1,722,238 research outputs found
Discussion and reply: Reply to the discussion
No full textRevil (2013) contests that the depth from extreme points (DEXP) method could be used to interpret self-potential (SP) data, mainly because he thinks it is incompatible with the physics of SP signals and the specific boundary conditions. However, any reader of our paper would wonder why such an incompatible theoretical ap- proach could work so well: We in fact presented three synthetic cases and three real cases in which the method yields good results, which are also well consistent with the known information. This happens because our approach, contrarily to what is stated by Revil (2013), is physically consistent, based on the same theoretical framework of a number of already published papers (e.g., Bhatta- charya and Roy, 1981; Gibert and Pessel, 2001; Abdelrahman et al., 2008; Agarwal and Srivastava, 2009; Srivastava and Agarwal, 2009; Mauri et al., 2010; and many others). In addition, we find much of the comment does not sufficient consider the new theoreti- cal and practical aspects emerging in our and other imaging meth- ods (e.g., Fedi and Pilkington, 2012)
A sandbox experiment of self-potential signals associated with a pumping test
No full textThe flow of water in a charged porous material is the source of in the relaxation phase following the shutdown of the an electrical field called the streaming potential. The origin of this pump. Despite the fact that the problem is treated here coupling is associated with the drag of the excess of charge contained for a thin tank (two-dimensional approximation), all the in the vicinity of the pore–water interface by the pore fluid flow. In this results obtained in this paper can easily be transposed paper, we present a sandbox experiment to study this “hydroelectric” to the three-dimensional case corresponding to the apcoupling in the case of a pumping test. A relatively thin Plexiglas plication of the method in the field. tank was filled with homogeneous sand and then infiltrated with tapwater. A pumping test experiment was performed in the middle THEORY of the tank with a peristaltic pump. The resulting electrical potential distribution was measured passively at the top of the tank with a net- In this section, we present a model that will be used later work of 27 nonpolarizable electrodes related to a digital multichan- to interpret the sandbox experiment. The porous material is nel multimeter plus an additional electrode used as a reference. A assumed to be isotropic with respect to all the material properdetectable electrical field was produced at the ground surface and ties introduced below. The total electrical density J (A m2) analyzed with analytical solutions of the coupled hydroelectric prob- is the sum of a conductive current given by Ohm’s Law and lem. After the shutdown of the pump, the electrical potential and the a driving current density JS. The latest is associated with the piezometric level exhibit similar relaxation times in the vicinity of the pore fluid pressure field (e.g., Titov et al., 2000, 2002; Revil pumping well. This means that the electrical potential measured at et al., 2003, and references therein). This yields the following the ground surface can be used to track the flow of the groundwater constitutive equation: and possibly to invert the distribution of the hydraulic transmissivity of the ground
Vivre en situation de non-recours frictionnel. Une enquête menée dans trois Caf
No full textMazet Pierre, Revil Héléna. Vivre en situation de non-recours frictionnel. Une enquête menée dans trois Caf. In: Revue des politiques sociales et familiales, n°128, 2018. pp. 51-58
Data for the paper "Field investigation of serpentinite with induced polarization and the K-means clustering technique" by A. Revil, A. Ghorbani, J. Jacquet, S. Barde-Cabusson, H. Chen, J. Richard, P. Vaudelet, G. Ménard, and J.J. Delannoy
No full text<p><span>Readme file for the manuscript entitled “Field investigation of serpentinite with induced polarization and the </span><span>K-means </span><span>clustering technique” by </span><span>A. Revil, A. Ghorbani, </span><span>J. Jacquet, S. Barde-Cabusson, H. Chen, J. Richard, P. Vaudelet, G. Ménard, and J.J. Delannoy. This manuscript has been submitted to Geophysical research letters. The data comprises 4 files. </span></p>
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<p><span>The first two files (Data 1 and Data 2) comprise the geophysical survey as a .DAT file with the apparent resistivity and apparent resistivity data. the format is the classical format to be read by softwares such as RES2DINV. <span>Version 6.2 of the Res2DInv software supporting this research </span></span><span>used for inversion of the apparent resistivity and chargeability data sets</span><span> is available in the Aarhus GeoSoftware website via</span><span> </span><a href="https://www.aarhusgeosoftware.dk/download-resxdinv"><span>https://www.aarhusgeosoftware.dk/download-resxdinv</span></a><span>, under commercial licensing, and is accessible to the public or research community as a demo/display version.</span><span> </span></p>
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<p><span>Data 3 corresponds to the inverted resistivity and chargeability data in an xcel data file. Data 4 corresponds to the complex conductivity spectrum (real and imaginary parts) for the serpentinite core sample investigated in the manuscript. </span></p>
Sandbox Experiments of Self-Potential Signals Associated With Pumping Tests
No full textSandbox Experiments of Self-Potential Signals Associated With Pumping Test
Reply to comment by D. Gibert and P. Sailhac on ''Self-potential signals associated with preferential groundwater flow pathways in sinkholes
No full textInternational audienceJardani et al. [2006a] analyzed self-potential signals associated with the shallow groundwater flow in sinkholes. These signals were electrokinetic in nature resulting from the percolation of water in the ground and the drag of the excess of electrical charge that is present in the bulk pore water [e.g., Leroy and Revil, 2004]. Using the formulation of the electrokinetic coupling introduced by Revil and Leroy [2004] (and extended rece tly to unsaturated flow by Revil et al. [2007] and Linde et al. [2007] and to the inertial laminar flow regime by Bole've et al. [2007]), the electrical potential can be obtained from the solution of the Poisson equation. In this equation, the source term is equal to the divergence of the streaming current density, which in turn is equal to the excess of charge per unit pore volume time the seepage velocity. Generalizing the work by Revil et al. [2003b], Jardani et al. [2006a] used a cross-correlation method to reconstruct the possible shapes of the water table and to locate sinkholes at depth. [2] Numerical simulations of self-potential signals associated with the flow of the groundwater shows the dipolar character of the source [e.g., Revil et al., 1999; Bole've et al., 2007]. In a multipole development of the self-potential field, the monopole contribution is equal to zero because of the global electroneutrality condition prevailing in porous materials. Therefore the leading term is the dipolar field. [3] If the support volume of the source is small or if the sources are located along an interface (like the water table), it is possible to use the cross-correlation method to determine the position of the source or to image this interface by optimizing the semblance between the selfpotential anomaly, normalized by its power, and the signal modeled with the appropriate Green function [see Birch, 1993, 1998]. The Green's function can be computed analytically for a homogeneous ground but it can be also computed numerically accounting for the real (or inverted) electrical resistivity distribution and appropriate boundary conditions for the self-potential field. The cross-correlation approach has been used as a source localization method in acoustic [e.g., Omologo and Svaizer, 1994; Thomann, 1996], in seismology [e.g., Saccorotti and Del Pezzo, 2000], in magnetoencephalography [e.g., Cao et al., 2002], and in the localization of contaminant plumes in the atmosphere [e.g., Roussel et al., 2002], just to cite few of them. This is therefore not a new approach. We discuss below the validity of this approach to self-potential data. Note that this approach was also used very successfully by Revil et al. [2001], Iuliano et al. [2002], and Revil et al. [2003a, 2003b] and recently by Jardani et al. [2006b] and Bhattacharyal et al. [2007] to localize the causative source of self-potential anomalies. Finally, we will discuss briefly future exciting trends in the inversion of self-potential signals
Diffusion of ionic tracers in the Callovo-Oxfordian clay-rock using the Donnan equilibrium model and the formation factor
No full textInternational audienceThe transient diffusion of cationic and anionic tracers through clay-rocks is usually modeled with parameters like porosity, tortuosity (and/or constrictivity), sorption coefficients, and anionic exclusion. Recently, a new pore scale model has been developed by Revil and Linde [Revil A. and Linde N. (2006) Chemico-electromechanical coupling in microporous media. J. Colloid Interface Sci. 302, 682–694]. This model is based on a volume-averaging approach of the Nernst–Planck equation. The influence of the electrical diffuse layer is accounted for by a generalized Donnan equilibrium model through the whole connected pore space that is valid for a multicomponent electrolyte. This new model can be used to determine the composition of the pore water of the Callovo-Oxfordian clay-rock, the osmotic efficiency of bentonite as a function of salinity, the osmotic pressure, and the streaming potential coupling coefficient of clay-rocks. This pore scale model is used here to model the transient diffusion of ionic tracers ( 22Na+, 36C
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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