Spatial Distribution Of Physical Properties Research Articles

Comparison Between Hydraulic Conductivity Anisotropy and Electrical Resistivity Anisotropy From Tomography Inverse Modeling

Hydrogeophysics is increasingly used to understand groundwater flow and contaminant transport, essential basis for groundwater resources forecast, management and remediation. It has proven its ability to improve the characterization of the hydraulic conductivity (\textit{K}) when used along with hydrogeological knowledge. Geophysical tools and methods provide high density information of the spatial distribution of physical properties in the ground at relatively low costs and in a non-destructive manner. Amongst them, the Electrical Resistivity Tomography (ERT) has been widely used for its high spatial coverage and for the strong theoretical links between electrical resistivity ($\rho$) and key hydrogeological parameters such as \textit{K}. Historically, ERT data processing was based on isotropic hypothesis. However, the unconsolidated aquifers in Canada reveal in most cases a strong anisotropic behaviour for \textit{K} both with \textit{in situ} or laboratory measurements. Recently, electrical anisotropy has been considered model-wise, but it is seldom considered as an interpretation tool or in the characterization process of the anisotropy of \textit{K}. In order to evaluate the potential of ERT to assess the anisotropy of electrical resistivity, we developed a forward and inverse modeling code. These codes have been validated and tested on a realistic synthetic case reproducing the behaviour of a real aquifer extensively characterized, the site of Saint-Lambert-de-Lauzon in Quebec (Canada). On this site, innovative \textit{in situ} hydraulic tomography has revealed a strong anisotropy, with up to three orders of magnitude between horizontal and vertical \textit{K} components. In order to confirm the link between \textit{in situ} \textit{K}- and $\rho$-anisotropies, an ERT survey has been performed, using the same wells as for the hydraulic tomography. The inversion confirms a strong link between \textit{K}- and $\rho$-anisotropies. It demonstrates the suitability of the anisotropic ERT approach coupled with well measurements to provide better estimates of \textit{K} and its anisotropy at the scale of a site.

Characterization and Monitoring of Porous Media with Electrical Imaging: A Review

Electrical geophysical imaging is a widely used noninvasive technology for visualizing porous media at scales larger than individual pores. Originally developed for medical applications, the technology has been applied to investigate flow and transport properties/processes in a wide range of fields including earth sciences, civil and environmental engineering, agricultural sciences and biology. Conventional electrical imaging measures electrical conduction processes occurring through the fluids filling the interconnected pores and within the electrical double layer at the solid–fluid interface. Complex electrical imaging, an extension of the methodology, also measures electrical polarization processes within the electric double layer and in the presence of metals. Electrical imaging has been used to determine the spatial distribution of physical properties controlling flow/transport in porous media, image fluid dynamics, observe solute transport phenomena and capture matrix transformations. The method has been applied to investigate porous media processes in soils, rocks, concrete, engineered barriers, wastewater filters and living trees. Advances in the technology will result from (1) improving the understanding of the relationship of complex conductivity measurements to more processes occurring in porous media and (2) developing new instrumentation that will support longer-term autonomous electrical monitoring.

CFD MODELING OF HEAT TRANSFER UNDER FLOW OF SUPERCRITICAL PARAMETERS WATER IN VERTICAL BARE TUBES

The results of the CFD modeling of heat transfer under condition of the upstream flow of supercritical water in vertical bare tubes are presented with a change in the wide range of mass flux and heat flux at the channel wall. The results of comparison of experimental and calculated data for different heat transfer regimes - improved, normal and deteriorated - are presented. The results of the CFD modeling relating to the spatial distribution of physical properties of supercritical water are analyzed.

Reservoir characterization and inversion uncertainty via a family of particle swarm optimizers

History matching provides to reservoir engineers an improved spatial distribution of physical properties to be used in forecasting the reservoir response for field management. The ill-posed character of the history-matching problem yields nonuniqueness and numerical instabilities that increase with the reservoir complexity. These features might cause local optimization methods to provide unpredictable results not being able to discriminate among the multiple models that fit the observed data (production history). Also, the high dimensionality of the inverse problem impedes estimation of uncertainties using classical Markov-chain Monte Carlo methods. We attenuated the ill-conditioned character of this history-matching inverse problem by reducing the model complexity using a spatial principal component basis and by combining as observables flow production measurements and time-lapse seismic crosswell tomographic images. Additionally the inverse problem was solved in a stochastic framework. For this purpose, we used a family of particle swarm optimization (PSO) optimizers that have been deduced from a physical analogy of the swarm system. For a synthetic sand-and-shale reservoir, we analyzed the performance of the different PSO optimizers, both in terms of exploration and convergence rate for two different reservoir models with different complexity and under the presence of different levels of white Gaussian noise added to the synthetic observed data. We demonstrated that PSO optimizers have a very good convergence rate for this example, and provide in addition, approximate measures of uncertainty around the optimum facies model. The PSO algorithms are robust in presence of noise, which is always the case for real data.

Estimating the timing and location of shallow rainfall‐induced landslides using a model for transient, unsaturated infiltration

Shallow rainfall‐induced landslides commonly occur under conditions of transient infiltration into initially unsaturated soils. In an effort to predict the timing and location of such landslides, we developed a model of the infiltration process using a two‐layer system that consists of an unsaturated zone above a saturated zone and implemented this model in a geographic information system (GIS) framework. The model links analytical solutions for transient, unsaturated, vertical infiltration above the water table to pressure‐diffusion solutions for pressure changes below the water table. The solutions are coupled through a transient water table that rises as water accumulates at the base of the unsaturated zone. This scheme, though limited to simplified soil‐water characteristics and moist initial conditions, greatly improves computational efficiency over numerical models in spatially distributed modeling applications. Pore pressures computed by these coupled models are subsequently used in one‐dimensional slope‐stability computations to estimate the timing and locations of slope failures. Applied over a digital landscape near Seattle, Washington, for an hourly rainfall history known to trigger shallow landslides, the model computes a factor of safety for each grid cell at any time during a rainstorm. The unsaturated layer attenuates and delays the rainfall‐induced pore‐pressure response of the model at depth, consistent with observations at an instrumented hillside near Edmonds, Washington. This attenuation results in realistic estimates of timing for the onset of slope instability (7 h earlier than observed landslides, on average). By considering the spatial distribution of physical properties, the model predicts the primary source areas of landslides.

Morphological classification of galaxies and its relation to physical properties

We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies approaches the problem separately through either morphological classification or, in more recent times, through analysis of physical properties. A combined approach has significant potential in producing a consistent and accurate classification scheme as well as shedding light on the origin and evolution of galaxy morphology. Here we present an analysis of a volume limited sample of 31703 galaxies from the fourth data release of the Sloan Digital Sky Survey. We use an image analysis method called Pixel-z to extract the underlying physical properties of the galaxies, which is then quantified using the concentration, asymmetry and clumpiness (CAS) parameters. The galaxies also have their multiwavelength morphologies quantified using QMM, and these results are then related to the distributed physical properties through a regression analysis. We show that this method can be used to relate the spatial distribution of physical properties with the morphological properties of galaxies.

Under the Volcano: Unsaturated Flow and Induced Variations of Electromagnetic and Gravitational Fields

A number of electric and magnetic signals have been observed on La Fournaise volcano, which are attributed to electrokinetic effects induced by the heavy rains which fall in this area. A general modeling of the flow in the unsaturated and saturated zones is proposed for an arbitrary topography, arbitrary spatial distributions of physical properties, and arbitrary rains. This flow generates an electrical field and an associated current which itself induces a variable magnetic field. Variations of water masses inside the volcano are also determined to predict gravity variations. Saturation, electric, magnetic, and gravity fields are given and discussed for various rain distributions including real ones.

Microenvironmental heterogeneity of physical soil properties in a broad-leaved Pinus koraiensis forest gap

Microenvironmental heterogeneity of soil physical properties in 0–20 cm and 20–40 cm soil layers in a broad-leaved Pinus koraiensis forest gap in Xiao Xing’anling Mountains were analyzed by geostatistical method. The results show that the amount of soil water, saturation water capacity, capillary water capacity and porosity in the top layer were greater than those in the lower layer, except for bulk density, where the opposite applied. Soil physical properties in the top soil layer had relatively higher ranges and coefficients of variation. The total and auto correlation spatial heterogeneity of soil physical properties in the top layer were larger than those in the lower layer. The soil water had a strong anisotropic structure in an easterly and northerly direction, but porosity shows isotropy in the same directions. With increasing spatial distance, the other three physical factors exhibited anisotropic structures. The mutual effect between semi-variograms of soil physical properties in the top layer within the spatial autocorrelation range was not significant. For spatial distribution of physical properties within different layers, the patches at the middle and lower ranks in the forest gap dominated. Patches at higher rank were only distributed in the 0–20 cm soil layer and were located north of the forest gap center.

Two-dimensional properties of nearby galaxies

Research on two-dimensional (2-D) properties of galaxies is a significant component of the study of galaxy formation and evolution. Through the spatial distribution of physical properties (derived from integrated luminosity and spectroscopy) of galaxies, we are allowed to realize the inner environment and evolution history of each individual galaxy and finally answer how galaxies were assembled. In this paper, with reviewing previous work, we present a proposal for study on 2-D properties of nearby galaxies. In our prospective work, we will make use of multi-wavelength data covering a range from ultraviolet to far-infrared to determine the distributions of properties such as age, metallicity and dust-reddening in nearby galaxies, and try to remove the degeneracy among them. Combining with surface photometry and spectroscopy, we will also analyze the distribution of HII regions and star formation properties in galaxies. In our future plan, the World Space Observatory for Ultraviolet (WSO/UV) will be applied to our research and allow detail diagnosis of nearby galaxies at ultraviolet band.

Spectrophotometry of Star-forming Regions in HiiGalaxies

We present spectrophotometric observations of 111 H II galaxies selected from various surveys. Apart from the integrated spectra, we present emission-line fluxes and equivalent widths of different star-forming knots for 33 galaxies for which the spatial distribution of physical properties can be assessed. Most of the objects have been observed previously. We reobserved these galaxies with uniform instrumentation, and data reduction was performed with homogeneous methods. Our analysis of the quality of the data indicates that our observations reach good signal-to-noise ratio over the whole spectral range, allowing the measurement of—and the inclusion of additional—low-intensity emission lines.

Nanoscale Mapping of the Elasticity of Microbial Cells by Atomic Force Microscopy

Single microbial cells can show important local variations of elasticity due to the complex, anisotropic composition of their walls. An example of this is the yeast during cell division, where chitin is known to accumulate in the localized region of the cell wall involved in budding. We used atomic force microscopy (AFM) to measure quantitatively the local mechanical properties of hydrated yeast cells. Topographic images and spatially resolved force maps revealed significant lateral variations of elasticity across the cell surface, the bud scar region being significantly stiffer than the surrounding cell wall. To get quantitative information on sample elasticity, force curves were converted into force vs indentation curves. The curves were then fitted with the Hertz model, yielding Young's modulus values of 6.1 +/- 2.4 and 0.6 +/- 0.4 MPa for the bud scar and surrounding cell surface, respectively. These data lead us to conclude that in yeast, the bud scar is 10 times stiffer than the surrounding cell wall, a finding which is consistent with the accumulation of chitin in the bud scar region. This is the first report in which spatially resolved AFM force curves are used to distinguish regions of different elasticity at the surface of single microbial cells in relation with function (i.e., cell division). In future research, this approach will provide fundamental insights into the spatial distribution of physical properties at heterogeneous microbial cell surfaces.

A Bayesian criterion for simplicity in inverse problem parametrization

Summary To solve a geophysical inverse problem in practice means using noisy measurements to estimate a finite number of parameters. These parameters in turn describe a continuous spatial distribution of physical properties. (For example, the continuous solution may be expressed as the linear combination of a number of orthogonal functions; the parameters are the coefficients multiplying each of these functions.) As the solution is non-unique, estimating the parameters of interest also requires a measure of their uncertainty for the given data. In a Bayesian approach, this uncertainty is quantified by the posterior probability density function (pdf) of the parameters. This ‘parameter estimation’, however, can only be carried out for a given way of parametrizing the problem; choosing a parametrization is the ‘model selection’ problem. The purpose of this paper is to illustrate a Bayesian model selection criterion that ranks different parametrizations from their posterior probability for the given set of geophysical measurements. This posterior probability is computed using Bayes’ rule and is higher for parametrizations that better fit the data, which are simple in that they have fewer free parameters, and which result in a posterior pdf that departs the least from what is expected a priori. Bayesian model selection is illustrated for a gravitational edge effect inverse problem, where the variation of density contrast with depth is to be inferred from gravity gradient measurements at the surface. Two parametrizations of the density contrast are examined, where the parameters are the coefficients of an orthogonal function expansion or the values at the nodes of a cubic spline interpolation. Bayesian model selection allows one to decide how many free parameters should be used in either parametrization and which of the two parametrizations is preferred given the data. While the illustration used here is for a simple linear problem, the proposed Bayesian criterion can be extended to the general non-linear case.

Velocity anomalies and spatial distributions of physical properties in horizontally lying slabs beneath the Northwestern Pacific region

We calculated velocity anomalies by constructing thermal structural models of horizontally lying slabs beneath Kuriles, Central Japan, Northern Izu–Bonin and Central Izu–Bonin arcs. The values of V p and V s anomalies become maximum in the depth range of 100 to 200 km within the slabs, reaching 5 to 6.4% for V p anomalies and 7 to 8.5% for V s anomalies. The calculated V s anomalies are larger than the V p anomalies, and the ratio of the former to the latter is 1.2 to 1.5 within the slab. This suggests that V s anomalies are more sensitive to temperature variation than V p anomalies, indicating that the existence of the horizontally lying slabs is detectable in more detail by using S-wave. We also calculated spatial distributions of physical properties in the horizontally lying slabs beneath the four regions. In the calculation, we assumed that the material of the slabs consists of olivine (Mg 0.89Fe 0.11) 2SiO 4. The estimated values of physical properties within the slabs are larger than those in the surrounding upper mantle, except for Poisson's ratio, while the values within the metastable wedge of olivine become smaller. This is most remarkable within the slab beneath the Central Izu–Bonin arc due to the lowest temperature among the four regions. The horizontally lying slab above the 660 km seismic discontinuity beneath the Central Izu–Bonin arc is denser up to 60 kg/m 3 and the slab within the metastable wedge of olivine is lighter up to −120 kg/m 3. The values of the physical properties, except for Poisson's ratio, decrease with increasing the horizontal distances of the horizontally lying portions of the slabs. This is due to thermal assimilation, which is largely dependent on moving velocity of the slabs.

In‐situ induced‐polarization and magnetic susceptibility measurements—Yerington mine

The Yerington Mine is an open pit mine of “porphyry‐copper” type. Primary mineralization (quartz veins, Cu‐Fe sulfides, magnetite, and silicate alteration) is closely associated with a complex sequence of quartz monzonite porphyry intrusives. This primary mineralization is disrupted by subsequent alteration and faulting. The fault block containing the deposit has been rotated almost 90 degrees to the west; plan maps represent pretilt vertical sections. Almost one mile of pretilt vertical extent is exposed in the pit. Geologic observations may be taken only upon mining advances at discrete intervals. Detailed in‐situ induced‐polarization response and magnetic susceptibility surveys, both taken upon the pit floor, have been used to supplement geologic mapping. These in‐situ measurements reveal the distribution patterns of sulfides and magnetite and are useful in interpolation or correlation of contacts, faults, and mineralization patterns between mapped advances. In‐situ induced‐polarization (IP) response was measured using a Scintrex IPR-7 receiver. Observations were made on a 10 × 10-ft grid using a Wenner electrode array with 3 1/3-ft a‐spacing. Susceptibility measurements were taken with a Bison model 3101-A bridge and an in‐situ coil arrangement 5 ft in diameter. A composite area approximately 3000 by 500 ft, representing 15,000 data points, has been surveyed. Contoured maps of in‐situ IP response and magnetic susceptibility reveal the mineralization pattern in detail. These maps correlate well with the geologically mapped distribution of porphyry intrusives and also indicate zones of sulfide remobilization and/or magnetite destruction, including fault zones. IP response and magnetic susceptibility correlate well with elemental assays, mineral abundances, ratios, and textures determined from bench mapping and pit floor samples. The spatial distribution of physical properties is extremely complex, which demonstrates the need for caution in the use of simple interpretative models. The abundance of magnetite locally present in this particular porphyry‐copper environment is noteworthy.

Analytical solutions to the semi‐discrete form of the conduction equation for non‐homogeneous media

AbstractThe partial differential equation describing transient conduction (or diffusion) in non‐homogeneous media may be approximated by a set of first order linear ordinary differential equations if the derivatives involving the space variables are replaced by finite difference expressions. A general method of obtaining a closed form solution of these equations is presented, using some operational methods of linear algebra. The solution is given in terms of a matrix, which describes the spatial distribution of physical properties in the media, and vectors describing the initial and boundary conditions.