Regularization of the AVO inverse problem by means of a ...

More documents

Recommendations

Info

Examining Committee Dr. Mauricio D. Sacchi (Supervisor), Physics Dr. V. Kravchinsky (Chair and Examiner), Physics Dr. J. Gu (Examiner), Physics Dr. O. Leuangthong (Examiner), Faculty of Engineering
Abstract Amplitude Variation with Offset (AVO) inversion is one of the techniques that is being used to estimate subsurface physical parameters such as P-wave velocity, S-wave velocity, and density or their attributes. AVO inversion is an ill-conditioned problem which has to be reg- ularized in order to obtain a stable and unique solution. In this thesis, a Bayesian procedure that uses a Multivariate Cauchy distribution as a prior probability distribution is introduced. The prior includes a scale matrix that imposes correlation among the AVO attributes and induces a regularization that provokes solutions that are sparse and stable in the presence of noise. The performance of this regularization is demonstrated by both synthetic and real data examples using linearized approximations to the Zoeppritz equations.
Page 1: University of Alberta Regularizatio
Page 5 and 6: Contents 1 Introduction 1 1.1 Forwa
Page 7 and 8: 5 Three-term AVO Inversion 55 5.1 I
Page 9 and 10: List of Figures 1.1 A simple diagra
Page 11 and 12: 5.3 (a) P-wave reflectivity (RMSEA
Page 13 and 14: CHAPTER 1 Introduction The reflecti
Page 15 and 16: CHAPTER 1. INTRODUCTION 3 ! !!!!!!!
Page 17 and 18: CHAPTER 1. INTRODUCTION 5 1.4.1 Rel
Page 19 and 20: CHAPTER 1. INTRODUCTION 7 three-ter
Page 21 and 22: 2.1 Introduction CHAPTER 2 AVO Mode
Page 23 and 24: CHAPTER 2. AVO MODELING 11 (S-wave
Page 25 and 26: CHAPTER 2. AVO MODELING 13 At this
Page 27 and 28: CHAPTER 2. AVO MODELING 15 The resu
Page 29 and 30: CHAPTER 2. AVO MODELING 17 2.3.3 Sh
Page 31 and 32: CHAPTER 2. AVO MODELING 19 Assuming
Page 33 and 34: CHAPTER 2. AVO MODELING 21 Reflecti
Page 35 and 36: CHAPTER 2. AVO MODELING 23 ! !"# %$
Page 37 and 38: CHAPTER 2. AVO MODELING 25 can be r
Page 39 and 40: CHAPTER 3. BAYESIAN INVERSION APPRO
Page 51 and 52: 4.1 Introduction CHAPTER 4 Two-term
Page 53 and 54:
CHAPTER 4. TWO-TERM AVO INVERSION 4
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
5.1 Introduction CHAPTER 5 Three-te
Page 69 and 70:
CHAPTER 5. THREE-TERM AVO INVERSION
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
CHAPTER 6. CONCLUSIONS 77 two terms
Page 91 and 92:
Bibliography Aki, K. and P. G. Rich
Page 93 and 94:
BIBLIOGRAPHY 81 Sacchi, M.D. and T.
Page 95 and 96:
APPENDIX A Multivariate t distribut
Page 97 and 98:
APPENDIX A. MULTIVARIATE T DISTRIBU
Page 99 and 100:
APPENDIX B EM Algorithm B.1 EM-Algo
Page 101:
APPENDIX C Calculation of root mean
show all

Regularization of the AVO inverse problem by means of a ...

Create successful ePaper yourself

Delete template?

Save as template?