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Joint Stochastic Inversion of Geophysical Data in Fractured Rock

English title Joint Stochastic Inversion of Geophysical Data in Fractured Rock
Applicant Linde Niklas
Number 140390
Funding scheme Project funding (Div. I-III)
Research institution Institut des sciences de la Terre Université de Lausanne
Institution of higher education University of Lausanne - LA
Main discipline Geophysics
Start/End 01.05.2012 - 30.04.2013
Approved amount 58'061.00
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Keywords (11)

Inversion theory; Flow and transport modeling; Flowmeter data; Single- and cross-borehole radar; Borehole geophysics; Bayesian methods; Hydrogeophysics; Fractured media; Stochastic methods; joint inversion; Hydrogeology

Lay Summary (English)

Lead
Lay summary

Hydrological and geophysical characterization and prediction of flow and transport processes in fractured rock pose extraordinary challenges. The discrete nature of fractured rock implies that physical properties and the geometry of individual fractures cannot be imaged using the same geophysical or hydrological data and approaches that are typically used in sedimentary environments. In a previous project, we have shown that reflections from high-frequency electromagnetic signals that are emitted and received in boreholes makes it possible to obtain important constraints about fracture geometry away from the boreholes. In a case study, we acquired such single-borehole and cross-borehole Ground Penetrating Radar (GPR) data at a well-characterized fractured rock aquifer located in Brittany, France. We then acquired five successful saline tracer injection tests in known transmissive fractures while monitoring single-borehole GPR in another borehole to track the resultant tracer movement stimulated by pumping and injection, as well as the natural flow regime. After developing a suitable processing scheme, we found for the different experiments that we could image the tracer movement over tenths of meters through a network of connected fractures.

 

The present one-year prolongation of the previous project focuses on developing a method to identify the geometry and properties of transmissive fractures in low to moderately fractured rock by jointly combining (inverting) different types of geophysical and hydrological data. The approach will be stochastic (it relies on Bayesian Theory), which implies that we seek many models that can explain the available data, but possibly with very different geometries. The method will be applied to the field site discussed above. The outcomes of the proposed inversion will be probability distribution functions of all model parameters (up to 100) describing possible geometries and hydrological properties of the fractures in which tracer movement occurs given available hydrological and geophysical data and a priori constraints. The application of the inversion algorithm to the existing field data will not only provide quantitative insights in the relative value of different data types in hydrological characterization of fractured rock, but also provide fundamental insights in the possible transport pathways and dispersion mechanisms that can explain hydrological data acquired in boreholes. By providing the full range of permissible parameter values, the proposed method is also suitable for risk and uncertainty assessments for a wide range of application areas related to contaminant transport, petroleum engineering, and geothermics.

Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data
Dorn Caroline, Linde Niklas, Le Borgne Tanguy, Bour Olivier, de Dreuzy Jean-Raynald (2013), Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data, in Advances in Water Resources, 62, 79-89.
Inferring transport characteristics in a fractured rock aquifer by combining single-hole ground-penetrating radar reflection monitoring and tracer test data
Dorn C, Linde N, Le Borgne T, Bour O, Klepikova M (2012), Inferring transport characteristics in a fractured rock aquifer by combining single-hole ground-penetrating radar reflection monitoring and tracer test data, in WATER RESOURCES RESEARCH, 48, W11521.

Collaboration

Group / person Country
Types of collaboration
University of Rennes 1, Géosciences Rennes France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel

Awards

Title Year
The PhD thesis of Caroline Dorn entitled "Fracture Network Characterization Using Hydrological and Geophysical Data" received the Faculty Price 2012-2013 of the Faculty of Geosciences and Environment at the University of Lausanne 2013

Associated projects

Number Title Start Funding scheme
124571 Joint Stochastic Inversion of Geophysical Data in Fractured Rock 01.05.2009 Project funding (Div. I-III)
146602 Imaging of tracer transport in fracture networks: Perfection of the single-hole GPR monitoring technique and its use in quantitative hydrology 01.11.2013 Project funding (Div. I-III)

Abstract

Hydrological and geophysical characterization and prediction in fractured rock pose extraordinary challenges. In fractured rock, physical properties and the geometry of individual fractures cannot be imaged using standard regularized inversion of geophysical or hydrological cross-borehole data. By acquiring single-borehole and cross-borehole ground penetrating radar to a well-characterized fractured rock aquifer located in Brittany, France, we obtained important structural constraints on the fracture geometry away from the boreholes. Five successful saline tracer injection tests in known transmissive fractures performed while monitoring single-borehole GPR in another borehole allowed us to track the resultant tracer movement due to the pumping and injection schemes, as well as the natural flow regime. After developing a suitable processing scheme, we find for the different experiments that we can image the tracer movement over tenths of meters through a network of connected fractures. The one-year prolongation of this ongoing project will focus on developing a method for stochastic identification of the geometry and properties of transmissive fractures in low to moderately fractured rock by jointly inverting different types of geophysical and hydrological data. The method will be tested at the field site discussed above. Multi-fold single-borehole and cross-borehole radar reflection experiments are useful for identifying major open fractures, including those that are nearly vertical and cannot be identified using borehole geophysical logging. These data have for our field-site been interpreted together with geophysical borehole logging data to provide geometrical constraints on possible fracture distributions. Geophysical data collected during natural flow conditions provide only limited information about the hydrological properties of fractures. It was therefore necessary to perform experiments in which saline solutions were injected in open fractures and to use time-lapse radar reflection data to monitor the fractures occupied by the tracer. These sets of processed geophysical and hydrological data will in the prolongation of this project be integrated within a Bayesian joint inversion framework using an efficient parallel Markov chain Monte Carlo method.The outcomes of the proposed inversion will be probability distribution functions of all model parameters (up to 100) describing the possible geometry and hydrological properties of the fractures in which tracer movement occurs given available data and a priori constraints. The application of the inversion algorithm to the existing field data will not only provide quantitative insights in the relative value of different data types in hydrological characterization of fractured rock, but also provide fundamental insights in the possible transport pathways and dispersion mechanisms that can explain hydrological data acquired in boreholes. By providing the full range of permissible parameter values, the proposed method is also suitable for risk assessments for a wide range of application areas related to contaminant transport, petroleum engineering, and geothermics.
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