Stochastic tomography and Gaussian beam depth migration

Ocean-bottom seismometers (OBS) allow wider angle recording and therefore, they have the potential to significantly enhance imaging of deep subsurface structures. Currently, conventional OBS data analysis still uses first arrival traveltime tomography and prestack Kirchhoff depth migration method. However, using first arrival traveltimes to build a velocity model has its limitations. In the Taiwan region, subduction and collision cause very complex subsurface structures and generate extensive basalt-like anomalies. Since the velocity beneath basalt-like anomalies is lower than that of high velocity anomalies, no first-arrival refractions for the target areas occur. Thus, conventional traveltime tomography is not accurate and amplitude constrained traveltime tomography can be dangerous. Here, a new first-arrival stochastic tomography method for automatic background velocity estimation is proposed. Our method uses the local beam semblance of each common-shot or common-receiver gathers instead of first-arrival picking. Both the ray parameter and traveltime information are utilized. The use of Very Fast Simulated Annealing (VFSA) method also allows for easier implementation of the uncertainty analysis. Synthetic and real data benchmark tests demonstrate that this new method is robust, efficient, and accurate. In addition, migrated images of low-fold data or data with limited observation geometry like OBS are often corrupted by migration aliasing. Incorporation of prestack instantaneous-slowness information into the imaging condition can significantly reduce migration artifacts and noise and improve the image quality in areas of poor illumination. Here I combine slowness information with Gaussian beam depth migration and implement a new slowness driven Gaussian beam prestack depth migration. The prestack instantaneous slowness information, denoted by ray parameter gathers p(x,t), is extracted from the original OBS or shot gathers using local slant stacking and subsequent localsemblance analysis. In migration, we propagate both the seismic energy and the principal instantaneous slowness information backward. At a specific image location, the beam summation is localized in the resolution-dependent Fresnel zone where the instantaneousslowness-information-related weights are used to control the beams. The effectiveness of the new method is illustrated using two synthetic data examples: a simple model and a more realistic complicated sub-basalt model. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/18012
Date25 September 2012
CreatorsHu, Chaoshun, 1976-
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
Formatelectronic
RightsCopyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.

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