Signal Processing for geologists and geophysicists Hack 5.0 + Redeem Codes
Developer: ODYSYS SARL
Category: Education
Price: Free
Version: 5.0
ID: com.odysys.signalprocessing
Screenshots
Description
ABOUT THIS COURSE
This course introduces signal processing tools currently used in geophysics. It has been elaborated both from the book "Signal processing for geologists and geophysicists" (J.L. Mari, F. Glangeaud, F. Coppens, 1999) and from the CD "Signal processing in geosciences" (F. Glangeaud ,J.L. Mari, 2000).
For signal processing specialists, it will be a source of how classical or new theories can be applied to field data.Teaching staff should find it provides a means of tackling the teaching signal processing techniques.
- - -
FOREWORD
This on line course presents a succession of lessons classed by theme. The different themes that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
• Filtering
• Near Surface Geophysics
• Stochastic Signal Processing
• Attributes
Each theme has an introduction and a series of lessons which are associated with it. A lesson comprises of text, a video, a formulary, if judged necessary, and in some cases an applet to practice.
• The text present has been voluntarily reduced; its objective is put across by the animation. This objective may be the presentation of a specific transform used in signal processing and applied in seismic processing. The term "transform" is used here in a very general sense. It covers at times the notion of transformation, such as the Fourier transformation or filters such as the Wiener filter. The objective perhaps being to show the application of a "transform" on simulated synthetic data or on real acquired geophysical data.
• The video is an illustration of the text. It permits a visualization of the data, to study the influence of processing parameters on the data. The images were conceived in a manner which permits an immediate visual comparison and that enables an evaluation of the influence of a parameter change on the data processing. If an applet is associated with the video, some parameters can be modified by moving the cursors, the calculations taking place in real time.
• The formulary gives the mathematical formula used in the animation. The reader is invited to use the book cited above as a reference for the notations used and the demonstrations. The formulary should be considered as a simple memory aid.
The videos and the applets have been created thanks to the MUSTIG software ( mustig.free.fr, Gérard Lejeune).
In this on line course, 20 lessons can be selected. For the animations based on field data measurement, the authors or organisms that provide with them are mentioned.
This on line course does not constitute a complete course in itself ; referral to the basic signal processing texts remains essential.
- - -
THE AUTHOR
Jean-Luc Mari is at present a geophysics professor at IFP School and an IFPEN expert. He supervises the MSc research program in "Lithosphere, Basins, Petroleum" part of the Master's program in Science and Technology (Paris VI).
Jean-Luc Mari is a member of the European Association of Geoscientists and Engineers.
Jean-Luc Mari is author and co-author of patents (in the field of acoustic well logging), numerous scientific articles and books on geophysical methods and signal processing.
He has been involved in the design and development of specific teaching aids (on-line (http://www-ig.unil.ch/cours/) and CD-ROMs).
His main fields of expertise are seismic acquisition and processing, geophysics of reservoirs and civil engineering.
This course introduces signal processing tools currently used in geophysics. It has been elaborated both from the book "Signal processing for geologists and geophysicists" (J.L. Mari, F. Glangeaud, F. Coppens, 1999) and from the CD "Signal processing in geosciences" (F. Glangeaud ,J.L. Mari, 2000).
For signal processing specialists, it will be a source of how classical or new theories can be applied to field data.Teaching staff should find it provides a means of tackling the teaching signal processing techniques.
- - -
FOREWORD
This on line course presents a succession of lessons classed by theme. The different themes that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
• Filtering
• Near Surface Geophysics
• Stochastic Signal Processing
• Attributes
Each theme has an introduction and a series of lessons which are associated with it. A lesson comprises of text, a video, a formulary, if judged necessary, and in some cases an applet to practice.
• The text present has been voluntarily reduced; its objective is put across by the animation. This objective may be the presentation of a specific transform used in signal processing and applied in seismic processing. The term "transform" is used here in a very general sense. It covers at times the notion of transformation, such as the Fourier transformation or filters such as the Wiener filter. The objective perhaps being to show the application of a "transform" on simulated synthetic data or on real acquired geophysical data.
• The video is an illustration of the text. It permits a visualization of the data, to study the influence of processing parameters on the data. The images were conceived in a manner which permits an immediate visual comparison and that enables an evaluation of the influence of a parameter change on the data processing. If an applet is associated with the video, some parameters can be modified by moving the cursors, the calculations taking place in real time.
• The formulary gives the mathematical formula used in the animation. The reader is invited to use the book cited above as a reference for the notations used and the demonstrations. The formulary should be considered as a simple memory aid.
The videos and the applets have been created thanks to the MUSTIG software ( mustig.free.fr, Gérard Lejeune).
In this on line course, 20 lessons can be selected. For the animations based on field data measurement, the authors or organisms that provide with them are mentioned.
This on line course does not constitute a complete course in itself ; referral to the basic signal processing texts remains essential.
- - -
THE AUTHOR
Jean-Luc Mari is at present a geophysics professor at IFP School and an IFPEN expert. He supervises the MSc research program in "Lithosphere, Basins, Petroleum" part of the Master's program in Science and Technology (Paris VI).
Jean-Luc Mari is a member of the European Association of Geoscientists and Engineers.
Jean-Luc Mari is author and co-author of patents (in the field of acoustic well logging), numerous scientific articles and books on geophysical methods and signal processing.
He has been involved in the design and development of specific teaching aids (on-line (http://www-ig.unil.ch/cours/) and CD-ROMs).
His main fields of expertise are seismic acquisition and processing, geophysics of reservoirs and civil engineering.
Version history
5.0
2016-09-19
This app has been updated by Apple to display the Apple Watch app icon.
A new subject entitled “Attributes” has been added.
In the “ Near surface geophysics” subject, the lesson “ Flow” has been added.
In the “Stochastic Signal Processing” subject, the lesson “Depth conversion” has been added.
The subjects “Seismic applications” and “ Dispersive waves” have been merged in a single subject” Seismic applications”
The “ Attribute” subject is composed of 6 lessons. In the session, we give the fundamentals on the main seismic attributes. We show how signal processing tools are used to create the attributes. Through examples, we illustrate the applications of seismic attributes to seismic processing and interpretation:
• Envelope
• RMS-Amplitude
• Instantaneous Phase
• Instantaneous Frequency
• Dip & Azimuth
• Coherency
Now, the different subjects that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
• Filtering
• Near Surface Geophysics
• Stochastic Signal Processing
• Attributes
A new subject entitled “Attributes” has been added.
In the “ Near surface geophysics” subject, the lesson “ Flow” has been added.
In the “Stochastic Signal Processing” subject, the lesson “Depth conversion” has been added.
The subjects “Seismic applications” and “ Dispersive waves” have been merged in a single subject” Seismic applications”
The “ Attribute” subject is composed of 6 lessons. In the session, we give the fundamentals on the main seismic attributes. We show how signal processing tools are used to create the attributes. Through examples, we illustrate the applications of seismic attributes to seismic processing and interpretation:
• Envelope
• RMS-Amplitude
• Instantaneous Phase
• Instantaneous Frequency
• Dip & Azimuth
• Coherency
Now, the different subjects that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
• Filtering
• Near Surface Geophysics
• Stochastic Signal Processing
• Attributes
4.0
2016-03-17
Four new themes have been added:
• Filtering
• Dispersive Waves
• Near surface geophysics
• Stochastic signal processing
• Filtering
• Dispersive Waves
• Near surface geophysics
• Stochastic signal processing
3.0
2015-06-07
A new theme entitled “The Hilbert transformation” has been added. Some additional lessons have been introduced in the topics “wave separation” and “seismic applications”.
In the “Wave separation” subject, the following lessons have been added:
• Vertical Seismic Profile
• Selection of a Rayleigh wave by a polarization filter
In the “Seismic applications” subject, the following lessons have been added:
• Dispersion analysis of Rayleigh waves
• Love Waves
• Refaction-Reflection seismic survey
• Seismic processing with an industrial software
• 3D seismic example
The Hilbert transformation subject is composed of 8 lessons which illustrate the main applications of the Hilbert transform in seismics:
• computing an envelope
• introducing a phase change
• measuring the instantaneous frequency of a sweep
• computing an analytic signal
• studying the polarization of a wave
• separating wave by polarization filters
• studying group and phase velocities
• transforming a signal into a zero phase signal
Now, the different themes that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
In the “Wave separation” subject, the following lessons have been added:
• Vertical Seismic Profile
• Selection of a Rayleigh wave by a polarization filter
In the “Seismic applications” subject, the following lessons have been added:
• Dispersion analysis of Rayleigh waves
• Love Waves
• Refaction-Reflection seismic survey
• Seismic processing with an industrial software
• 3D seismic example
The Hilbert transformation subject is composed of 8 lessons which illustrate the main applications of the Hilbert transform in seismics:
• computing an envelope
• introducing a phase change
• measuring the instantaneous frequency of a sweep
• computing an analytic signal
• studying the polarization of a wave
• separating wave by polarization filters
• studying group and phase velocities
• transforming a signal into a zero phase signal
Now, the different themes that are tackled are:
• The Fourier Transformation
• Common functions in spectral analysis
• Sampling
• Correlation
• Wave separation
• Seismic applications
• The Hilbert transformation
2.0
2014-09-03
A new theme entitled “The Hilbert transformation” has been added. Some additional lessons have been introduced in the topics “wave separation” and “seismic applications”.
In the “Wave separation” subject, the following lessons have been added:
•Vertical Seismic Profile
•Selection of a Rayleigh wave by a polarization filter
In the “Seismic applications” subject, the following lessons have been added:
•Dispersion analysis of Rayleigh waves
•Love Waves
•Refaction-Reflection seismic survey
•Seismic processing with an industrial software
•3D seismic example
The Hilbert transformation subject is composed of 8 lessons which illustrate the main applications of the Hilbert transform in seismics:
•computing an envelope
•introducing a phase change
•measuring the instantaneous frequency of a sweep
•computing an analytic signal
•studying the polarization of a wave
•separating wave by polarization filters
•studying group and phase velocities
•transforming a signal into a zero phase signal
Now, the different themes that are tackled are:
•The Fourier Transformation
•Common functions in spectral analysis
•Sampling
•Correlation
•Wave separation
•Seismic applications
•The Hilbert transformation
In the “Wave separation” subject, the following lessons have been added:
•Vertical Seismic Profile
•Selection of a Rayleigh wave by a polarization filter
In the “Seismic applications” subject, the following lessons have been added:
•Dispersion analysis of Rayleigh waves
•Love Waves
•Refaction-Reflection seismic survey
•Seismic processing with an industrial software
•3D seismic example
The Hilbert transformation subject is composed of 8 lessons which illustrate the main applications of the Hilbert transform in seismics:
•computing an envelope
•introducing a phase change
•measuring the instantaneous frequency of a sweep
•computing an analytic signal
•studying the polarization of a wave
•separating wave by polarization filters
•studying group and phase velocities
•transforming a signal into a zero phase signal
Now, the different themes that are tackled are:
•The Fourier Transformation
•Common functions in spectral analysis
•Sampling
•Correlation
•Wave separation
•Seismic applications
•The Hilbert transformation
1.3
2013-01-12
Bug fixed
1.2
2012-12-01
- Bug fix
1.1
2012-10-19
Bug fixed, new splashscreen
1.0
2012-03-19
Ways to hack Signal Processing for geologists and geophysicists
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Ratings
5 out of 5
2 Ratings
Reviews
Fadhil O'bead,
Thank you 🙏🏻
Thank you so much for this app ❤️
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