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sep:research:theses:sep146 [2012/01/05 14:49]
gayeni created
sep:research:theses:sep146 [2015/05/27 02:06] (current)
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//by [[http://sepwww.stanford.edu/sep/gayeni|Gboyega Ayeni]]// //by [[http://sepwww.stanford.edu/sep/gayeni|Gboyega Ayeni]]//
-Thesis ([[http://sepwww.stanford.edu/data/media/public/docs/sep146/sep146.pdf|PDF]])+Full thesis ([[http://sepwww.stanford.edu/data/media/public/docs/sep146/sep146.pdf|PDF]])
**Table of contents** **Table of contents**
-  * Chapter 1: Introduction +  * Chapter 1: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap1.pdf|Introduction]] 
-  * Chapter 2: Time-lapse cross-equalization +  * Chapter 2: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap2.pdf|Time-lapse cross-equalization]] 
-  * Chapter 3: Joint least-squares migration/inversion: theory +  * Chapter 3: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap3.pdf|Joint least-squares migration/inversion: theory]] 
-  * Chapter 4: Synthetic examples +  * Chapter 4: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap4.pdf|Synthetic examples]] 
-  * Chapter 5: 2D field data application  +  * Chapter 5: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap5.pdf|2D field data application]]  
-  * Chapter 6: 3D field data application  +  * Chapter 6: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap6.pdf|3D field data application]]  
-  * Chapter 7: Conclusions +  * Chapter 7: [[http://sepwww.stanford.edu/data/media/public/docs/sep146/chap7.pdf|Conclusions]] 
-  * Appendix A:  +  * [[http://sepwww.stanford.edu/data/media/public/docs/sep146/sep146.pdf|Appendices]]
-  * Appendix B: +
**Abstract** **Abstract**
 +This dissertation presents methods that overcome some limitations in the application
 +of time-lapse seismic imaging to subsurface reservoir monitoring. These methods
 +attenuate artifacts and distortions in time-lapse seismic images that are caused by
 +differences in survey acquisition geometries, presence of obstructions, complex overburden
 +and man-made noise. Unless these artifacts are attenuated, it is impossible
 +to make reliable deductions about changes in subsurface reservoir properties from
 +time-lapse seismic images.
 +Improvements to two conventional post-imaging seismic cross-equalization methods
 +are considered. Multidimensional warping of baseline and monitor images is implemented
 +as sequential one-dimensional cross-correlations and interpolations. This
 +method avoids the cost of full three-dimensional warping, and it avoids errors caused
 +by considering only vertical apparent displacements between images. After warping,
 +matched filters are derived using optimal parameters derived using an Evolutionary
 +Programming algorithm. Applications to four North Sea data sets show that a
 +combination of these two methods provides an efficient and robust cross-equalization
 +scheme. Importantly, the warping method is a key preprocessing tool for linearized
 +joint inversion.
 +Linearized joint inversion of time-lapse data sets is an extension of least-squares
 +migration/inversion of seismic data sets. Linearized inversion improves both structural
 +and amplitude information in seismic images. Joint inversion allows incorporation
 +spatial and temporal regularizations/constraints, which stabilize the inversion
 +and ensure that results are geologically plausible. Implementations of regularized
 +joint inversion in both the data-domain and image-domain are considered. Joint
 +data-domain inversion minimizes a global least-squares objective function, whereas
 +joint image-domain inversion utilizes combinations of target-oriented approximations
 +of the Hessian of the least-squares objective function. Applications to synthetic data
 +sets show that, compared to migration or separate inversion, linearized joint inversion
 +provides time-lapse seismic images that are less sensitive to geometry differences
 +between surveys and to the overburden complexity. An important advantage of an
 +image-domain inversion is that it can be solved efficiently for a small target around
 +the reservoir.
 +Joint image-domain inversion requires careful preprocessing to ensure that the
 +data contain only primary reflections, and that the migrated images from different
 +vintages are aligned. The importances of various preprocessing steps are demonstrated
 +using two-dimensional time-lapse data subsets from the Norne field. Applications
 +of regularized image-domain joint inversion to the Valhall Life-of-Field Seismic
 +(LoFS) data sets show that it provides improved time-lapse images compared to
 +migration. These applications show that regularized joint image-domain inversion
 +attenuates obstruction artifacts in time-lapse seismic images and that it can be used
 +to image several data sets simultaneously. Furthermore, because it is computationally
 +efficient, joint image-domain inversion can be repeated quickly using various a priori
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