A methodology to interpret cross-hole tests in a granite block

Water flow through low permeability fractured media is often concentrated in a small number of fractures. This fractures need to be characterized in order to simulate accurately the hydraulic behaviour of such media. We present a methodology to identify the most significant water conductive fractures. The method is based on the interpretation of cross-hole tests, and is supported by geology, geophysics and hydraulic data. The methodology has been applied to the hydrogeological characterization of a granitic block around the FEBEX experiment, at the Grimsel underground laboratory, Switzerland. Geology and geophysics are used for identifying candidates to flow controlling fractures. Single borehole hydraulic tests help in neglecting those with low transmissivity, but the only means to assess connectivity consists of performing cross-hole tests. The resulting geometry is later implemented into a 3D finite element mesh, where the fractures are simulated as 2D elements embedded into a 3D porous medium. The latter includes the effect of minor fracturing and can be heterogeneous and anisotropic. The resulting model is calibrated to obtain an integrated model. This methodology has proven capable of reproducing single-hole and cross-hole tests and steady-state heads, and also of quantifying groundwater flow to the experimental area of the FEBEX tunnel.

[1]  C. Tsang,et al.  Flow channeling in heterogeneous fractured rocks , 1998 .

[2]  Urban Svensson,et al.  A continuum representation of fracture networks. Part I: Method and basic test cases , 2001 .

[3]  Jesús Carrera,et al.  Geostatistical Inversion of Cross‐Hole Pumping Tests for Identifying Preferential Flow Channels Within a Shear Zone , 2001 .

[4]  Jesús Carrera,et al.  An analysis of hydraulic conductivity scale effects in granite (Full‐scale Engineered Barrier Experiment (FEBEX), Grimsel, Switzerland) , 2005 .

[5]  Jesús Carrera,et al.  Computational techniques for optimization of problems involving non-linear transient simulations , 1999 .

[6]  P. Witherspoon,et al.  Porous media equivalents for networks of discontinuous fractures , 1982 .

[7]  Frederick Delay,et al.  Solute transport in a single fracture with negligible matrix permeability: 1. fundamental mechanisms , 2003 .

[8]  J. Jaime Gómez-Hernández,et al.  Stochastic analysis of flow response in a three-dimensional fractured rock mass block $ , 2001 .

[9]  Agust Gudmundsson,et al.  The effects of dykes and faults on groundwater flow in an arid land: the Red Sea Hills, Sudan , 2004 .

[10]  S. P. Neuman,et al.  Stochastic continuum representation of fractured rock permeability as an alternative to the REV and fracture network concepts , 1988 .

[11]  F. Schwartz,et al.  An Analysis of the Influence of Fracture Geometry on Mass Transport in Fractured Media , 1984 .

[12]  Antoine Mensch,et al.  An inverse technique for developing models for fluid flow in fracture systems using simulated annealing , 1993 .

[13]  Roger Thunvik,et al.  Predicting mass transport in discrete fracture networks with the aid of geometrical field data , 1986 .

[14]  J. J. Gómez-Hernández,et al.  3D inverse modelling of groundwater flow at a fractured site using a stochastic continuum model with multiple statistical populations , 2002 .

[15]  Ivars Neretnieks,et al.  A note on fracture flow dispersion mechanisms in the ground , 1983 .

[16]  Ivars Neretnieks,et al.  The Channel Network Model—A Tool for Transport Simulations in Fractured Media , 1999 .

[17]  C. Talbot,et al.  Stress control of hydraulic conductivity in fracture-saturated Swedish bedrock , 2001 .

[18]  Velimir V. Vesselinov,et al.  Three‐dimensional numerical inversion of pneumatic cross‐hole tests in unsaturated fractured tuff: 1. Methodology and borehole effects , 2001 .

[19]  Maria José Jurado,et al.  Architecture of fault zones determined from outcrop, cores, 3-D seismic tomography and geostatistical modeling: example from the Albalá Granitic Pluton, SW Iberian Variscan Massif , 2003 .

[20]  X. Sanchez‐Vila,et al.  Pumping tests in heterogeneous aquifers: An analytical study of what can be obtained from their interpretation using Jacob's Method , 1999 .

[21]  Ivars Neretnieks,et al.  2 – Solute Transport in Fractured Rock — Applications to Radionuclide Waste Repositories , 1993 .

[22]  Shlomo P. Neuman,et al.  Stochastic continuum modeling of flow and transport in a crystalline rock mass: Fanay-Augères, France, revisited , 2003 .

[23]  Andres Alcolea,et al.  Pilot points method incorporating prior information for solving the groundwater flow inverse problem , 2006 .

[24]  Numerical inverse interpretation of single-hole pneumatic tests in unsaturated fractured tuff. , 2001, Ground water.

[25]  Agust Gudmundsson,et al.  Active fault zones and groundwater flow , 2000 .

[26]  Jesús Carrera,et al.  On the use of apparent hydraulic diffusivity as an indicator of connectivity , 2006 .

[27]  Jesús Carrera,et al.  Binary upscaling—the role of connectivity and a new formula , 2006 .

[28]  Jan-Olof Selroos,et al.  Comparison of alternative modelling approaches for groundwater flow in fractured rock , 2002 .

[29]  S. P. Neuman,et al.  Trends, prospects and challenges in quantifying flow and transport through fractured rocks , 2005 .

[30]  John D. Bredehoeft,et al.  On the analysis of ‘slug test’ data , 1973 .

[31]  G. Marsily,et al.  Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model , 1990 .

[32]  J. Barker.  A generalized radial flow model for hydraulic tests in fractured rock , 1988 .

[33]  Chin-Fu Tsang,et al.  Flow and Contaminant Transport in Fractured Rock , 1993 .

[34]  Frederick D. Day-Lewis,et al.  Identifying fracture‐zone geometry using simulated annealing and hydraulic‐connection data , 2000 .

[35]  Urban Svensson,et al.  A continuum representation of fracture networks. Part II: application to the Äspö Hard Rock laboratory , 2001 .

[36]  J. Carrera,et al.  Mixed Discrete‐Continuum Models: A Summary of Experiences in Test Interpretation and Model Prediction , 2013 .

[37]  Jesús Carrera,et al.  On the relationship between indicators of geostatistical, flow and transport connectivity , 2005 .

[38]  Ivars Neretnieks,et al.  Fluid flow and solute transport in a network of channels , 1993 .

[39]  Joseph F. Atkinson,et al.  Groundwater Flow And Quality Modeling , 2001 .

[40]  Walter A Illman,et al.  Asymptotic Analysis of Cross‐Hole Hydraulic Tests in Fractured Granite , 2006, Ground water.

[41]  C. V. Theis.  The relation between the lowering of the Piezometric surface and the rate and duration of discharge of a well using ground‐water storage , 1935 .

[42]  J. Carrera,et al.  A discussion of scale effects on hydraulic conductivity at a granitic site (El Berrocal, Spain) , 1995 .

[43]  Chin-Fu Tsang,et al.  Tracer transport in a stochastic continuum model of fractured media , 1996 .

[44]  Chin-Fu Tsang,et al.  Flow channeling in strongly heterogeneous porous media: A numerical study , 1994 .

[45]  Björn Dverstorp,et al.  Application of the discrete fracture network concept with field data: Possibilities of model calibration and validation , 1989 .

[46]  William Dershowitz,et al.  Rock joint systems , 1984 .

[47]  S. P. Neuman,et al.  Field Determination of the Three‐Dimensional Hydraulic Conductivity Tensor of Anisotropic Media: 1. Theory , 1985 .

[48]  B. Berkowitz.  Characterizing flow and transport in fractured geological media: A review , 2002 .

[49]  M. Zoback,et al.  Determination of stress orientation and magnitude in deep wells , 2003 .

[50]  X. Sanchez‐Vila,et al.  An evaluation of Jacob's Method for the interpretation of pumping tests in heterogeneous formations , 1998 .