Abstract
When using waveform tomography to perform high-resolution imaging of a medium, it is vital to calculate the sensitivity in order to describe how well a model fits a given set of data and how the sensitivity changes with the spatial distribution of the heterogeneities. The traditional principle behind calculating the sensitivity—for detecting small changes—suffers from an inherent limitation in case other structures, not of interest, are present along the wave propagation path. We propose a novel principle that leads to enhanced localization of the sensitivity of the waveform tomography, without having to know the intermediate structures. This new principle emerges from a boundary integral representation which utilizes wave interferences observed at multiple points. When tested on geophysical acoustic wave data, this new principle leads to much better sensitivity localization and detection of small changes in seismic velocities, which were otherwise impossible. Overcoming the insensitivity to a target area, it offers new possibilities for imaging and monitoring small changes in properties, which is critical in a wide range of disciplines and scales.
Highlights
When using waveform tomography to perform high-resolution imaging of a medium, it is vital to calculate the sensitivity in order to describe how well a model fits a given set of data and how the sensitivity changes with the spatial distribution of the heterogeneities
The sensitivity of waveform tomography is defined by the change in the goodness-of-fit of the simulated waveforms with respect to the change in the assumed heterogeneity, which indicates spatial locations where the assumed heterogeneity needs to be updated during a nonlinear o ptimization[3,7,8]
As the conventional physical principle addresses material heterogeneities that are present along the wave propagation paths starting from a source and ending at an observation point, small material perturbation between the observation points does not appear in the sensitivity, unless the heterogeneities around the source points and those present along the source-observation paths are sufficiently known
Summary
When using waveform tomography to perform high-resolution imaging of a medium, it is vital to calculate the sensitivity in order to describe how well a model fits a given set of data and how the sensitivity changes with the spatial distribution of the heterogeneities. Waveform tomography extracts information of the heterogeneity by fitting the observed waveforms with the simulated waveforms based on a physical principle (i.e., forward modeling), assuming that the source and the receiver locations are known. In this approach, the sensitivity (often represented by the gradient of the m isfit7) is of fundamental importance to determine the resolution capability of this approach. When monitoring is performed using downhole receivers and surface sources, in addition to time-lapse changes in the target area, the data contain the effect of time-lapse changes occurring around the source point, e.g., due to environmental effects (like rainfall), which can jeopardize the entire time-lapse monitoring e fforts[25]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
