Essentials of Geophysical Data Processing

2021 ◽  
Author(s):  
Clark R. Wilson
Keyword(s):  
Time Series ◽  
Data Processing ◽  
Environmental Science ◽  
Sampling Theorem ◽  
Geophysical Data ◽  
Computing Environment ◽  
Science And Engineering ◽  
Advanced Students ◽  
Processing Techniques ◽  
Real World Problems

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual and all the figures from the book as PowerPoints for course instructors.

Method of preview processing of the primary geoelectromagnetic data received from a modified geophysical automatic station

2019 ◽  
Vol 24 (3-4) ◽  
pp. 93-106
Author(s):  
Shakhovska N. ◽  
◽  
Kaminsky R. ◽  
Savkiv L. ◽  
Varetsky Y. ◽  
...  
Keyword(s):  
Time Series ◽  
Electric Field ◽  
Data Processing ◽  
Mathematical Models ◽  
Geophysical Data ◽  
Descriptive Statistics ◽  
Primary Data ◽  
Preliminary Processing ◽  
Natural Electric Field ◽  
Automatic Station

Preliminary processing of primary geophysical data, automatically transmitted from the regime geophysical station to the daily specific files confirmed the feasibility of using such approaches. The purpose of the research is to focus on the choice of simple methods of primary data processing and the development of appropriate mathematical models of the dynamics. The results of preliminary processing of the primary data obtained from the regime geophysical automatic station are submitted. Descriptive statistics and simulation of time series were used as processing methods. The presentation of the results by multidimensional graphs allowed to reveal the phenomenon of coincidence in the first indicators of descriptive statistics, and in the second, the coincidence of the model's coefficients for the daily measurements of the natural electric field

Gaussian scaling noise model of seismic reflection sequences: Evidence from well logs

Geophysics ◽  
1990 ◽  
Vol 55 (4) ◽  
pp. 480-484 ◽  
Author(s):  
J. P. Todoeschuck ◽  
O. G. Jensen ◽  
S. Labonte
Keyword(s):  
Simple Model ◽  
Data Processing ◽  
Seismic Reflection ◽  
Geophysical Data ◽  
Well Logs ◽  
Noise Model ◽  
Self Similarity ◽  
Predictive Deconvolution ◽  
Organ Pipe ◽  
Processing Techniques

A simple model for reflection series is desirable for two reasons: first, to have a means of generating model reflection sequences on which to test geophysical data processing techniques, specifically methods of predictive deconvolution, and second, to suggest a way of parameterizing real reflection sequences for classification and further geologic study. In this note we wish to discuss a model suggested by Hosken (1980); our discussion is founded upon the powerful ideas of self‐similarity and scaling developed by Mandelbrot (1983) and on the paucity of typical lengths in geology. Typical lengths are common in physics problems; for example, the length of an organ pipe governs the wavelengths of the notes played. When taking photographs, geologists include some manmade object to give scale to the photo. Otherwise it is very hard to tell if, say, folds are of centimeter size or form whole mountains.

Review of data processing techniques for density profile evaluation from broadband FM-CW reflectometry on ASDEX Upgrade

2006 ◽  
Vol 46 (9) ◽  
pp. S693-S707 ◽  
Author(s):  
P Varela ◽  
M.E Manso ◽  
A Silva ◽  
the CFN Team ◽  
the ASDEX Upgrade Team
Keyword(s):  
Data Processing ◽  
Density Profile ◽  
Processing Techniques
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