems. The hydraulic distributions estimated from the image-guided inversion are closer to the true transmissivity model and have higher resolution than those computed from a classical Gauss-Newton method with uniform isotropic smoothing.

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“…Day-Lewis et al (2006) interpret field experimental cross-hole radar, tracer, and hydraulic data at a fractured rock aquifer at the same site and found that combining time-lapse geophysical monitoring with conventional hydrologic measurements improved the characterization of a fractured rock aquifer. Recent advances in the characterization of spatially distributed hydraulic properties of heterogeneous aquifers using hydraulic tomography (McDermott et al 2003;Brauchler et al 2003;Zhu and Yeh 2006;Hao et al 2008) provide a potential solution to this difficult problem.…”

Section: Introductionmentioning

confidence: 99%

Modeling spatial fracture intensity as a control on flow in fractured rock

Lee

Yeh

et al. 2010

Environ Earth Sci

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Spatial fracture intensity (P 32 , fracture area by volume) is an important characteristic of a jointed rock mass. Although it can hardly ever be measured, P 32 can be modeled based on available geological information such as spatial data of the fracture network. Flow in a mass composed of low-permeability hard rock is controlled by joints and fractures. In this article, models were developed from a geological data set of fractured andesite in LanYu Island (Taiwan) where a site is investigated for possible disposal of low-level and intermediate-level radionuclide waste. Three different types of conceptual models of spatial fracture intensity distribution were generated, an Enhanced Baecher's model (EBM), a Levy-Lee Fractal model (LLFM) and a Nearest Neighborhood model (NNM). Modeling was conducted on a 10 9 10 9 10 m synthetic fractured block. Simulated flow was forced by a 1% hydraulic gradient between two vertical x-z faces of the cube (from North to South) with other boundaries set to noflow conditions. Resulting flow vectors are very sensitive to spatial fracture intensity (P 32 ). Flow velocity increases with higher fracture intensity (P 32 ). R-squared values of regression analysis for the variables velocity (V/V max ) and fracture intensity (P 32 ) are 0.293, 0.353, and 0.408 in linear fit and 0.028, 0.08, and 0.084 in power fit. Higher R 2 values are positively linked with structural features but the relation between velocity and fracture intensity is non-linear. Possible flow channels are identified by stream-traces in the Levy-LeeFractal model.

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Hydraulic Tomography for Detecting Fracture Zone Connectivity

Cited by 83 publications

References 66 publications

A salt tracer test monitored with surface ERT to detect preferential flow and transport paths in fractured/karstified limestones

A salt tracer test monitored with surface ERT to detect preferential flow and transport paths in fractured/karstified limestones

Image-guided inversion in steady-state hydraulic tomography

Modeling spatial fracture intensity as a control on flow in fractured rock

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