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Open AccessArticle

Comparison of Hydraulic and Tracer Tomography for Discrete Fracture Network Inversion

1
Institute of New Energy Systems, Ingolstadt University of Applied Sciences, 85049 Ingolstadt, Germany
2
Institute of Mathematics, University of Potsdam, 14476 Potsdam, Germany
3
Department of Engineering Geology and Hydrogeology, RWTH Aachen, 52064 Aachen, Germany
*
Author to whom correspondence should be addressed.
Geosciences 2019, 9(6), 274; https://doi.org/10.3390/geosciences9060274
Received: 7 May 2019 / Revised: 14 June 2019 / Accepted: 18 June 2019 / Published: 21 June 2019
(This article belongs to the Special Issue Subsurface Thermography and the Use of Temperature in Geosciences)
Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat. The presented study compares the results from hydraulic and tracer tomography applied to invert a theoretical discrete fracture network (DFN) that is based on data from synthetic cross-well testing. For hydraulic tomography, pressure pulses in various injection intervals are induced and the pressure responses in the monitoring intervals of a nearby observation well are recorded. For tracer tomography, a conservative tracer is injected in different well levels and the depth-dependent breakthrough of the tracer is monitored. A recently introduced transdimensional Bayesian inversion procedure is applied for both tomographical methods, which adjusts the fracture positions, orientations, and numbers based on given geometrical fracture statistics. The used Metropolis-Hastings-Green algorithm is refined by the simultaneous estimation of the measurement error’s variance, that is, the measurement noise. Based on the presented application to invert the two-dimensional cross-section between source and the receiver well, the hydraulic tomography reveals itself to be more suitable for reconstructing the original DFN. This is based on a probabilistic representation of the inverted results by means of fracture probabilities. View Full-Text
Keywords: hydraulic tomography; tracer tomography; DFN; Bayesian inversion; heterogeneity; fracture; hydrogeophysics hydraulic tomography; tracer tomography; DFN; Bayesian inversion; heterogeneity; fracture; hydrogeophysics
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MDPI and ACS Style

Ringel, L.M.; Somogyvári, M.; Jalali, M.; Bayer, P. Comparison of Hydraulic and Tracer Tomography for Discrete Fracture Network Inversion. Geosciences 2019, 9, 274.

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