scholarly journals Magnetic field data processing methods of the China Seismo-Electromagnetic Satellite

2018 ◽  
Vol 2 (6) ◽  
pp. 455-461 ◽  
Author(s):  
Bin Zhou ◽  
◽  
YanYan Yang ◽  
YiTeng Zhang ◽  
XiaoChen Gou ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Data Processing ◽  
Field Data ◽  
Processing Methods ◽  
Magnetic Field Data ◽  
Data Processing Methods

Comparison of Field Data Processing Methods for the Evaluation of Topographic Effects

2016 ◽  
Vol 32 (4) ◽  
pp. 2127-2147 ◽  
Author(s):  
Clinton M. Wood ◽  
Brady R. Cox
Keyword(s):  
Data Processing ◽  
Field Data ◽  
Reference Method ◽  
Spectral Ratio ◽  
Frequency Domain Analysis ◽  
Topographic Effects ◽  
Frequency Range ◽  
Data Set ◽  
Processing Methods ◽  
Data Processing Methods

This paper presents a comparison of field data processing methods used to evaluate topographic effects. A data set of 52 weak motion events recorded using a dense array of seismometers located on steep, complex topography is analyzed. Both time domain and frequency domain analysis methods are evaluated for effectiveness at resolving the amplitude and frequency range associated with topographic effects. Results from this study indicate the median reference method (MRM) provides a more stable estimate of the frequency range and expected amplification value than the standard spectral ratio (SSR) or horizontal-to-vertical spectral ratio (HVSR) methods.

scholarly journals LOCAL MAGNETIC FIELD DATA PROCESSING

2015 ◽  
Vol 62 (1) ◽  
Author(s):  
Ivan Ostroumov ◽  
Olena Mironyuk ◽  
Mykhailo Nychak
Keyword(s):  
Magnetic Field ◽  
Data Processing ◽  
Field Data ◽  
Local Magnetic Field ◽  
Magnetic Field Data

The energy balance experiment EBEX-2000. Part II: Intercomparison of eddy-covariance sensors and post-field data processing methods

2006 ◽  
Vol 123 (1) ◽  
pp. 29-54 ◽  
Author(s):  
Matthias Mauder ◽  
Steven P. Oncley ◽  
Roland Vogt ◽  
Tamas Weidinger ◽  
Luis Ribeiro ◽  
...  
Keyword(s):  
Energy Balance ◽  
Data Processing ◽  
Eddy Covariance ◽  
Field Data ◽  
Processing Methods ◽  
Data Processing Methods

An Augmented Iteratively Re-weighted and Refined Least Squares Method for lp Minimization Problem in Inverse Modeling of Potential Field Magnetic Data

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Maysam Abedi
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
Least Squares ◽  
Minimization Problem ◽  
Potential Field ◽  
Field Data ◽  
Least Squares Method ◽  
Porphyry Copper ◽  
Magnetic Data ◽  
Magnetic Field Data

The presented work examines application of an Augmented Iteratively Re-weighted and Refined Least Squares method (AIRRLS) to construct a 3D magnetic susceptibility property from potential field magnetic anomalies. This algorithm replaces an lp minimization problem by a sequence of weighted linear systems in which the retrieved magnetic susceptibility model is successively converged to an optimum solution, while the regularization parameter is the stopping iteration numbers. To avoid the natural tendency of causative magnetic sources to concentrate at shallow depth, a prior depth weighting function is incorporated in the original formulation of the objective function. The speed of lp minimization problem is increased by inserting a pre-conditioner conjugate gradient method (PCCG) to solve the central system of equation in cases of large scale magnetic field data. It is assumed that there is no remanent magnetization since this study focuses on inversion of a geological structure with low magnetic susceptibility property. The method is applied on a multi-source noise-corrupted synthetic magnetic field data to demonstrate its suitability for 3D inversion, and then is applied to a real data pertaining to a geologically plausible porphyry copper unit.  The real case study located in  Semnan province of  Iran  consists  of  an arc-shaped  porphyry  andesite  covered  by  sedimentary  units  which  may  have  potential  of  mineral  occurrences, especially  porphyry copper. It is demonstrated that such structure extends down at depth, and consequently exploratory drilling is highly recommended for acquiring more pieces of information about its potential for ore-bearing mineralization.

ANALYSIS OF THE FLOODING SYSTEM WITH APPLICATION OF STATISTICAL DATA PROCESSING METHODS

2020 ◽  
pp. 5-9
Author(s):  
A.Yu. Sentsov ◽  
◽  
I.V. Ryabov ◽  
A.A. Ankudinov ◽  
Yu.E. Radevich ◽  
...  
Keyword(s):  
Data Processing ◽  
Statistical Data ◽  
Processing Methods ◽  
Statistical Data Processing ◽  
Data Processing Methods

Use of Mathematical Modeling in Building Ceramics Functional Properties Studies

2016 ◽  
Vol 870 ◽  
pp. 191-195
Author(s):  
N.A. Vil'bitskaya ◽  
S.A. Vilbitsky ◽  
A.G. Avakyan
Keyword(s):  
Mathematical Modeling ◽  
Data Processing ◽  
Ceramic Material ◽  
Functional Properties ◽  
Statistical Data ◽  
Ceramic Tiles ◽  
Processing Methods ◽  
Statistical Data Processing ◽  
High Calcium ◽  
Data Processing Methods

The peculiarities of using mathematical and statistical data processing methods in studying the intensification in the process of sintering a ceramic material with a high content of high-calcium waste, and mineralizing sintering lithium-containing waste were studied. The region of optimal ceramic masses composition, which allows obtaining ceramic tiles with high functional properties, was defined.

Surface movement radar data processing methods for airport surveillance

2001 ◽  
Vol 37 (2) ◽  
pp. 563-585 ◽  
Author(s):  
J. Garcia Herrero ◽  
J.A. Besada Portas ◽  
F.J. Jimenez Rodriguez ◽  
J.R. Casar Corredera
Keyword(s):  
Data Processing ◽  
Radar Data ◽  
Processing Methods ◽  
Surface Movement ◽  
Radar Data Processing ◽  
Data Processing Methods

Data Processing Methods for a High Throughput Brain Imaging PET Research Center

2006 ◽  
Author(s):  
Judson P. Jones ◽  
Arman Rahmim ◽  
Merence Sibomana ◽  
Andrew Crabb ◽  
Ziad Burbar ◽  
...  
Keyword(s):  
Data Processing ◽  
Brain Imaging ◽  
High Throughput ◽  
Research Center ◽  
Processing Methods ◽  
Data Processing Methods

Data Processing Methods for Unsteady Pressure-Sensitive Paint Application

2018 ◽  
Author(s):  
Nettie Roozeboom ◽  
Christina Ngo ◽  
Jessica M. Powell ◽  
Jennifer Baerny ◽  
David Murakami ◽  
...  
Keyword(s):  
Data Processing ◽  
Pressure Sensitive Paint ◽  
Processing Methods ◽  
Unsteady Pressure ◽  
Pressure Sensitive ◽  
Data Processing Methods
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