scholarly journals Electrical Resistivity and Porosity of Crystalline Rock Samples From the Kapuskasing Structural Zone, Ontario

1992 ◽  
Author(s):  
T J Katsube ◽  
N Scromeda ◽  
M Mareschal ◽  
R C Bailey
Author(s):  
Т.С. Хачкова ◽  
В.В. Лисица ◽  
Г.В. Решетова ◽  
В.А. Чеверда

Представлен алгоритм расчета потенциального электрического поля в образцах горных пород и предложены оценки их удельного электрического сопротивления (проводимости). Алгоритм ориентирован на расчет поля в существенно неоднородных моделях среды с частично насыщенными и полиминеральными образцами горных пород. В основе алгоритма – итерационные методы крыловского типа, в качестве предобусловливателя используется оператор, обратный к оператору Лапласа для однородной среды. Для вычисления предобусловливателя используется спектральный метод в направлениях, нормальных к основному направлению электрического тока, а серия одномерных задач решается методом прогонки. Решатель реализован с использованием графических процессоров (GPU) и позволяет обрабатывать образцы размером до 4003 вокселей на одном GPU. We present a numerical algorithm for computing the electric field in digital rock samples and estimating their electrical resistivity (conductivity). The main peculiarity of the algorithm is its applicability tostrongly heterogeneous models including partially saturated and multi-mineral rock samples. The algorithm is based on the iterative Krylov-type solver preconditioned by the inverse Laplace operator for homogeneous media. The preconditioner is computed using the spectral method in directions orthogonal to the direction of the main electric current, whereas the series of 1D problems are solved by the Thomas algorithm. We implement the algorithm using GPUs, which allows us to use a single GPU to solve the problems for samples whose size is up to 4003 voxels.


1985 ◽  
Vol 50 ◽  
Author(s):  
Kristina Skagius ◽  
Ivars Neretnieks

AbstractThe diffusion of non-sorbing species in different crystalline rocks and fissure coating materials has been studied. The results show that the effective diffusivity of iodide, Uranine and Cr-EDTA in rock materials with fissure coating material is of the same magnitude or higher than in granites and gneisses. The results also show that it is not possible to assign one value to the diffusivity of a rock from a given area. The variations in properties are too large. The estimated effective diffusivity of iodide in rocks without fissure coating material was found to be in the range 1.10-14 m2/s to 70.10-14 m2/s.To simulate the stress that exists in the bedrock at large depths, diffusion experiments with iodide and electrical resistivity measurements in rock materials under mechanical stress have been performed. It was found that the diffusivity in rock samples at 300–350 bars stress was reduced to 20–70% of the value in samples under atmospheric pressure.


1983 ◽  
Vol 26 ◽  
Author(s):  
Kristina Skagius ◽  
Ivars Neretnieks

ABSTRACTThe diffusion of non-sorbing species in different rock materials and fissure coating materials have been studied. The results show that the effective diffusivity of iodide in granites with fissure coating materials is of the same magnitude or higher as the effective diffusivity for iodide in granites without fissure coating material. Also the porosities of the granites with fissure coating material were higher. The effective diffusivity for iodide in rock materials without fissure coating material was determined to be from 1.i0-14 m2/s to about 7.10-13 m2/s.To simulate the stress that exists in the bedrock at large depths diffusion experiments with iodide in rock materials under mechanical stress, and electrical resistivity measurements in salt-water-saturated rock cores under stress have been started. Electrical resistivity measurements is an indirect method to determine the diffusivity.Results from some initial measurements show that the effective diffusivity is reduced to about 40 % of the value for unstressed samples at pressures of 230-280 bar. This is the expected stress at repository depths.


2017 ◽  
Vol 31 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Ivan Alekseev ◽  
Jakub Kostecki ◽  
Evgeny Abakumov

Abstract The aim of the study was to determine electrical resistivity peculiarities of tundra and forest tundra soils and soil-permafrost layers of the Yamal region. Measurements of electrical resistivity of soil and permafrost strata were performed with a portable device LandMapper (to a depth of 300-500 cm). These measurements allow determination of the values of apparent electrical resistivity of soils and permafrost at different depths and determination of the depths of the permafrost table on each key plot. It was found that there are several trends in vertical distribution of apparent electrical resistivity values. The first trend is a monotonous increase in electrical resistivity values to the depth. It may be explained by the increasing electrical resistivity within the soil depth in relation to the increase in permafrost density. The second trend is a sharp decrease replaced by a gradual increase in electrical resistivity values caused by changing of non-frozen friable debris to frozen massive crystalline rock. These differences were related to the type of landscape: flat lowlands composed of friable grounds underlain by permafrost or friable grounds with permafrost underlain by a rock crystalline layer.


2020 ◽  
Author(s):  
Václava Havlová ◽  
Milan Zuna ◽  
Anna Pecková ◽  
Filip Jankovský

<p>Geochemistry of groundwater within the host rock is one of the most crucial boundary conditions for radionuclide speciation and migration.</p><p>The typical porosity of crystalline rock is less 0,5 wt%. In addition to the circulation of groundwater in the cracks, different types of fluids may be present in the pore space. Total porosity ε<sub>T</sub> - corresponds to the volume of rock not filled with mineral grains. It is often defined by the relation: ε<sub>T</sub> = ε<sub>F</sub> + ε<sub>D </sub>+ ε<sub>R</sub>, where ε<sub>F </sub>stands for effective porosity (the dominant fluid transport is advective flow). ε<sub>D</sub> represents diffusive porosity (the predominant transport in water-filled pores is diffusion) and ε<sub>R</sub> represents residual porosity (discontinuous pores in which no transport takes place), in which solutions may also be present in closed inclusions.</p><p>Most of the solutions contained in the pore space, the "pore fluid of the rock matrix", cannot be collected using conventional groundwater sampling techniques. Only limited number of techniques has been reported, e.g. Smellie et al., (2003); Waber and Smellie (2008) and Eichinger et al. (2008).</p><p>Therefore, determination of pore water chemistry in crystalline rock from underground laboratory Bukov (SÚRAO) in at least 500 m depth was in focus, testing different laboratory and in-situ techniques. Fresh crystalline rock samples from the 12<sup>th</sup> (-550 m) and 24<sup>th</sup> (-1 000 m) horizon of Bukov URL were used for the laboratory experiments. In-situ sampler was installed at undisturbed section of the borehole at URL Bukov.</p><p>Firstly, leaching experiments, inspired by methods mentioned above were performed.</p><p>Secondly, high pressure techniques were used in order to extract pore water from the rock samples.</p><p>Finally, in-situ extraction of rock fluids, using a sampling packer system, installed into the undisturbed rock section, was applied.</p><p>Paralelly, geochemical modelling, using PHREEQC code, considering long-term interaction of main rock constituting minerals with solution in pores, was ongoing.</p><p>The results of in-situ sampling, lab leaching and modelling indicated that the determination of the pore water composition of crystalline rocks is still an open issue, since only about 1.5 ml of groundwater was present in approximately 20 cm of drill core (porosity below 0.5%).</p><p>Its composition will be significantly influenced by the equilibration of the solutions, entering pores, with the main and minor rock components (e.g. sulphites). The composition will most probably move towards the Na-HCO<sub>3</sub>-Cl type with increasing chloride component with increasing depth. Here close communication with depth specific groundwater can be found. However, chlorine source within quartz – plagioclase – biotite – amphibolites rock type is not clear. Geochemical modelling showed that Cl<sup>- </sup>source other than rock forming minerals might have an influence, either residual solutions or fluid inclusions (containing NaCl according to the analyses).</p><p>References:</p><p>Smellie J. et al.. (2003): Technical Report, SKB, TR-03-18.</p><p>Waber, H., Smellie (2008):  Applied Geochemistry 23, 1834-1861.</p><p>Eichinger F. et al. (2008): Project Report, Nagra, NPB 08-16.</p><p>Eichinger F. at al. (2006): Posiva Working Report 2006-103.</p><p>Acknowledgements</p><p>The work described herein was funded by SÚRAO within Deep Horizons project (SO2017-023).</p>


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