On the seismic discontinuities detection in 3D wavelet domain Xiaokai Wang* and Jinghuai Gao Institute.

Slides:



Advertisements
Similar presentations
A Theory For Multiresolution Signal Decomposition: The Wavelet Representation Stephane Mallat, IEEE Transactions on Pattern Analysis and Machine Intelligence,
Advertisements

Time-frequency-domain modal identification of ambient vibration structures using Wavelet Transform Numerical example.
DFT/FFT and Wavelets ● Additive Synthesis demonstration (wave addition) ● Standard Definitions ● Computing the DFT and FFT ● Sine and cosine wave multiplication.
Feature Detection and Outline Registration in Dorsal Fin Images A. S. Russell, K. R. Debure, Eckerd College, St. Petersburg, FL Most Prominent Notch analyze.
Wavelet Transform Modulus Maxima ridge and its application on Stratigraphic Profiling STUDENT: R CHUN-HSIANG WANG LECTURER: JIAN-JIUN DING DATE:
Abrupt Feature Extraction via the Combination of Sparse Representations Wei Wang, Wenchao Chen, Jinghuai Gao, Jin Xu Institute of Wave & Information, Xi’an.
Tom Wilson, Department of Geology and Geography Environmental and Exploration Geophysics II tom.h.wilson
Communication & Multimedia C. -H. Hong 2015/6/12 Contourlet Student: Chao-Hsiung Hong Advisor: Prof. Hsueh-Ming Hang.
Time-Frequency and Time-Scale Analysis of Doppler Ultrasound Signals
Wavelet Transform 國立交通大學電子工程學系 陳奕安 Outline Comparison of Transformations Multiresolution Analysis Discrete Wavelet Transform Fast Wavelet Transform.
Undecimated wavelet transform (Stationary Wavelet Transform)
Total Variation Imaging followed by spectral decomposition using continuous wavelet transform Partha Routh 1 and Satish Sinha 2, 1 Boise State University,
Xi’an Jiaotong University 1 Quality Factor Inversion from Prestack CMP data using EPIF Matching Jing Zhao, Jinghuai Gao Institute of Wave and Information,
ECE Spring 2010 Introduction to ECE 802 Selin Aviyente Associate Professor.
Smart Traveller with Visual Translator for OCR and Face Recognition LYU0203 FYP.
Imaging of diffraction objects using post-stack reverse-time migration
Transforms: Basis to Basis Normal Basis Hadamard Basis Basis functions Method to find coefficients (“Transform”) Inverse Transform.
Multiscale transforms : wavelets, ridgelets, curvelets, etc.
CS 485/685 Computer Vision Face Recognition Using Principal Components Analysis (PCA) M. Turk, A. Pentland, "Eigenfaces for Recognition", Journal of Cognitive.
Geol 755: Basin Analysis Geophysics Week 1
Wavelets Series Used to Solve Dynamic Optimization Problems Lizandro S. Santos, Argimiro R. Secchi, Evaristo. C. Biscaia Jr. Programa de Engenharia Química/COPPE,
Wavelets: theory and applications
MULTITEMP 2005 – Biloxi, Mississippi, USA, May 16-18, 2005 Remote Sensing Laboratory Dept. of Information and Communication Technology University of Trento.
Characterizing a fault-zone and associated fractures using lab experiments and attribute-based seismic analysis: Zonghu Liao 1* ), Nabanita.
Geology 5660/6660 Applied Geophysics 24 Feb 2014 © A.R. Lowry 2014 For Wed 26 Feb: Burger (§8.4) Last Time: Industry Seismic Interpretation Well.
Seismic Thickness Estimation: Three Approaches, Pros and Cons Gregory A. Partyka bp.
2D phase unwrapping by DCT method Kui Zhang, Marcilio Castro de Matos, and Kurt J. Marfurt ConocoPhillips School of Geology & Geophysics, University of.
OPTIMIZATION OF FUNCTIONAL BRAIN ROIS VIA MAXIMIZATION OF CONSISTENCY OF STRUCTURAL CONNECTIVITY PROFILES Dajiang Zhu Computer Science Department The University.
Uncertainty Maps for Seismic Images through Geostatistical Model Randomization Lewis Li, Paul Sava, & Jef Caers 27 th SCRF Affiliates’ Meeting May 8-9.
Contrasts & Inference - EEG & MEG Himn Sabir 1. Topics 1 st level analysis 2 nd level analysis Space-Time SPMs Time-frequency analysis Conclusion 2.
Basics Course Outline, Discussion about the course material, reference books, papers, assignments, course projects, software packages, etc.
A Two-level Pose Estimation Framework Using Majority Voting of Gabor Wavelets and Bunch Graph Analysis J. Wu, J. M. Pedersen, D. Putthividhya, D. Norgaard,
1 Registration algorithm based on image matching for outdoor AR system with fixed viewing position IEE Proc.-Vis. Image Signal Process., Vol. 153, No.
“Digital stand for training undergraduate and graduate students for processing of statistical time-series, based on fractal analysis and wavelet analysis.
Fast Fourier Transform & Assignment 2
CCN COMPLEX COMPUTING NETWORKS1 This research has been supported in part by European Commission FP6 IYTE-Wireless Project (Contract No: )
Fractures play a major role in many tight reservoirs such as shale, carbonate, and low permeability sand by providing fluid flow conduits, for this reason.
1 Wavelet Transform. 2 Definition of The Continuous Wavelet Transform CWT The continuous-time wavelet transform (CWT) of f(x) with respect to a wavelet.
Wavelet Spectral Analysis Ken Nowak 7 December 2010.
On Optimization Techniques for the One-Dimensional Seismic Problem M. Argaez¹ J. Gomez¹ J. Islas¹ V. Kreinovich³ C. Quintero ¹ L. Salayandia³ M.C. Villamarin¹.
1 Chapter 02 Continuous Wavelet Transform CWT. 2 Definition of the CWT The continuous-time wavelet transform (CWT) of f(t) with respect to a wavelet 
WAVELET AND IDENTIFICATION WAVELET AND IDENTIFICATION Hamed Kashani.
Fourier and Wavelet Transformations Michael J. Watts
Time-frequency analysis of thin bed using a modified matching pursuit algorithm Bo Zhang Graduated from AASP consortium of OU in 2014 currently with The.
An Improved Approach For Image Matching Using Principle Component Analysis(PCA An Improved Approach For Image Matching Using Principle Component Analysis(PCA.
Computing Attributers on Depth-Migrated Data Name : Tengfei Lin Major : Geophysics Advisor : Kurt J. Marfurt AASPI,The University of Oklahoma 1.
The Story of Wavelets Theory and Engineering Applications
By Dr. Rajeev Srivastava CSE, IIT(BHU)
Wavelet Transforms ( WT ) -Introduction and Applications
Jun Li 1, Zhongdong Yang 1, W. Paul Menzel 2, and H.-L. Huang 1 1 Cooperative Institute for Meteorological Satellite Studies (CIMSS), UW-Madison 2 NOAA/NESDIS/ORA.
In The Name of God The Compassionate The Merciful.
Continuous wavelet transform of function f(t) at time relative to wavelet kernel at frequency scale f: "Multiscale reconstruction of shallow marine sediments.
Environmental and Exploration Geophysics II tom.h.wilson
WLD: A Robust Local Image Descriptor Jie Chen, Shiguang Shan, Chu He, Guoying Zhao, Matti Pietikäinen, Xilin Chen, Wen Gao 报告人:蒲薇榄.
Earth models for early exploration stages PETROLEUM ENGINEERING ÂNGELA PEREIRA Introduction Frontier basins and unexplored.
Micro-terrain feature identification and processing: An overview with practical implementations along with discussion of a potential application area of.
Progress in phase unwrapping
Wavelet domain image denoising via support vector regression
Wavelet Transform Advanced Digital Signal Processing Lecture 12
Adam Zadrożny The Andrzej Sołtan Institute for Nuclear Studies
On Optimization Techniques for the One-Dimensional Seismic Problem
Supervised Time Series Pattern Discovery through Local Importance
Wavelets : Introduction and Examples
VII. Other Time Frequency Distributions (II)
Fourier and Wavelet Transformations
IGRASS2011 An Interferometric Coherence Optimization Method Based on Genetic Algorithm in PolInSAR Peifeng Ma, Hong Zhang, Chao Wang, Jiehong Chen Center.
Multi-resolution analysis
Windowed Fourier Transform
Classes of seismic attributes?
Chapter 15: Wavelets (i) Fourier spectrum provides all the frequencies
Presentation transcript:

On the seismic discontinuities detection in 3D wavelet domain Xiaokai Wang* and Jinghuai Gao Institute of Wave and Information, Xi’an Jiaotong University Xi'an, Shaanxi, , P.R. China International Symposium on Geophysical Imaging with Localized Waves Sanya, Hainan, July, 2011

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Outlines Introduction Principles of 2D/3D CWT Seismic discontinuity detection based on 2D/3DCWT Field-data examples Conclusions and future works Acknowledgements

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Introductions The consistent and reliable detection of seismic discontinuity provides interpreters powerful means to quickly visualize and map complex ge- ological structures. The computational cost of these methods, such as C3 algorithm (Gersztenkorn & Marfurt, 1998) and LSE (Cohen & Coif- man, 2002), will increase as analyzing window widen. 1D CWT can not properly characterize the correlated information bet- ween neighboring traces. Boucherea applied 2D CWT (Antoine, 2004) with Morlet to detect the faults in a seismogram (Bouchereau, 1997). 2D CWT has some shortages for 3D seismic data which was frequen- tly used in industry. 3D CWT has good properties such as multiscale and orientation sele- ctivity, which has the potential to detect the seismic discontinuities directly. So we choose 3D CWT as a novel tool to detect seismic disc- ontinuity.

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Operations on mother wavelet Translation Dilation Rotation Use 2D Morlet as an example to illustrate three operations Principles of 2D/3D CWT Three operation on mother wavelet ψ( ) : translation, dilation, rotation :translated factor :dilated factor :rotated operator

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU The definition of 2D/3D CWT Realizing in Space domain Fast Realizing in wavenumber domain by using 2D/3D FFT : 2D/3D signal to be analyzed : 2D/3D operated wavelet 2D CWT: dilated factor is 1D variable, translated factor is a 2D vector, and rotated operator only contains a dip . 3D CWT: dilated factor is 1D variable, translated factor is a 3D vector, and rotated operator contains a dip  and a azimuth . Principles of 2D/3D CWT

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Two common-use slice/cube of 2D/3D CWT 2D CWT (i) The position slice: a and  are fixed and the slice of 2DCWT coefficients is considered as a function of position. (ii) The scale-angle slice: position is fixed and the slice of 2DCWT coefficients is considered as a function of a and . High dimension of 2D/3D CWT coefficients Use slice/cube to visualize 3D CWT (i) The position cube: a,  and  are fixed and the cube of 3DCWT coefficients is considered as a function of position. (ii) The scale-angle cube: position is fixed and the cube of 3DCWT coefficients is considered as a function of ,  and . Principles of 2D/3D CWT

Institute of Wave and Information, XJTU 2D signal to be analyzed (contains 6 damping plane waves) The scale-angle slice of 2DCWT Coeffs. (modulus, in origin) 2DCWT The position slice of 2DCWT Coeffs. (phase)

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU 2D signal to be analyzed The position slice of 2DCWT Coeffs. (small scale,  =135º, modulus) Orientation selectivity of 2DCWT Principles of 2D/3D CWT

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU discontinuity detection based on 2D/3DCWT Part of oilfield data (a), small scale 2DCWT’s modulus in position A (b) and small scale 2DCWT’s modulus in position B (c) Two dimension Three dimension

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU We summarize the complete procedure of seismic discontinuities detection method based on 3D CWT as follows: 1.Extract the Instantaneous phase (IP) of 3D seismic data by using Hilbert transform (or 1D wavelet transform), and get the IP cube IP(x,y,t); 2. Obtain the a new cubes IP_exp(x,y,t) by using exp[j* IP(x,y,t)]. (ps: by doing this, the phase’s jump from 180º to -180º can be overcame); 3. Choose the scale and dip/azimuth searching region; 4. Do 3D CWT to IP_exp(x,y,t) and get the a series of 3D CWT coefficients (many position cubes), and obtain the modulus of these coefficients; 5. In each point, get the largest coefficients and assign the modulus as the discontinuity measure of this point. the complete procedure of our method

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU A B A B Field-data example 1 Time slice of coherence (common used software) Time slice of our results (based on 3D CWT) C C

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Conclusions and future works Conclusions Future works 1.2D/3D continuous wavelet transform is a useful tool with multiscale properties and orientation selectivity; 1.The mother wavelet will effect the results, and more attention should be focused on choosing wavelets or proposing a new wavelet; 2. In order to depict more geological structure, more researches should be carried on to construct different measures in high dimensional continuous wavelet transform domain. 2. The computation cost will not increase as the size of analyzing win- dow enlarging by realizing high dimensional CWT in wave-number domain through FFT algorithm; 3.The field-data examples show our method can detect seismic disco- ntinuities more subtly comparing with commonly used methods ;

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU Acknowledgements 1.We thank National Natural Science Foundation of China ( , ), National 863 Program (2006A09- A102) and National Science & Technology Major Project (2008ZX , 2008ZX ) for their supports. 2. We thank Research center of China national offshore oil corporation for providing field-data. We also thank Erhua Zhang in Exploration and Development Research Institute of Daqing Oilfield Company Ltd. for the help of interpretation.

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU References [1] A. Gersztenkorn, and K.J. Marfurt, “Eigenstructure-based coherence computations as an aid to 3D structural and stratigraphic mapping,” Geophysics, vol.64, No.5, pp , [2] I. Cohen, and R.R. Coifman, “Local discontinuity measures for 3D seismic data,” Geophysics, vol.67, pp , [3] S. Mallat, A Wavelet Tour of Signal Processing, Second Edition, Elsevier, [4] E.B. Bouchereau, “analyse d’images par transformees en ondelettes: Ph.D. Thesis,” Universite Jose- ph Fourier. [5] G., Ouillon, D., Sornette and C., Castaing, 1995, Organization of joints and faults from 1-cm to 100-km scales revealed by optimized anisotropic wavelet coefficient method and multifractal analysis: Nonlinear processes in geophysics, 2, [6] J.P., Antoine, R. Murenzi, P., Vandergheynst and S.T., Ali, 2004, Two-Dimensional wavelets and their relatives: Cambridge University Press. [7] J.P., Antoine, and R., Murenzi, 1996, Two-dimensional directional wavelets and the scale-angle representation: Signal processing, 52, [8] Xiaokai Wang, et.al.. 2D seismic attributes extraction based on two-dimensional continuous wavelet transform. 79th Annual Internation meeting, SEG Expanded Abstracts, pp , [9] Xiaokai Wang, Jinghuai Gao, Wenchao Chen, Erhua Zhang: On the method of detecting the discontinuity of seismic data via 3D wavelet transform. IGARSS 2010:

XI’AN JIAOTONG UNIVERSITY Institute of Wave and Information, XJTU