Variogram analysis of magnetic and gravity data

Geophysics ◽  
1999 ◽  
Vol 64 (3) ◽  
pp. 776-784 ◽  
Author(s):  
Stefan Maus
Keyword(s):  
Gravity Data ◽  
Source Parameters ◽  
Power Spectra ◽  
Spectral Model ◽  
Scaling Exponent ◽  
Space Domain ◽  
Variogram Analysis ◽  
Wavenumber Domain ◽  
Gravity Line ◽  
Self Similar

Model variograms describe the space domain statistics of magnetic and gravity data. Variogram analysis can be used to map intensity, depth, and scaling exponent (self‐correlation) of source. In previous statistical methods the measured data were gridded and transformed to the wavenumber domain; then their power spectrum was analyzed using a spectral model. To avoid the loss and distortion of information during gridding and wavenumber domain transform, I transform the spectral model to the space domain instead. Variograms are the appropriate space domain counterparts of magnetic and gravity power spectra. The variogram of the field above a self‐similar half‐space model is governed by three parameters: intensity, depth, and scaling exponent. These source parameters can be mapped with high resolution and accuracy by fitting model variograms directly to magnetic and gravity line data variograms.

THE FEASIBILITIES OF USING THE STATISTICAL, FRACTAL AND SINGULAR PROCESSING OF HOMINAL BLOOD PLASMA PHASE IMAGES DURING THE DIAGNOSTICS AND DIFFERENTIATION OF MAMMARY GLAND PATHOLOGICAL STATES

2012 ◽  
Vol 05 (01) ◽  
pp. 1150001 ◽  
Author(s):  
YU. A. USHENKO
Keyword(s):  
Mammary Gland ◽  
Blood Plasma ◽  
Statistical Approach ◽  
Power Spectra ◽  
Thin Layers ◽  
Fractal Approach ◽  
Phase Images ◽  
Orthogonal Components ◽  
Self Similar ◽  
Plasma Phase

Performed in this work are complex statistical, fractal and singular analyses of phase properties inherent to birefringence networks of protein crystals consisting of optically-thin layers prepared from blood plasma. Within the framework of a statistical approach, the authors have investigated values and ranges for changes of statistical moments of the first to the fourth orders that characterize coordinate distributions for phase shifts between orthogonal components of amplitudes inherent to laser radiation transformed by blood plasma with various pathologies. In the framework of the fractal approach, determined are the dimensions of self-similar coordinate phase distributions as well as features of transformation of logarithmic dependences for power spectra of these distributions for various types of hominal mammary gland pathologies.

scholarly journals 3D Gravity Inversion with Correlation Image in Space Domain and Application to the Northern Sinai Peninsula

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Xu Zhang ◽  
Peng Yu ◽  
Jian Wang
Keyword(s):  
Density Distribution ◽  
Gravity Data ◽  
Descent Method ◽  
Steepest Descent Method ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Sinai Peninsula ◽  
Space Domain ◽  
Correlation Image ◽  
Starting Model

We present a 3D inversion method to recover density distribution from gravity data in space domain. Our method firstly employs 3D correlation image of the vertical gradient of gravity data as a starting model to generate a higher resolution image for inversion. The 3D density distribution is then obtained by inverting the correlation image of gravity data to fit the observed data based on classical inversion method of the steepest descent method. We also perform the effective equivalent storage and subdomain techniques in the starting model calculation, the forward modeling and the inversion procedures, which allow fast computation in space domain with reducing memory consumption but maintaining accuracy. The efficiency and stability of our method is demonstrated on two sets of synthetic data and one set of the Northern Sinai Peninsula gravity data. The inverted 3D density distributions show that high density bodies beneath Risan Aniza and low density bodies exist to the southeast of Risan Aniza at depths between 1~10 and 20 km, which may be originated from hot anomalies in the lower crust. The results show that our inversion method is useful for 3D quantitative interpretation.

A continuum of non-Gaussian self-similar image ensembles with white power spectra

1994 ◽  
Vol 8 (4) ◽  
pp. 503-513
Author(s):  
Jonathan D. Victor ◽  
Julian S. Joseph
Keyword(s):  
Power Spectra ◽  
Similar Image ◽  
Self Similar ◽  
Non Gaussian

Intermittency caused by compressibility: a Lagrangian study

2015 ◽  
Vol 786 ◽  
Author(s):  
Yantao Yang ◽  
Jianchun Wang ◽  
Yipeng Shi ◽  
Zuoli Xiao ◽  
X. T. He ◽  
...  
Keyword(s):  
Mach Number ◽  
Time Scales ◽  
Time Scale ◽  
Driving Force ◽  
Three Dimensional ◽  
Point Of View ◽  
Scaling Exponent ◽  
Similar Region ◽  
Turbulent Statistics ◽  
Self Similar

We investigate how compressibility affects the turbulent statistics from a Lagrangian point of view, particularly in the parameter range where the flow transits from the incompressible type to a state dominated by shocklets. A series of three-dimensional simulations were conducted for different types of driving and several Mach numbers. For purely solenoidal driving, as the Mach number increases a new self-similar region first emerges in the Lagrangian structure functions at sub-Kolmogorov time scale and gradually extends to larger time scale. In this region the relative scaling exponent saturates and the saturated value decreases as the compressibility becomes stronger, which can be attributed to the shocklets. The scaling exponent for the inertial range is still very close to that of incompressible turbulence for small Mach number, and discrepancy becomes visible when the Mach number is high enough. When the driving force is dominated by the compressive component the shocklet-induced self-similar region occupies a much wider range of time scales than that in the purely solenoidal driving case. Regardless of the type of driving force, the probability density functions of the velocity increment collapse onto one another for the time scales in the new self-similar region after proper normalization.

scholarly journals Frequency Power Spectra of Global Quantities in Unsteady Magnetoconvection

Fluids ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 163
Author(s):  
Sandip Das ◽  
Krishna Kumar
Keyword(s):  
Heat Flux ◽  
Power Spectra ◽  
Direct Numerical Simulations ◽  
Scaling Exponent ◽  
Spectral Densities ◽  
Frequency Space ◽  
Power Spectral ◽  
Power Spectral Densities ◽  
Rayleigh Benard ◽  
Frequency Power

We present the results of direct numerical simulations of power spectral densities for kinetic energy, convective entropy, and heat flux for unsteady Rayleigh–Bénard magnetoconvection in the frequency space. For larger values of frequency, the power spectral densities for all the global quantities vary with frequency (f) as f−2. The scaling exponent is independent of Rayleigh number, Chandrasekhar’s number, and thermal Prandtl number.

scholarly journals Blind Visualization of Task-Related Networks From Visual Oddball Simultaneous EEG-fMRI Data: Spectral or Spatiospectral Model?

2021 ◽  
Vol 12 ◽  
Author(s):  
René Labounek ◽  
Zhuolin Wu ◽  
David A. Bridwell ◽  
Milan Brázdil ◽  
Jiří Jan ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Power Spectra ◽  
Spectral Model ◽  
Dorsal Part ◽  
Frontal Part ◽  
Sensory Motor ◽  
Spectral Patterns ◽  
The Relationship ◽  
Visual Oddball ◽  
F Statistics

Various disease conditions can alter EEG event-related responses and fMRI-BOLD signals. We hypothesized that event-related responses and their clinical alterations are imprinted in the EEG spectral domain as event-related (spatio)spectral patterns (ERSPat). We tested four EEG-fMRI fusion models utilizing EEG power spectra fluctuations (i.e., absolute spectral model - ASM; relative spectral model - RSM; absolute spatiospectral model - ASSM; and relative spatiospectral model - RSSM) for fully automated and blind visualization of task-related neural networks. Two (spatio)spectral patterns (high δ4 band and low β1 band) demonstrated significant negative linear relationship (pFWE < 0.05) to the frequent stimulus and three patterns (two low δ2 and δ3 bands, and narrow θ1 band) demonstrated significant positive relationship (p < 0.05) to the target stimulus. These patterns were identified as ERSPats. EEG-fMRI F-map of each δ4 model showed strong engagement of insula, cuneus, precuneus, basal ganglia, sensory-motor, motor and dorsal part of fronto-parietal control (FPCN) networks with fast HRF peak and noticeable trough. ASM and RSSM emphasized spatial statistics, and the relative power amplified the relationship to the frequent stimulus. For the δ4 model, we detected a reduced HRF peak amplitude and a magnified HRF trough amplitude in the frontal part of the FPCN, default mode network (DMN) and in the frontal white matter. The frequent-related β1 patterns visualized less significant and distinct suprathreshold spatial associations. Each θ1 model showed strong involvement of lateralized left-sided sensory-motor and motor networks with simultaneous basal ganglia co-activations and reduced HRF peak and amplified HRF trough in the frontal part of the FPCN and DMN. The ASM θ1 model preserved target-related EEG-fMRI associations in the dorsal part of the FPCN. For δ4, β1, and θ1 bands, all models provided high local F-statistics in expected regions. The most robust EEG-fMRI associations were observed for ASM and RSSM.

scholarly journals Physics of blastocoel formation by hydro-osmotic lumen coarsening

2020 ◽  
Author(s):  
Mathieu Le Verge–Serandour ◽  
Hervé Turlier
Keyword(s):  
Scaling Law ◽  
Dynamic Scaling ◽  
Scaling Exponent ◽  
Spatial Bias ◽  
Blastula Stage ◽  
Early Embryos ◽  
Minor Influence ◽  
Self Similar ◽  
A Minor ◽  
Single Cavity

The blastocoel is a fluid-filled cavity characterizing early embryos at blastula stage. It is commonly described as the result of cell division patterning, but in tightly compacted embryos the mechanism underlying its emergence remains unclear. Based on experimental observations, we discuss an alternative physical model by which a single cavity forms by growth and coarsening of myriad of micrometric lumens interconnected through the intercellular space. Considering explicitly ion and fluid exchanges, we find that cavity formation is primarily controlled by hydraulic fluxes, with a minor influence of osmotic heterogeneities on the dynamics. Performing extensive numerical simulations on 1-dimensional chains of lumens, we show that coarsening is self-similar with a dynamic scaling exponent reminiscent of dewetting films over a large range of ion and water permeability values. Adding active pumping of ions to account for lumen growth largely enriches the dynamics: it prevents from collective collapse and leads to the emergence of a novel coalescence-dominated regime exhibiting a distinct scaling law. Finally, we prove that a spatial bias in pumping may be sufficient to position the final cavity, delineating hence a novel mode of symmetry breaking for tissue patterning. Providing generic testable predictions our hydro-osmotic coarsening theory highlights the essential roles of hydraulic and osmotic flows in development, with expected applications in early embryogenesis and lumenogenesis.

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