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Effective porosity

About: Effective porosity is a research topic. Over the lifetime, 1199 publications have been published within this topic receiving 26511 citations.


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Journal ArticleDOI
TL;DR: In this article, the authors measured diffusion coefficients for 14C (in the form of carbonate) in bentonite compacted to a series of dry bulk densities, ranging from about 0.9 to 1.6 Mg/m3.
Abstract: Diffusion coefficients are critical parameters for predicting migration rates and fluxes of contaminants through clay-based barrier materials used in many waste containment strategies. Cabon-14 is present in high-level nuclear fuel waste and also in many low-level wastes such as those generated from some medical research activities. Diffusion coefficients were measured for14C (in the form of carbonate) in bentonite compacted to a series of dry bulk densities,ρb, ranging from about 0.9 to 1.6 Mg/m3. The clay was saturated with a Na-Ca-Cl-dominated groundwater solution typical of those found deep in plutonic rock on the Canadian Shield. Both effective,De, and apparent,Da, diffusion coefficients were determined.De is defined asD0Τane, where D0 is the diffusion coefficient in pure bulk water,Τa the apparent tortuosity factor, andne the effective porosity available for diffusion; andDa is defined asD0Τane/(ne+ρbKd), where Kd is the solid/liquid distribution coefficient. BothDe andDa decrease with increasingρb:De values range from about 10×10−12 m2/s atρb≃0.9 Mg/m3 to 0.6×10−12 m2/s at 1.6 Mg/m3, andDa values vary from approximately 40×10−12 to 4×10−12 m2/s over the same density range. The decrease inDe andDa is attributed to a decrease in bothΤa andne asρb increases. The data indicate thatne is <10% of the total solution-filled porosity of the clay at all densities.Kd values for14C with the clay range from about 0.3 to <0.1 m3/Mg; this indicates there is a small amount of14C sorbed on the clay and/or some14C is isotopically exchanged with12C in carbonate phases present in the clay. Finally, theDe values for14C are lower than those of other diffusants — I−, Cl−, TcO4−, and Cs+ — that have been measured in this clay and pore-water solution. This is attributed to lower values for bothne andD0 for14C species relative to those of the other diffusants.

15 citations

Journal ArticleDOI
TL;DR: In this paper, a modified Kozeny-Carman model is proposed to estimate the anisotropic permeability of soft mudrocks with emphasis on micro-level mechanisms.

15 citations

Journal ArticleDOI
TL;DR: In this article, the authors compared different experimental methods for measuring water permeability in 17 different porous building rocks and found that for very low and low permeability samples (k −6 m/s), triaxial conditions were found the most accurate procedures and they provided similar or slightly lower permeability values than constant and falling head methods.
Abstract: This paper compares different experimental methods for measuring water permeability in 17 different porous building rocks. Both commercial apparatus and specially made designed permeameters are used for characterising intrinsic permeability and hydraulic conductivity, k, of rocks in the range of 10 −12 to 10 −4 m/s (~ 10 −19 −10 −11 m 2 or ~ 10 −4 −10 4 mD). We use both falling head and constant head permeameter methods including the triaxial and modified triaxial tests and a classical constant head permeameter. Results showed that for very low and low permeability samples (k −6 m/s), triaxial conditions were found the most accurate procedures and they provided similar or slightly lower permeability values than constant and falling head methods. The latter techniques were highly recommended for permeable and high permeable porous building materials. Water permeability values were also linked to effective porosity and interpreted in terms of interparticle and vugs porosity. Finally, some modifications in the apparatus and procedures were carried out in order to assess water permeability in soft materials, which involve the use of non-saturated samples.

15 citations

Proceedings ArticleDOI
TL;DR: Goodway et al. as mentioned in this paper proposed a new improved fluid detection and lithology discrimination indicator using petrophysical parameters and where and are Lame's constants (incompressibility and rigidity) and is density.
Abstract: Introduction Upper Mannville aged strata in southern Alberta consist of a complex lithologic assemblage of narrow shoestring like “Glauconite” and “Lithic” valley-systems trending roughly north-south and variably cutting down into older regional Glauconite, Ostracod and Basal Quartz strata. These valley systems are commonly filled with hydrocarbon-bearing sandstones with varying reservoir quality. In the study area, the Glauconite valley systems are up to 35 meters deep, 2 kilometres wide and several tens of kilometres long. The younger “Lithic” valleysystems generally follow the same trend as the Glauconite valleys and are up to 40 meters deep, 3 to 4 kilometres wide and also several tens of kilometres long. In 1996, a 3D seismic survey was acquired over the valley trends to image reservoir quality sands. It is often difficult to seismically distinguish between Glauconite sand and Ostracod shale by using poststack amplitudes. Improved techniques from recent prestack seismic work suggest that AVO (Amplitude Versus Offset) might be an effective way to extract rock properties and detect gas (Smith and Gidlow, 1987; Gidlow et al., 1992; Fatti et al., 1994, Goodway et al., 1997). Smith and Gidlow (1987), Gidlow et al(1992) and Fatti et al. (1994) proposed a method to create a display which highlights the Vp/Vs ratio anomaly (often caused by the presence of gas) by using the so called “fluid factor stack”. Goodway et al. (1997) proposed a new improved fluid detection and lithology discrimination indicator using petrophysical parameters and where and are Lame’s constants (incompressibility and rigidity) and is density. The geological and geophysical effort in this area is to determine where the two valleys are present, and to differentiate sands from shale. Geology and Reservoir Quality Log analysis and core data, where available, indicate that the Glauconite sandstones generally have good to excellent reservoir quality whereas the Lithic sandstones are generally moderate to poor quality rocks. For example, the Glauconite sandstones in well B (Figures 1 & 2) have core porosities ranging from 18 to 26% and permeabilities ranging from 948 to 4900 md.. In contrast, the Lithic sandstones in well C (Figure 1) have core porosities ranging from 10 to 14% and permeabilities from 1 to 40 md.. Glauconite channels in the study area produce both oil and gas whereas Lithic channels produce primarily gas. The differences in reservoir quality between the Glauconite and Lithic channels are related to major differences in sandstone framework grain composition. Sedimentological interpretations from available core indicate that the Glauconite and Lithic channels consist predominantly of fine to medium grained fluvial sandstone at the base and grade upwards into finer grained marine influenced (estuarine) deposits at the top. Typical regional, non-channel, deposits in this area can be seen in wells A & D in Figure 1. The Ostracod interval, which consists of shale and limestone is a significant regionally extensive stratigraphic marker. Absence of the Ostracod is one of the key correlation indicators for downwards incision by overlying Glauc and Lithic channels. Petrophysical Analysis and Lame Parameters Petrophysical parameters for “complex” lithology, porosity, and fluid saturations were modeled. A rather complete log-data set including density, neutron, sonic, gamma ray and magnetic resonance logs permitted a comprehensive model to be developed and correlated to core lithology, porosity and saturation data. This “complex” lithology model is required to account for bitumen, gas, irreducible water and intraparticle porosity evident in the log, core and thin section data. Magnetic resonance data enables meaningful evaluation of bitumen and irreducible water in this lithology. Model parameter selection is constrained by comparison of model results to core lithology, porosity and fluid saturations. The petrophysical model illustrated by figure 2 for well B shows a clean quartz rich sand lithology having a maximum effective porosity of 0.26 (core porosity overlaid in red). The porosity match deviates in intervals where intraparticle porosity is not included in the core porosity. Effective porosity is reduced by shaliness at the top and by bitumen at the base of the sand. Modeled hydrocarbon saturation is overlain by core oil saturation (in red). The saturation curves correspond in intervals containing residual oil and deviate in gas bearing intervals.

15 citations

Journal ArticleDOI
TL;DR: In this article, the split Hopkinson pressure bar testing method was used to quantify the dynamic strength characteristics of rocks with short cylindrical specimens, and the results showed that the dynamic compressive strength of rocks increases with increase in loading rate and/or increase in rock property values except porosity.
Abstract: In this study, the split Hopkinson pressure bar testing method was used to quantify the dynamic strength characteristics of rocks with short cylindrical specimens. Seventy dynamic compression tests were conducted on 10 different carbonate rocks with the split Hopkinson pressure bar apparatus. Experimental procedure for testing dynamic compressive strength and elastic behaviour of rock material at high strain rate loading is presented in the paper. Pulse-shaper technique was adopted to obtain dynamic stress equilibrium at the ends of the sample and to provide nearly a constant strain rate during the dynamic loading. In addition to dynamic tests, the physical properties covering bulk density, effective porosity, P-wave velocity and Schmidt hardness of rocks, and mechanical properties such as quasi-static compressive strength and tensile strength were determined through standard testing methods. Multiple linear regression analyses were carried out to investigate the variation of dynamic compressive strength depending on physical and mechanical properties of rocks and loading rate. A three parameter model was found to be simple and provided the best surface fit to data. It was found that dynamic compressive strength of rocks increases with increase in loading rate and/or increase in rock property values except porosity. Statistical tests of regression results showed that quasi-static compressive strength and Schmidt hardness are most significant rock properties to adequately predict the dynamic compressive strength value among the other properties. However, P-wave velocity, quasi-static tensile strength of rocks could also be used to estimate the dynamic compressive strength value of rocks, as well, except the bulk density and effective porosity.

15 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202232
202162
202065
201971
201847