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Data Processing SIG

Tuesday 2-Dec-08 5:00 PM to 7:00 PM CST

PGS

15150 Memorial Drive
Houston TX 77079
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Speaker Milos Cvetkovic, Yang Liu

Event Description

Milos Cvetkovic, GXT

Some applications of Wavelet Transform in Seismic Data processing

Ground-roll, swell noise, guided waves, and random noise are just some of most persistent types of noise in land, marine and OBC data. These types of noise can be hard to remove with traditional, Fourier based methods without damage to the signal. Wavelet Transforms present relatively new set of tools to aid seismic processing, and they have been successfully applied for compressing and de-noising purposes. In this talk I will give brief theoretical background on Wavelet Transforms and details about Wavelet Transform based filters and algorithms used in the research community. For prestack data I will show results of both 1D and 2D Stationary Wavelet Transform (SWT) -based filters for ground-roll and coherent noise removal. For poststack data I use 2D SWT filters for acquisition footprints and random noise suppression. F-X deconvolution and resolution enhancement in wavelet transform domain are the most recent applications of SWT with preliminary promising results.

Yang Liu, University of Texas

High-order seislet transform

The seislet transform is a wavelet-like transform that analyzes seismic data by following variable slopes of seismic events across different scales. In the case of multiple components, the transform turns into a frame (an invertible overcomplete representation) and becomes suitable for analyzing data with multiple frequencies (in 1-D) or multiple plane-wave slopes (in 2-D and 3-D). We extend this approach to a higher order, using the Cohen-Daubechies-Feauveau 9/7 biorthogonal wavelet transform (the basis for the JPEG2000 compression scheme) as a template.
Using synthetic and field-data examples, we demonstrate that the new transform can provide a better compression rate for seismic events than the Fourier transform, discrete wavelete transform, or the low-order seislet transform. Therefore, the high-order seislet transform can be more suitable for data processing tasks such as data regularization and noise attenuation.

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Event Contact	Event Coordinator
Raymond Abma	Clive Gerrard
(281) 366-4604	(281) 509-8183

Data Processing SIG

Tuesday 2-Dec-08 5:00 PM to 7:00 PM CST

Speaker Milos Cvetkovic, Yang Liu

Biography

Speaker #1
Milos Cvetkovic received a BS (2005) in Geophysics from Belgrade University, Serbia and a MSc (2007) in Geophysics from University of Houston. His master thesis was titled �Some Applications of Wavelet Transform in Seismic Data Processing�, with Dr.Hua-wei Zhou and Dr. Kurt J. Marfurt.
In 2007 he worked as an intern at BP America on the Advanced Seismic Imaging Team with Dr. Zhou Yu. Currently he is working in the DHS group at IONGEO GXT Imaging Solutions. He was the SEG Dr. Robert E. Sheriff and Leon Thomsen / BP scholar at University of Houston and received several awards for academic achievements.
His current research interests are in the application of 3D Wavelet and 3D Curvelet Transforms for seismic data, resolution enhancement techniques and attribute analysis.

Speaker #2
Yang Liu is a postdoctoral fellow at the Bureau of Economic Geology,
the University of Texas at Austin.
Dr. Liu received his M.S. (2003) and Ph.D. (2006) from College of Geo-Exploration Science
and Technology, Jilin University in China.
His research interests are seismic data regularization and noise attenuation.