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Geophysical Processing with dense arrays in passive and active seismic configurations

Abstract : In geophysics, spatially dense arrays enhance the spatial and frequential characterization of the various waves propagating in the medium. Of course, surface array is subject to strong surface waves. Surface waves highly impact the processing of geophysical data acquired at ground level. They can be considered as noise and subject to suppression as they mask sub-surface information.However, they can be useful for near-surface imaging if they are well retrieved. In any case, their characterization is crucial in active and passive exploration geophysics. In passive microseismic monitoring, ambient surface noise consists of surface waves. The main goal of passive monitoring is to minimize the impact of surface waves on the actual microseismic data. The strong ambient surface noise lowers the sensitivity and the efficiency ofdetection and location methods. Moreover, current location and detection methods usually require strong a priori information (e.g., a velocity model or a template).Active sources generate strong surface waves. In active seismic, current processing strategies often consist in manually picking surface wave arrivals in order to use or remove them. This is often a complex, time consuming, and an ambiguous task. However, it is needed for near- and sub-surface imaging. Surface waves can be particularly difficult to retrieve in sparse arrays. We propose to apply the techniques of interferometry and beamforming (Matched Field Processing in particular) in the context of dense arrays. High trace density opens new possibilities in geophysical processing in both passive and active surveys. We show that the ambient noise can be explored in the case of microseismic monitoring to extract important information about the medium properties. Moreover, we develop a denoising approach to remove the noise sources at the surface and detect the microseismic event. Furthermore, we propose an automatic detection and location method with a minimum a priori information to retrieve the distribution of heterogeneities in the reservoir, in the well vicinity.In active survey, we propose an interferometric, automatic approach to characterize the surface waves. We retrieve phase-sensitivity kernels of surface waves between any two points of the acquisition. These kernels are consequently used to obtain multi-mode dispersion curves. These dispersion curves make it possible to separate different modes of surface waves and provide near-surface information if inverted.The above presented methodologies benefit from spatially dense arrays.Dense arrays of sources or receivers enable alternative, innovative applications in geophysical processing.
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Submitted on : Monday, December 4, 2017 - 10:48:18 AM
Last modification on : Wednesday, October 14, 2020 - 4:16:27 AM

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Malgorzata Chmiel. Geophysical Processing with dense arrays in passive and active seismic configurations. Tectonics. Université Grenoble Alpes, 2017. English. ⟨NNT : 2017GREAU009⟩. ⟨tel-01654595⟩

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