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JFZ7195 | Improvement S/N Ratio By Noise Attenuation | 3+0+0 | ECTS:7.5 | Year / Semester | Spring Semester | Level of Course | Third Cycle | Status | Elective | Department | DEPARTMENT of GEOPHYSICAL ENGINEERING | Prerequisites and co-requisites | None | Mode of Delivery | Face to face, Practical | Contact Hours | 14 weeks - 3 hours of lectures per week | Lecturer | Prof. Dr. Hakan KARSLI | Co-Lecturer | None | Language of instruction | Turkish | Professional practise ( internship ) | None | | The aim of the course: | is to teach defining of the noises involving seismic data and new techniques, which improve signal-noise ratio, by filtering them from data. |
Programme Outcomes | CTPO | TOA | Upon successful completion of the course, the students will be able to : | | | PO - 1 : | learn making a distinction between signal and noise in the seismic data. | 4,6 | 1,3 | PO - 2 : | learn choosing an appropriate techniques according to noise problems. | 4,6 | 1,3 | PO - 3 : | learn noise attenuation and improving signal-noise ratio techniques which are unconventional. | 4,6 | 1,3 | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | |
Definition of Noises and Classification, Multiple and Noise Attenuation in Common Midpoint Domain, Frequency-Wavenumber Filtering, Slant-Stack Transformation, Radon Transformation, Linear Uncorrelated Noise Attenuation, Multichannel Filtering Techniques for Noise and Multiple Attenuation, F-X filtering, AR and ARMA Projection Filtering, Eigen Images and KL Transformation, Eigen Images and Fourier Transformation, Singular Value Decomposition, Time Variant Deconvolution, Time Variant Spectral Whitening, Frequency Domain Deconvolution, Invers Q Filtering, Deconvolution Strategies. |
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Course Syllabus | Week | Subject | Related Notes / Files | Week 1 | Definition of Noises and Classification | | Week 2 | Multichannel Filtering Techniques for Noise and Multiple Attenuation | | Week 3 | Multiple and Noise Attenuation in Common Midpoint Domain | | Week 4 | Frequency-Wavenumber Filters | | Week 5 | Radon Transform, Slant-Stack Transformation | | Week 6 | Linear Uncorrelated Noise Attenuation | | Week 7 | F-X filters | | Week 8 | AR and ARMA Projection Filters | | Week 9 | Mid-term exam | | Week 10 | Eigen Vectors, KL Transformation, Singular Value Decomposition | | Week 11 | Eigen Vectors and Fourier Transform | | Week 12 | Deconvolution Strategies | | Week 13 | Time Variant Deconvolution | | Week 14 | Time Variant Spectral Whitening | | Week 15 | Invers Q Filtering, Frequency Domain Deconvolution | | Week 16 | End-of-term exam | | |
1 | Ulrych, T. J. and Sacchi, M.D. (2005); Information-based inversion and processing with appplications, Elsevier, Vol 36, Amsterdam, Netherland. | | |
1 | Buttkus, B., 2000, Spectral Analysis and Filter Theory in Applied Geophysics, Springer-Verlag, Germany. | | 2 | Yilmaz, Ö. 2001; Seismic data Analysis: Processing, Inversion, and Interpretation of Seismic data. SEG Tulsa, OK, 2027 pp. | | |
Method of Assessment | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | Mid-term exam | 9 | 14/04/2012 | 2 | 30 | In-term studies (second mid-term exam) | 12 | 14/05/2012 | 2 | 20 | End-of-term exam | 16 | 11/06/2012 | 2 | 50 | |
Student Work Load and its Distribution | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | Yüz yüze eğitim | 3 | 14 | 42 | Sınıf dışı çalışma | 6 | 14 | 84 | Arasınav için hazırlık | 12 | 1 | 12 | Arasınav | 2 | 1 | 2 | Ödev | 6 | 7 | 42 | Dönem sonu sınavı için hazırlık | 16 | 1 | 16 | Dönem sonu sınavı | 2 | 1 | 2 | Total work load | | | 200 |
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