Distribution Of Physical Properties Research Articles

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.

Quantitative analysis of TCE biodegradation pathway in landfill cover utilizing continuous monitoring, droplet digital PCR and multi-omics sequencing technology

The remediation of volatile chlorinated hydrocarbons in the quasi-vadose zone has become a significant challenge. We applied an integrated approach to assess the biodegradability of trichloroethylene to identify the biotransformation mechanism. The formation of the functional zone biochemical layer was assessed by analyzing the distribution of landfill gas, physical and chemical properties of cover soil, spatial-temporal variations of micro-ecology, biodegradability of landfill cover soil and distributional difference metabolic pathway. Real-time online monitoring showed that trichloroethylene continuously undergoes anaerobic dichlorination and simultaneous aerobic/anaerobic conversion-aerobic co-metabolic degradation on the vertical gradient of the landfill cover system and reduction in trans-1,2-dichloroethylene in the anoxic zone but not 1,1-dichloroethylene. PCR and diversity sequencing revealed the abundance and spatial distribution of known dichlorination-related genes within the landfill cover, with 6.61 ± 0.25 × 104–6.78 ± 0.09 × 106 and 1.17 ± 0.78 × 103–7.82 ± 0.07 × 105 copies per g/soil of pmoA and tceA, respectively. In addition, dominant bacteria and diversity were significantly linked with physicochemical factors, and Mesorhizobium, Pseudoxanthomonas and Gemmatimonas were responsible for biodegradation in the aerobic, anoxic and anaerobic zones. Metagenome sequencing identified 6 degradation pathways of trichloroethylene that may occur in the landfill cover; the main pathway was incomplete dechlorination accompanied by cometabolic degradation. These results indicate that the anoxic zone is important for trichloroethylene degradation.

A novel high-dimensional and multi-physics modeling approach of proton exchange membrane fuel cell for real-time simulation

Fuel cell model provides state observation and quantitative analysis for Hardware-In-the-Loop (HIL) test platform. For a high-dimensional multi-physics model, the observed distribution of physical properties is meaningful for fuel cell stack optimization, manufacturing process and model-based control development. However, traditional modeling approach is difficult to consider both the calculation accuracy and efficiency. To solve this problem, this paper proposes a high-dimensional multi-physics real-time modeling approach for fuel cells based on partial differential equations (PDEs)-tridiagonal matrix equation transformation (TMET) and symmetric successive overrelaxation (SSOR) algorithm. In the proposed method, a generalized framework of TMET and a novel staggered grid technique is developed. In this case, both the convection and diffusion phenomena can be accurately described. For different fuel cells or parameters change, supplementary model modification or development is not required, only the global variables need to be re-assigned. Moreover, SSOR with bi-directional iteration mechanism is used to increase the probability of computational convergence and thus improve the calculation efficiency. Compared with commercial COMSOL model, by using the proposed modeling approach, the mean absolute percentage error (MAPE) of the simulated polarization output characteristics is 1.77%, the MAPE of different distribution characteristics can remain within 10%, and the calculation time can be shortened from hours even days to seconds.

Behavioral simulations and experimental evaluations of stress induced spatial nonuniformity of dynamic bulk modulus in additive friction stir deposited AA 6061

Additive friction stir deposition (AFSD) is a rapidly developing solid-state additive manufacturing (AM) technology that enables the fabrication of customized products on a relatively large scale. The unique forge-liked process offers high quality products with refined equiaxed microstructure and exceptional mechanical performance. However, in AFSD, the spatially distributed mechanical properties within a deposited layer have not been established so far, due to the lack of a suitable large-scale mapping method. In the present work, an ultrasonic dynamic-elasticity mapping method was employed to map the distribution of physical properties in a AFSD 6061 Al. Strong spatial asymmetries in elastographies were mainly due to the residual stresses. The origin of the asymmetries was investigated through thermo-mechanical simulations of the AFSD process. It was observed that majority of the asymmetries were associated with the mechanical residual stresses instead of the symmetric thermal residual stresses during linear deposition of the AFSD process. However, the thermal residual stresses can be manipulated to become asymmetric with a 90° turn in the linear deposition path, due to the difference between the levels of cooling along the edges of the inner and outer corners. Hence, the mechanical and thermo-mechanical residual stresses can be additive or subtractive depending on the direction of the turns. Such numerically predicted behaviors were also experimentally observed on the AFSD fabricated samples by ultrasonic elastography. Furthermore, additional preliminary studies on multi-layer AFSD fabrications show the asymmetric mechanical stresses generated during the deposition process on different layers generate constructive or destructive interference which results to spatially variable dynamic bulk modulus depending on the deposition orientations of layers.

Southern coastal system of the San Jorge Gulf during spring

The San Jorge Gulf was declared an area of national economic, commercial, conservation and diversity interest. To contribute to its study, the southern coastal sector of the gulf was characterised in physical and chemical parameters in spring campaigns (November 2016 and 2017). Samples were taken on board the oceanographic vessel Puerto Deseado in three perpendicular to the coast transects and another one to the southeast of the gulf, which crosses a thermohaline front. The perpendicular to the coast transects showed a similar pattern of distribution of physical and chemical properties in the water column. At nearshore stations, the water column was homogeneous and the nutrient concentrations between the surface and bottom layers were similar. At offshore stations, the water column was stratified and the nutrient concentrations were higher near the bottom than at surface. In 2016, a wind induced upwelling front was observed in the southwest of the gulf. Both sides of the thermohaline front did not show significant chemical differences. Throughout the study area, silicic acid and nitrate limited primary production. Satellite chlorophyll-a data and fluorescence profiles showed that the southern sector of the gulf has a high biomass of phytoplankton during November. We conclude that the southern sector of the SJG has different features depending on the external forcing caused by the front. The presence of fronts stimulates the growth of phytoplankton biomass through the injection of nutrients from the homogeneous part to the stratified sector. This would affect phytoplankton community and, thus, the productivity of the system.

Neural Stellar Population Synthesis Emulator for the DESI PROVABGS

The Probabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide the posterior distributions of physical properties of >10 million DESI Bright Galaxy Survey galaxies. Each posterior distribution will be inferred from joint Bayesian modeling of observed photometry and spectroscopy using Markov Chain Monte Carlo sampling and the Hahn et al. stellar population synthesis (SPS) model. To make this computationally feasible, PROVABGS will use a neural emulator for the SPS model to accelerate the posterior inference. In this work, we present how we construct the emulator using the Alsing et al. approach and verify that it can be used to accurately infer galaxy properties. We confirm that the emulator is in excellent agreement with the original SPS model with ≪1% error and is 100× faster. In addition, we demonstrate that the posteriors of galaxy properties derived using the emulator are also in excellent agreement with those inferred using the original model. The neural emulator presented in this work is essential in bypassing the computational challenge posed in constructing the PROVABGS catalog. Furthermore, it demonstrates the advantages of emulation for scaling sophisticated analyses to millions of galaxies.

Probabilistic approach to Gramian inversion of multiphysics data

We consider a probabilistic approach to the joint inversion of multiphysics data based on Gramian constraints. The multiphysics geophysical survey represents the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the various components of the geological system. By joint inversion of the multiphysics data, one can produce enhanced subsurface images of the physical properties distribution, which improves our ability to explore natural resources. One powerful method of joint inversion is based on Gramian constraints. This technique enforces the relationships between different model parameters during the inversion process. We demonstrate that the Gramian can be interpreted as a determinant of the covariance matrix between different physical models representing the subsurface geology in the framework of the probabilistic approach to inversion theory. This interpretation opens the way to use all the power of the modern probability theory and statistics in developing novel methods for joint inversion of the multiphysics data. We apply the developed joint inversion methodology to inversion of gravity gradiometry and magnetic data in the Nordkapp Basin, Barents Sea to image salt diapirs.