Experimental Study of Some Hydrogeophysical Properties of Unconsolidated Porous Media

Biella, G.; Lozej, A.; Tabacco, Ignazio

doi:10.1111/j.1745-6584.1983.tb01945.x

Cited by 70 publications

(39 citation statements)

References 21 publications

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“…Our task in this discussion is to identify the origin of the PWB breakdown. The granular materials investigated by Biella and Tabacco (1981), Biella et al (1983), Glover and Walker (2009) and Glover and Déry (2010) cover nearly three orders of magnitude in grain size and nevertheless display very narrow ranges of porosity (0.37 to 0.41, except a couple of outliers as high as 0.45) and formation factor (4 to 5). This insensitivity to grain size demonstrates that these materials have essentially identical pore structures, characterized by nearly constant scale-invariant factors.…”

Section: Discussionmentioning

confidence: 99%

“…1b). Compilation of published experimental data, a) k versus /, b) F versus / and c) k versus F, in unconsolidated monodisperse glass beads (Glover and Walker, 2009;Glover and Déry, 2010; black dots), well-sorted, rounded sands (Biella and Tabacco, 1981;Biella et al, 1983; blue dots), sintered glass beads (Wong et al, 1984;Guyon et al, 1987;Li et al, 1995;Blair et al, 1996; purple, red and orange squares corresponding to different grain sizes as indicated in the inset) and Fontainebleau sandstone (Doyen, 1988;Fredrich et al, 1993;Zamora, unpublished data;black diamonds;Revil et al, 2014; grey diamonds). The colored lines are inserted to highlight power-law trends in the various materials (note that the three families of sintered glass obey fairly similar power laws).…”

Section: Sintered Glass Beadsmentioning

confidence: 99%

“…The same should be approximately true of unconsolidated packs of well-sorted, slightly non-spherical particles. To test this we considered the experimental data collected on unconsolidated packs of monodisperse spherical glass beads (Glover and Walker, 2009;Glover and Déry, 2010) and well-sorted, rounded sands (Biella and Tabacco, 1981;Biella et al, 1983). These datasets include values of porosity, grain radius, permeability and formation factor (note that F was measured in the high salinity limit, with negligible surface conduction).…”

Section: Unconsolidated Glass Beads and Sandmentioning

confidence: 99%

“…However, in addition to being slightly elongated or flattened (roughly corresponding to prolate or oblate ellipsoids), sand grains have irregular, uneven surfaces that further increase A G and therefore f G . Since the Biella and Tabacco (1981) and Biella et al (1983) sands were described as rounded, we only increased f G by a limited amount. Our final f G estimates ranged from about 1.5 for the coarsest sands to 1.9 for the finest ones.…”

Section: Unconsolidated Glass Beads and Sandmentioning

confidence: 99%

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Pore Space Connectivity and the Transport Properties of Rocks

Bernabé

Tang

et al. 2016

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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-Pore connectivity is likely one of the most important factors affecting the permeability of reservoir rocks. Furthermore, connectivity effects are not restricted to materials approaching a percolation transition but can continuously and gradually occur in rocks undergoing geological processes such as mechanical and chemical diagenesis. In this study, we compiled sets of published measurements of porosity, permeability and formation factor, performed in samples of unconsolidated granular aggregates, in which connectivity does not change, and in two other materials, sintered glass beads and Fontainebleau sandstone, in which connectivity does change. We compared these data to the predictions of a Kozeny-Carman model of permeability, which does not account for variations in connectivity, and to those of Bernabé et al. (2010Bernabé et al. ( , 2011 ]. Both models agreed equally well with experimental data obtained in unconsolidated granular media. But, in the other materials, especially in the low porosity samples that had undergone the greatest amount of sintering or diagenesis, only Bernabé et al. model matched the experimental data satisfactorily. In comparison, predictions of the Kozeny-Carman model differed by orders of magnitude. The advantage of the Bernabé et al. model was its ability to account for a continuous, gradual reduction in pore connectivity during sintering or diagenesis. Although we can only speculate at this juncture about the mechanisms responsible for the connectivity reduction, we propose two possible mechanisms, likely to be active at different stages of sintering and diagenesis, and thus allowing the gradual evolution observed experimentally.Résumé -Connectivité de l'espace poreux et propriétés de transport des roches -La connectivité porale est probablement l'un des plus importants facteurs affectant la perméabilité des roches réservoir. En outre, les effets de connectivité ne sont pas limités aux seuls matériaux approchant un seuil de percolation mais peuvent avoir lieu progressivement dans des roches soumises à des processus tels que la diagénèse mécanique ou chimique. Dans cette étude, nous avons compilé plusieurs jeux, préalablement publiés, de mesures de porosité, perméabilité et facteur de formation, obtenues sur des agrégats granulaires non-consolidés, pour lesquels la connectivité ne change pas, ainsi que dans deux autres matériaux, billes de verre frittées et grès de Fontainebleau, pour lesquels elle varie. Nous avons comparé ces données aux prédictions d'un modèle de perméabilité de type Kozeny-Carman, qui ne tient pas compte des variations de connectivité, et à celles du modèle de Bernabé et al. (2010Bernabé et al. ( , 2011

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Section: Discussionmentioning

confidence: 99%

Section: Sintered Glass Beadsmentioning

confidence: 99%

Section: Unconsolidated Glass Beads and Sandmentioning

confidence: 99%

Section: Unconsolidated Glass Beads and Sandmentioning

confidence: 99%

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Pore Space Connectivity and the Transport Properties of Rocks

Bernabé

Tang

et al. 2016

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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“…Using a perfect relationship to generate resistivity from hydraulic conductivity must be characterized as the ideal case because in this case electrical resistivity data can be expected to provide maximal information about hydraulic conductivity. In practice, when possible, estimation of hydraulic conductivity from electrical resistivity is usually based on a site-specific noisy linear log-log relationship (see, e.g., Mazáč et al, 1985;Revil and Cathles, 1999;Purvance and Andricevic, 2000;Slater, 2007), which has been found to be a positive relationship in some cases (Urish, 1981;Frohlich and Kelly, 1985), and a negative relationship in other cases (Worthington, 1975;Heigold et al, 1979;Biella et al, 1983).…”

Section: Reference Geophysical System and Data -Stepmentioning

confidence: 99%

Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

Christensen¹,

Christensen²,

Ferré³

2016

Hydrol. Earth Syst. Sci.

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Abstract. In spite of geophysics being used increasingly, it is often unclear how and when the integration of geophysical data and models can best improve the construction and predictive capability of groundwater models. This paper uses a newly developed HYdrogeophysical TEst-Bench (HYTEB) that is a collection of geological, groundwater and geophysical modeling and inversion software to demonstrate alternative uses of electromagnetic (EM) data for groundwater modeling in a hydrogeological environment consisting of various types of glacial deposits with typical hydraulic conductivities and electrical resistivities covering impermeable bedrock with low resistivity (clay). The synthetic 3-D reference system is designed so that there is a perfect relationship between hydraulic conductivity and electrical resistivity. For this system it is investigated to what extent groundwater model calibration and, often more importantly, model predictions can be improved by including in the calibration process electrical resistivity estimates obtained from TEM data. In all calibration cases, the hydraulic conductivity field is highly parameterized and the estimation is stabilized by (in most cases) geophysics-based regularization.For the studied system and inversion approaches it is found that resistivities estimated by sequential hydrogeophysical inversion (SHI) or joint hydrogeophysical inversion (JHI) should be used with caution as estimators of hydraulic conductivity or as regularization means for subsequent hydrological inversion. The limited groundwater model improvement obtained by using the geophysical data probably mainly arises from the way these data are used here: the alternative inversion approaches propagate geophysical estimation errors into the hydrologic model parameters. It was expected that JHI would compensate for this, but the hydrologic data were apparently insufficient to secure such compensation. With respect to reducing model prediction error, it depends on the type of prediction whether it has value to include geophysics in a joint or sequential hydrogeophysical model calibration. It is found that all calibrated models are good predictors of hydraulic head. When the stress situation is changed from that of the hydrologic calibration data, then all models make biased predictions of head change. All calibrated models turn out to be very poor predictors of the pumping well's recharge area and groundwater age. The reason for this is that distributed recharge is parameterized as depending on estimated hydraulic conductivity of the upper model layer, which tends to be underestimated. Another important insight from our analysis is thus that either recharge should be parameterized and estimated in a different way, or other types of data should be added to better constrain the recharge estimates.

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Observation network design for selecting locations for water supply wells

1994

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SUMMARYAn observation network design method, which simultaneously minimizes parameter uncertainty and exploration cost, is developed for locating water supply wells. Observation networks combining wells and geophysical measurements are considered for delineating the 'best' areas for wells. An area is considered the 'best' where the sustainable pumping rate and the degree of protection for the well are the possible maximum. The level of protection is measured by the travel time for a fixed radius protection zone around a well. The 'most appropriate' measurement network is selected based on two often conflicting objectives:(1) minimization of the uncertainty in characterizing the spatial distribution of the expected yield and travel time; and (2) minimization of the observation cost. The accuracy of estimation is characterized by the average and maximum kriging variance for yields and travel times calculated from measured hydrogeologic parameters. The parameters to be measured by an observation network for estimating yields and travel times are layer thicknesses, porosity, hydraulic conductivity and volumetric water content. They may be obtained from direct measurements (e.g. well logs, specific capacity test, and pumping tests) or estimated indirectly from geoelectric measurements. The approach combines two common techniques, geostatistics and multi-criterion decision making (MCDM), to determine the 'best' measurement network. Geostatistics are used to determine the spatial distribution of the estimation variance for yield and travel time calculated from different sources of data. MCDM is utilized to evaluate observation network alternatives based on the estimation variances and the costs associated with them. The methodology is illustrated for a study area located near Ashland, Nebraska.

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Experimental Study of Some Hydrogeophysical Properties of Unconsolidated Porous Media

Cited by 70 publications

References 21 publications

Pore Space Connectivity and the Transport Properties of Rocks

Pore Space Connectivity and the Transport Properties of Rocks

Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

Observation network design for selecting locations for water supply wells

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