Distribution Of Physical Properties Research Articles

Spatial Distribution of Physical and Chemical Properties of Deep Sea Water in Xisha, South China Sea

Deep sea water (DSW) is a globally utilized source of renewable energy and other resources. To understand the characteristics of DSW resources in the South China Sea, in July 2022, the Guangzhou Marine Geological Survey (GMGS) investigated temperature, salinity, pH, dissolved oxygen (DO), inorganic salts (DIN, PO43−-P, and SiO3-Si), heavy metals (Hg, Pb, As, and Cd), trace elements (Cu, Zn, Fe, Mn, Ni, Se, and Mo), and other related indicators. The results of this investigation elucidate the horizontal and vertical changes in the physical and chemical properties of deep sea water in the Xisha Sea. The surface seawater quality in Xisha was found to be excellent and to meet first-class seawater survey standards. However, the concentrations of various nutrient salts in the surface layer were relatively low. As the seawater depth increased, different trace elements and heavy metals exhibited variations, and the concentrations of various nutrients also gradually increased.

Spaceborne lidar measurement of global cloud properties through machine learning

With a large footprint size, multiple scattering measurements of clouds from spaceborne lidar provide useful information about cloud physical properties, such as cloud optical depths and cloud droplet size, both during daytime and nighttime. A neural network algorithm, with a subset of cloud backscatter profiles of dual-polarization and dual-wavelength Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements during daytime as input variables and cloud physical properties derived from collocated Moderate Resolution Imaging Spectroradiometer (MODIS) multi-spectral measurements as output, is developed and evaluated with an independent subset of the collocated CALIPSO and MODIS measurements. The study suggests that with a receiver footprint size of 110 m, CALIPSO lidar measurements are sensitive to liquid-phase cloud optical depth variations from 0 to 25. A larger footprint size, thus more multiple scattering, is required for lidar to have sensitivities to all liquid-phase clouds. The technique can be applied to all 17 years of CALIPSO daytime and nighttime measurements and, thus, provides useful information about global distributions of cloud physical properties both during day and night.

Coupled Hydrogeophysical Modeling to Constrain Unsaturated Soil Parameters for a Slow‐Moving Landslide

AbstractGeophysical methods have proven to be useful for investigating unstable slopes as they are both non‐invasive and sensitive to the spatial distribution of physical properties in the subsurface. Of particular interest are the links between electrical resistivity and near‐surface moisture content; recent work has demonstrated that it is possible to calibrate hydrological models using geophysical measurements. In this study we explore the use of in‐field electrical resistivity data for calibrating unsaturated soil retention parameters and saturated hydraulic conductivity used for modeling unsaturated fluid flow. We study a synthetic case study, and a well‐characterized site in the northeast of England and develop an approach to calibrate retention parameters for a mudstone and a sandstone formation, the former being an actively failing unit. Petrophysical relationships between electrical resistivity and moisture content (or saturation) are established for both formations. 2D hydrological models are driven by effective rainfall estimations; subsequently these models are coupled with a geophysical forward model via a Markov chain Monte Carlo approach. For the synthetic case, we show that our modeling approach is sensitive to the moisture retention parameters, while less so to saturated hydraulic conductivity. We observe the same characteristics and sensitivities for the field case, albeit with a greater data misfit. Further hydrological simulations suggest that the slope retained high moisture contents in the months preceding a rotational failure. Therefore, we propose that coupled hydrological and geophysical modeling approaches could aid in enhancing landslide monitoring, modeling, and early warning efforts.

Analysis of classification results of rock cores with different physical properties based on clustering algorithm

Abstract In response to the problem of high difficulty in development caused by different physical properties differences during water flooding in high water bearing oil fields, effective flow unit division and analysis were carried out in Zone 1 of Gangxi through flow unit analysis. The physical property classification of each rock core in the flow unit was determined using the GMM cluster algorithm. The results show that Class I flow units have high permeability and porosity, and good pore permeability performance; The porosity and permeability distribution range of Class II flow units is the widest, with some pore permeability performance comparable to or even higher than Class I, and overall pore permeability performance is good; The porosity and permeability of Class III flow units are lower than the first two types, and their pore permeability performance is relatively poor. The types of core porosity and permeability in the study area can be divided into four categories, with the majority being high permeability, ultra-high permeability, and high permeability. The new research results provide a reference basis for the study of physical property distribution and later well network deployment in the first block of Gangxi District.

Modeling the spatial distribution of soil physical properties in a semiarid tropical region

In semiarid regions, sustainably managing the limited available water resources is critical for food, water, and economic security. An important aspect of water management is monitoring, analyzing, and predicting soil moisture and hydrologic fluxes, especially under the threats of climate change. Unfortunately, since monitoring of soil moisture and water fluxes is often sparse in these regions, one needs to rely on hydrological modeling. The latter requires accurate knowledge of soil properties (e.g., texture, porosity, hydraulic conductivity), which in semiarid regions is also complicated by high level of spatial heterogeneity that is not captured by the low density of soil sampling efforts as well as by globally gridded soil databases. Using 300 monitoring sites across the Semiarid region of NE Brazil and a soil moisture model, this study aims to estimate soil properties at the sites through inverse-modeling and then spatially interpolation these properties via geostatistics. Inverse modeling with the Levenberg–Marquardt algorithm accurately captured soil properties across the sites, while clear spatial patterns in these properties allowed us to confidently interpolation them across the region. Comparing our results with a global soil dataset shows that the latter does not capture spatial variability in the region, underlining the need to leverage small scale information. The derived soil property datasets may then particularly be valuable for regional water and ecosystem management applications.

Bio-Optical Properties near a Coastal Convergence Zone Derived from Aircraft Remote Sensing Imagery and Modeling

Bio-optical and physical measurements were collected in the Mississippi Sound (Northern Gulf of Mexico) during the spring of 2018 as part of the Integrated Coastal Bio-Optical Dynamics project. The goal was to examine the impact of atmospheric and tidal fronts on fine-scale physical and bio-optical property distributions in a shallow, dynamic, coastal environment. During a 25-day experiment, eight moorings were deployed in the vicinity of a frontal zone. For a one-week period in the middle of the mooring deployment, focused ship sampling was conducted with aircraft and unmanned aerial vehicle overflights, acquiring hyperspectral optical and thermal data. The personnel in the aircraft located visible color fronts indicating the convergence of two water masses and directed the ship to the front. Dye releases were performed on opposite sides of a front, and coincident aircraft and unmanned aerial vehicle overflights were collected to facilitate visualization of advection/mixing/dispersion processes. Radiometric calibration of the optical hyperspectral sensor was performed. Empirical Line Calibration was also performed to atmospherically correct the aircraft imagery using in situ remote sensing reflectance measurements as calibration sources. Bio-optical properties were subsequently derived from the atmospherically corrected aircraft and unmanned aerial vehicle imagery using the Naval Research Laboratory Automated Processing System.

Looking for Optimal Maps of Soil Properties at the Regional Scale

Around 70% of surface in Extremadura, Spain, faces a critical risk of degradation processes, highlighting the necessity for regional-scale soil property mapping to monitor degradation trends. This study aimed to generate the most reliable soil property maps, employing the most accurate methods for each case. To achieve this, six different machine learning (ML) techniques were tested to map nine soil properties across three depth intervals (0–5, 5–10 and > 10 cm). Additionally, 22 environmental covariates were utilized as inputs for model performance. Results revealed that the Random Forest (RF) model exhibited the highest precision, followed by Cubist, while Support Vector Machine showed effectiveness with limited data availability. Moreover, the study highlighted the influence of sample size on model performance. Concerning environmental covariates, vegetation indices along with selected topographic indices proved optimal for explaining the spatial distribution of soil physical properties, whereas climatic variables emerged as crucial for mapping the spatial distribution of chemical properties and key nutrients at a regional scale. Despite providing an initial insight into the regional soil property distribution using ML, future work is warranted to ensure a robust, up-to-date, and equitable database for accurate monitoring of soil degradation processes arising from various land uses.

“Core–core” petrophysical relationships generation for reservoir modeling

Relevance. The need in a detailed analysis of distribution of physical properties of the formation in space. Currently, the parameters connecting the results of responses of geophysical fields and petrophysical studies of core are averaged. On the one hand, this is due to the small number of wells with cores in the fields, and on the other hand, to simplify and speed up calculations in the presence of a large number of wells with geophysical surveys of wells. However, this approach does not allow us to identify the largest number of a particular layer or section characteristics. This, in its turn, may lead to inaccuracies in calculating filtration and capacitance properties. When averaging parameters, the features of formation of the deposit in parts of the field with core sampling are lost. And this is a very big opportunity to more accurately form facies models of deposits. Aims. To generate a map of skeletal density distribution based on core data for the supra-coal strata of a terrigenous oil reservoir; analyze the resulting distribution map, identify areas with increased and decreased density values; assess the degree of change in the porosity coefficient when compared with density values; identify areas of high and low density and trends. Object. Supra-coal strata of terrigenous sediments of one of the layers of an oil field in the Tomsk region. Methods. Analysis of the petrophysical database leads to formation of an idea of the reservoir. Laboratory core studies are the source of the most reliable information about the filtration and reservoir properties of the formation. The analysis technique involves the well-by-well construction of dependencies of petrophysical parameters and determination of the value of the constant density of the skeleton. Additionally, a general relationship is built for all wells to compare values and identify maximum and minimum parameters boundaries, skeletal density distribution map and resulting zones with low- and high-density values analysis. Borehole differentiation of values leads to increased detail of the distribution of the studied parameter and identification of zones with abnormally high and low values for more detailed study and the formation of a conceptual geological model.

SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN SOUTHERN MANKAYAN, BENGUET, PHILIPPINES

Abstract. Hydrothermal alteration in the Mankayan Mineral District in Benguet, Philippines, has had a significant impact on the soil characteristics. Thus, soil characterisation in landslide zones offer useful insights on the nature of slope failure and provide baseline data that may be used with susceptibility mapping and hazard zonations. The study elucidated the physical characteristics of the soils in the southern portion of Mankayan and mapped out the spatial distribution in the area. High sand and low clay content cause low slope stability due to the low water retention in soil, low plasticity, and low shear strength of materials while the resulting porosity led to poor drainage. Results show that the soil's physical properties, whereas most rock units have been affected by alteration, have caused rock deterioration that eventually led to slope failures. The presence of various parent material in the study site influenced the distribution of soil physical properties, specifically the influence of dacite on the Atterberg limits in the central area of southern Mankayan.

Red Clay Soil Physical and Chemical Properties Distribution Using Remote Sensing and GIS Techniques in Kirkuk City, Iraq

This research focuses on the study of the physical and chemical properties of red clay found in the Injana and Fatha Formations. The aim is to establish correlations among various physical and chemical elements using geographic information system (GIS), remote sensing, and a regression analysis model. Laboratory analysis, including X-ray diffraction, was conducted to determine the properties of the clay, as well as nonclay minerals. Statistical Package for the Social Sciences software was utilized for regression analysis to determine property correlations. Landsat 7 and Landsat 8 images were employed to establish relationships between digital numbers and soil properties. The study revealed that the dry density of the Fatha Formation was lower than that of the Injana Formation. Silt content was highest among all samples, ranging from 28% to 93%. The Fatha Formation exhibited a high gypsum rate due to the presence of gypsum layers. Strong positive correlations were observed between gypsum and sulfate, as well as between electrical conductivity and total soluble salt. Multiple linear regression analysis was appropriate for clay properties, with regression coefficients ranging from 0.6 to 0.72. Nonlinear regression yielded better results than linear regression, with high regression coefficients. Landsat images proved valuable for obtaining data in remote or expansive areas. The association between clay characteristics and Landsat 8 provided superior results compared to Landsat 7.

Petrological Evolution and Mass Redistribution in Basaltic Fault Zones: An Example From the Faroe Islands, North Atlantic Igneous Province

AbstractFault rock petrology exerts an important influence on the permeability structure and mechanical properties of fault zones. Slip‐related deformation on upper‐crustal faults in basaltic rocks is closely associated with fluid‐rock interaction, altering the distribution of physical properties within the fault. Here, we present quantitative descriptions of the geochemical and petrological evolution of basalt‐derived fault rocks from three passively exhumed fault zones in the Faroe Islands. Fault‐rock petrology is determined by optical petrography and automated phase identification based on micrometer‐scale chemical maps from scanning electron microscope X‐ray spectroscopy. Geochemical evolution is assessed from major and trace element composition measured by X‐ray fluorescence. The fault rocks show intense fluid‐mediated alteration from a tholeiitic basalt protolith in the damage zones, and mechanical mixing in the fault cores. Pervasive alteration occurs early during fault zone evolution, with incipient fault damage increasing permeability and allowing along‐fault percolation of carbonated meteoric water, increasing fluid‐rock ratios. Our results suggest that the only mobile species within the fault zones are Ca, Si, and Al, which are leached during the hydrolysis of volcanic glass and plagioclase, and CO2, which is added by percolating waters. These species are transported from the damage zones into the fault cores, where they precipitate as zeolite and calcite cement in veins and hydrothermal breccias. We propose that solutes are replenished by cement dissolution through pressure‐solution during cataclastic creep, during repeated cycles of hydrofracture and cementation. The fault zones are natural reactors for fluid‐mediated alteration by CO2 and water, while other species are redistributed within the fault zones.

Weighing Geophysical Data With Trans‐Dimensional Algorithms: An Earthquake Location Case Study

AbstractIn geophysical inverse problems, the distribution of physical properties in an Earth model is inferred from a set of measured data. A necessary step is to select data that are best suited to the problem at hand. This step is performed ahead of solving the inverse problem, generally on the basis of expert knowledge. However, expert‐opinion can introduce bias based on pre‐conceptions. Here we apply a trans‐dimensional algorithm to automatically weigh data on the basis of how consistent they are with the fundamental hypotheses made to solve the inverse problem. We demonstrate this approach by inverting arrival times for the location of a seismic source in an elastic half‐space, assuming a point‐source and uniform weights in concentric shells. The key advantage is that the data do no longer need to be selected by an expert, but they are assigned varying weights during the inversion procedure.

Effect of spherical alumina crystalline phase content and particle size distribution polydispersity on the properties of silicone rubber composites

High loading of thermally conductive fillers for enhancing thermal conductivity (TC) conflicts with proper rheological viscosity in excellent thermal interface materials (TIMs), which remains a significant challenge. The physical properties (crystalline phase, particle size and distribution, etc.) of thermally conductive filler are the base of the high load in the polymer. In this paper, the α-phase content of spherical aluminum (S–Al2O3) increases after calcination, leading to the viscosity of composites increasing sharply but was only slightly improved for the TC. The polydispersity of the S–Al2O3 particle size distribution was regulated to fill the silicone rubber under the premise of controlling the same average particle size, crystalline phase content and filling amount. Results indicated the viscosity of the sample with a polydispersity value of 0.74 was 41.21 Pa s at a shear rate of 10 s−1 at 66 vol%, which was 87.7% lower than that of the sample with a polydispersity value of 0.48. And the viscosity difference became more prominent with the increasing filling amount. However, the difference in TC between several groups of samples with different polydispersity is insignificant at 60–67 vol%, which provides practical, theoretical guidance for achieving controllable viscosity and developing low-viscosity TIMs in the processing process.

Comparative molecular dynamics study of liquid hydrogen annular jets in subcritical and supercritical environments

In this paper, the injection characteristics of a liquid hydrogen propellant jet under subcritical and supercritical operating conditions are comparatively studied at the molecular scale using molecular dynamics methods in the context of spacecraft propulsion systems. To control the temperature and pressure within the environment and nozzle respectively, two sub-computational domains are set up for separate modeling. The sub-computational domain merging process eliminates the broken molecular bonds by using the computational domain reduction in the x-direction. The jet velocity, density and other physical property distributions at different temperatures and pressures were comparatively studied. It is found that the rate of change of the radial density of the jet under supercritical conditions is small. Based on this, the surface area and volume of the liquid phase region of the jet were extracted and calculated. Compared to result of subcritical case, the volume of the liquid hydrogen jet in the supercritical environment is reduced by 1.9%, while the surface area is increase by 6.7%. To explain the variation in the surface area due to molecular diffusion, the molecular stress results revealed that the stress in the hydrogen jet in supercritical environment is only 88.9% of that in subcritical environment.

Geochemical characteristics of the braided river reservoir in block 19 of the sulige gas field

The sand body structure and geochemical characteristics of braided river reservoirs are the key geological factors affecting gas production and development effects. The Sulige gas field in the Ordos Basin is an important large-scale gas-producing layer. Owing to the control of sedimentary facies, the geological structure of the sand body changes greatly and its connectivity is poor. The geological characteristics have not yet been elucidated, and this is an important problem restricting the development of the Sulige Gas Field. To solve this problem, this study focuses on the braided river reservoir of the Shihezi Formation in Block 19 of the Sulige Gas Field, conducts geological surveys in the study area, analyzes the geological and geochemical characteristics of the reservoir, and obtains samples through drilling. Through a thin-section test, gas-water two-phase experiment, and simulation test, the braided river reservoir configuration and pore and gas-water characteristics are obtained. The results show that the reservoir lithology in the study area is mainly composed of quartz sandstone, lithic sandstone, and quartzy lithic sandstone, with a porosity of 3%–13% and a permeability of (0.05–0.7) × 10−3 m2. The reservoir has low porosity and low permeability. After drilling samples were obtained, 32 thin-section rock samples were selected. The pore types of the block reservoir mainly (82.9%) consisted of intragranular and intergranular dissolved pores. The difference in pore structure was mainly reflected by the size and distribution of the throat. The distribution of physical properties was 6%–10%, the gas saturation was 61%, the NMR effective porosity was 7.49%, the permeability was 4.08 × 102 μm2, and the physical properties were relatively good. In terms of the study area, the average thickness of the single braided channel in the lower section of He 8 was 4.7 m, the average width of the channel was 963 m, and the composite channel was distributed in a potato shape, parallel to the direction of the main flow. The average length of the channel was 2,147 m and the average width was 844 m. As the porosity increased, the efficiency of gas-driven water also increased, and there was a linear positive correlation between porosity and gas-driven water efficiency. With the increase in movable water saturation, the water-air ratio became larger and water production was greater. In low-amplitude structures and under low-permeability background conditions, for reservoirs with good local pore structure and physical properties, the water remaining at the bottom of the reservoir or sand body was controlled by the accumulation conditions or the weak structural differentiation after accumulation. In terms of the gas and water produced simultaneously in the study area, gas production was less than 2 × 104 m3/d and water production was relatively large at more than 10 m3/d; gas and water were mainly distributed in the downdip part of the main channel structure or in the island lens-shaped permeable sand bodies trapped by the surrounding tight layers. The study results provide theoretical data support for the exploration and production of the Sulige Gas Field.

Quantitative Low-Field 19 F Nuclear Magnetic Resonance Analysis of Carbonyl Groups in Pyrolysis Oils.

Pyrolysis bio-oils, one of the products of lignocellulosic biomass pyrolysis, have the potential to be widely used as fuels. The chemical composition of bio-oils is very complicated as they contain hundreds, if not thousands, of different, mostly oxygen-containing, compounds with a wide distribution of physical properties, chemical structures, and concentrations. Detailed knowledge of bio-oil composition is crucial for optimizing both the pyrolysis processes and for any subsequent upgrading into a more viable fuel resource. Here we report the successful use of low-field, or benchtop, nuclear magnetic resonance (NMR) spectrometers in the analysis of pyrolysis oils. Pyrolysis oils from four different feedstocks were derivatized and analyzed using 19 F NMR techniques. The NMR results compare favorably with titrations for total carbonyl content. In addition, the benchtop NMR spectrometer proves able to reveal key spectral features, thus allowing the quantification of different carbonyl groups, such as aldehydes, ketones and quinones. Benchtop NMR spectrometers are typically compact, cheaper than their superconducting counterparts and do not require cryogens. Their use will make NMR analysis of pyrolysis oils easier and more accessible to a wide range of different potential users.

Impedance Response Influenced by Variability in the Random Distribution of Physical Properties of Coated Materials in Two-Dimensional Space

Heterogeneous physical characteristics of a system featuring a single-layer film on a metallic surface have been explored via its impedance response. The Nyquist plot showed a distorted semicircle, indicative of the system’s unique distribution characteristics. Utilizing a copula-based probability method, a two-dimensional deterministic impedance model was successfully integrated, accounting for spatial physical properties such as permittivity and electrical conductivity. This strategy enabled in-depth exploration and mechanistic quantification of a broad spectrum of properties. A quantitative understanding of impedance signal alterations, characterized by normally or log-normally correlated variables, was achieved through the variation in aspect ratio and characteristic frequency of the impedance spectra. Log-normally distributed electrical properties provided a superior representation of the distorted impedance spectra. As coefficient of variation (CV) values fluctuated, the aspect ratio and characteristic frequency showed heightened sensitivity to log-normal permittivity compared to log-normal electrical conductivity. Notably, a marked positive linear correlation between electrical properties resulted in an impedance response that approximated perfect semicircular spectra. The variability in the electrical properties’ distribution was demonstrated by considering the correlation coefficient between electrical conductivity and the z-direction position. The highest aspect ratio of the impedance spectra was observed when the electrical conductivity was randomly distributed across the z-direction space.

Event Rate of Strongly Lensed Gravitational Waves of Stellar Binary Black Hole Mergers Produced by Dynamical Interactions

Gravitational waves emitted from stellar binary black hole (sBBH) mergers can be gravitationally lensed by intervening galaxies and detected by future ground-based detectors. A great amount of effort has been put into the estimation of the detection rate of lensed sBBH originating from the evolution of massive binary stars (EMBS channel). However, sBBHs produced by the dynamical interaction in dense clusters (dynamical channel) may also be dominant in our universe and their intrinsic distribution of physical properties can be significantly different from those produced by massive stars, especially mass and redshift distribution. In this paper, we investigate the event rate of lensed sBBHs produced via the dynamical channel by Monte Carlo simulations and the number is yr−1 for the Einstein telescope and yr−1 for Cosmic Explorer, of which the median is about ∼2 times the rate of sBBHs originating from the EMBS channel (calibrated by the local merger rate density estimated for the dynamical and the EMBS channel, i.e., and , respectively). Therefore, one may constrain the fraction of both the EMBS and dynamical channels through the comparison of the predicted and observed number of lensed sBBH events statistically.

Relevance of charge interactions for contaminant transport in heterogeneous formations: a stochastic analysis

The electrostatic properties of clay (or other charged) mineral surfaces play a significant role in the fate, transport, persistence, and remediation of subsurface contaminant plumes. This study presents a stochastic assessment of the impact and relevance of microscale electrostatic effects on macroscopic, field-scale contaminant transport in heterogeneous groundwater systems involving spatially distributed clay zones. We present Monte Carlo simulations in two-dimensional heterogeneous fields, comprising heterogeneous distributions of physical (i.e., hydraulic conductivity, porosity, tortuosity) and electrostatic (i.e., surface charge) properties, and compare scenarios with different combination and extent of physical and electrostatic processes. The simulations were performed with the multi-continua based reactive transport code, MMIT-Clay, and considering an explicit treatment of the diffuse layer processes. The results reveal that the microscopic electrostatic mechanisms within clay’s diffuse layer can significantly accelerate or retard a particular contaminant depending on its charge, leading to considerably different solute breakthroughs and mass loading/release behaviors in low permeability inclusions. Furthermore, we show that such variations in the macroscale transport behavior, solely driven by charge interactions, are statistically significant over the ensembles of Monte Carlo realizations. The simulations also demonstrate that the omission of electrostatic processes, which is still a common practice in subsurface hydrology, can lead to substantial over- or underestimation of contaminant migration.

A stable downward continuation method for processing gravity data using the equivalent sources with compactness and smoothing constraints

The downward continuation of the potential field is often a necessary step in data processing and interpretation, in which equivalent source is an available method. Unfortunately, due to the physical property distribution of the equivalent source obtained from the observed data inversion, this is an unstable operation. Particularly in the case of noisy data, the generation of false signals can severely obscure the useful information in the original data. To deal with the instability fundamentally, we have developed a constrained equivalent-source method to improve the physical property distribution in the equivalent layer for stable downward continuation of the gravity anomaly. In this method, the compactness constraint is applied to reduce divergent signals, and multiple smoothing is used to further eliminate the signals causing instability. Experiments on synthetic gravity anomalies show that the proposed method yields cleaner images of the physical properties and more accurate amplitudes of the downward-continuing gravity field. Application to measured data also shows that the proposed method can significantly attenuate the divergent signals and enhance the amplitude of the effective signals.