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In this thesis, we investigate and develop the optimal data processing procedures necessary to recover Green’s functions for body waves propagating among a network of borehole seismometers near Parkfield, CA. Applying these procedures, we detect P-waves propagating among these stations, which allows us to produce a first-order crustal velocity model for the San Andreas Fault in the Parkfield region. We also discuss under what conditions body wave phenomena such as reflections and mode conversions (P to S) may be observed, as further observing these would provide a dramatic improvement in our ability to characterize seismic velocity structures. Finally, we discuss the potential of seismic interferometry to produce time-lapse body wave characterizations of the San Andreas Fault, in which properties of the fault can be seen to change in time.

In Michelson interferometry, many algorithms are used to detect the number of active laser sources at any given time. Conventional FFT-based non-parametric methods are widely used for this purpose. However, non-parametric methods are not the only possible option to distinguish the peaks in a spectrum, as these methods are not the most suitable methods for short data records and for closely spaced wavelengths. This thesis aims to provide solutions to these problems. It puts forward the use of parametric methods such as autoregressive methods and harmonic methods, and proposes two new algorithms to detect the closely spaced peaks for different scenarios of optical signals in wavemeters. Various parametric algorithms are studied, and their performances are compared with non-parametric algorithms for different criteria, e.g. absolute levels, frequency resolution, and accuracy of peak positions. Simulations are performed on synthetic signals produced from specifications provided by our sponsor, i.e., a wavemeter manufacturing company.

From the main sequence onwards, stars of intermediate masses (1-8 Solar masses) eject a large portion of their mass with rates as high as 0.0001 Solar masses per year during their transition through the Asymptotical Giant Branch (AGB) stage. The outflows are shaped by the same mechanisms that shape the ejecta, which in turn appear to depart from spherical symmetry as early as the AGB stage. The ejecta are then evolving into asymmetrical structures. Stars like that are giant factories of dust, responsible for the enrichment of their surrounding Galactic medium in metals heavier than helium. Depending on their abundances during the AGB stage, the stars are either oxygen-rich or carbon-rich, and as such, the dust produced in their atmospheres is either O-rich or C-rich. The chemical composition of the ejecta, indicates the stellar chemistry at the moment of ejection. The disruption of the spherical symmetry of the mass loss can be caused by fast rotation, stellar magnetic fields or binarity, the latter being the most efficient and favourable mechanism. Such mechanisms can lead to the creation of circumstellar, equatorial, dusty structures, like discs, torii or spirals. Due to their small relative sizes, compared to their surrounding nebulae, they can be studied at best with the use of infrared interferometric techniques. We report the discovery of three such structures in sources at three different evolutionary stages, respectively, with the use of single- and multi-aperture interferometry. In the C-rich AGB star V Hya we imaged via aperture masking in the near-infrared, a complex and possibly orbiting structure, which is embedded within the star's molecular torus. Our MIDI observations in the mid-infrared have revealed, a silicate disc within the symbiotic nebula M2-9 that is currently being shaped by the central binary system within its core, and a C-rich disc-like structure in the born-again star Sakurai's Object, that is also aligned to an asymmetry found in its surrounding planetary nebula. Finally, we compare the properties of the structures found here with those found in the literature in order to establish a relation between late stellar evolution and the existence of dusty structures.

Dans le cadre de la préparation du Square Kilometre Array (SKA), le plus large radio interféromètre au monde, de nouveaux défis de traitement d'images sont à relever. En effet, les données fournies par SKA auront un débit énorme, nécessitant ainsi un traitement en temps réel. En outre, grâce à sa résolution et sa sensibilité sans précédent, les observations seront dotées d'une très forte dynamique sur des champs de vue très grands. De nouvelles méthodes de traitement d'images robustes, efficaces et automatisées sont alors exigées. L'objectif de la thèse consiste à développer une nouvelle méthode permettant la restauration du modèle de l'image du ciel à partir des observations. La méthode est conçue pour l'estimation des images de très forte dynamique avec une attention particulière à restaurer les émissions étendues et faibles en intensité, souvent noyées dans les lobes secondaires de la PSF et le bruit. L'approche proposée est basée sur les représentations parcimonieuses, nommée MORESANE. L'image du ciel est modélisée comme étant la superposition de sources, qui constitueront les atomes d'un dictionnaire de synthèse inconnu, ce dernier sera estimé par des a priori d'analyses. Les résultats obtenus sur des simulations réalistes montrent que MORESANE est plus performant que les outils standards et très compétitifs avec les méthodes récemment proposées dans la littérature. MORESANE est appliqué sur des simulations d'observations d'amas de galaxies avec SKA1 afin d'investiguer la détectabilité du milieu non thermique intra-amas. Nos résultats indiquent que cette émission, avec SKA, sera étudiée jusqu'à l'époque de la formation des amas de galaxies massifs. / Within the framework of the preparation for the Square Kilometre Array (SKA), that is the world largest radio telescope, new imaging challenges has to be conquered. The data acquired by SKA will have to be processed on real time because of their huge rate. In addition, thanks to its unprecedented resolution and sensitivity, SKA images will have very high dynamic range over wide fields of view. Hence, there is an urgent need for the design of new imaging techniques that are robust and efficient and fully automated. The goal of this thesis is to develop a new technique aiming to reconstruct a model image of the radio sky from the radio observations. The method have been designed to estimate images with high dynamic range with a particular attention to recover faint extended emission usually completely buried in the PSF sidelobes of the brighter sources and the noise. We propose a new approach, based on sparse representations, called MORESANE. The radio sky is assumed to be a summation of sources, considered as atoms of an unknown synthesis dictionary. These atoms are learned using analysis priors from the observed image. Results obtained on realistic simulations show that MORESANE is very promising in the restoration of radio images; it is outperforming the standard tools and very competitive with the newly proposed methods in the literature. MORESANE is also applied on simulations of observations using the SKA1 with the aim to investigate the detectability of the intracluster non thermal component. Our results indicate that these diffuse sources, characterized by very low surface brightness will be investigated up to the epoch of massive cluster formation with the SKA.

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This thesis describes new interferometric imaging methods for migration and waveform inversion. The key idea is to use reflection events from a known reference reflector to ”naturally redatum” the receivers and sources to the reference reflector. Here, ”natural redatuming” is a data-driven process where the redatuming Green’s functions are obtained from the data. Interferometric imaging eliminates the statics associated with the noisy overburden above the reference reflector. To mitigate the defocussing caused by overburden errors I first propose the use of interferometric least-squares migration (ILSM) to estimate the migration image. Here, a known reflector is used as the reference interface for ILSM, and the data are naturally redatumed to this reference interface before imaging. Numerical results on synthetic and field data show that ILSM can significantly reduce the defocussing artifacts in the migration image. Next, I develop a waveform tomography approach for inverting the velocity model by mitigating the velocity errors in the overburden. Unresolved velocity errors in the overburden velocity model can cause conventional full-waveform inversion to get stuck in a local minimum. To resolve this problem, I present interferometric full-waveform inversion (IFWI), where conventional waveform tomography is reformulated so a velocity model is found that minimizes the objective function with an interferometric crosscorrelogram misfit. Numerical examples show that IFWI, compared to FWI, computes a significantly more accurate velocity model in the presence of a nearsurface with unknown velocity anomalies. I use IFWI and ILSM for 4D imaging where seismic data are recorded at different times over the same reservoir. To eliminate the time-varying effects of the near surface both data sets are virtually redatumed to a common reference interface before migration. This largely eliminates the overburden-induced statics errors in both data sets. Results with synthetic and field data show that ILSM and IFWI can suppress the artifacts caused by non-repeatability in time-lapse surveys. This can lead to a much more accurate characterization of the movement of fluids over time. In turn, this information can be used to optimize the extraction of resources in enhanced oil recovery (EOR) operations.

Sonic logs are essential tools for reliably identifying interval velocities which, in turn, are used in many seismic processes. One problem that arises, while logging, is irregularities due to washout zones along the borehole surfaces that scatters the transmitted energy and hence weakens the signal recorded at the receivers. To alleviate this problem, I have extended the theory of super-virtual refraction interferometry to enhance the signal-to-noise ratio (SNR) sonic waveforms. Tests on synthetic and real data show noticeable signal-to-noise ratio (SNR) enhancements of refracted P-wave arrivals in the sonic waveforms. The theory of super-virtual interferometric stacking is composed of two redatuming steps followed by a stacking procedure. The first redatuming procedure is of correlation type, where traces are correlated together to get virtual traces with the sources datumed to the refractor. The second datuming step is of convolution type, where traces are convolved together to dedatum the sources back to their original positions. The stacking procedure following each step enhances the signal to noise ratio of the refracted P-wave first arrivals. Datuming with correlation and convolution of traces introduces severe artifacts denoted as correlation artifacts in super-virtual data. To overcome this problem, I replace the datuming with correlation step by datuming with deconvolution. Although the former datuming method is more robust, the latter one reduces the artifacts significantly. Moreover, deconvolution can be a noise amplifier which is why a regularization term is utilized, rendering the datuming with deconvolution more stable. Tests of datuming with deconvolution instead of correlation with synthetic and real data examples show significant reduction of these artifacts. This is especially true when compared with the conventional way of applying the super-virtual refraction interferometry method.

Seismic exploration utilizes controlled sources, which emit seismic waves that propagate through the earth subsurface and get reflected off subsurface interfaces and scatterers. The reflected and scattered waves are recorded by recording stations installed along the earth surface or down boreholes. Seismic imaging is a powerful tool to map these reflected and scattered energy back to their subsurface scattering or reflection points. Seismic imaging is conventionally based on the single-scattering assumption, where only energy that bounces once off a subsurface scatterer and recorded by a receiver is projected back to its subsurface position. The internally multiply scattered seismic energy is considered as unwanted noise and is usually suppressed or removed from the recorded data. Conventional seismic imaging techniques yield subsurface images that suffer from low spatial resolution, migration artifacts, and acquisition fingerprint due to the limited acquisition aperture, number of sources and receivers, and bandwidth of the source wavelet. Hydrocarbon traps are becoming more challenging and considerable reserves are trapped in stratigraphic and pinch-out traps, which require highly resolved seismic images to delineate them. This thesis focuses on developing and implementing new advanced cost-effective seismic imaging techniques aiming at enhancing the resolution of the migrated images by exploiting the sparseness of the subsurface reflectivity distribution and utilizing the multiples that are usually neglected when imaging seismic data. I first formulate the seismic imaging problem as a Basis pursuit denoise problem, which I solve using an L1-minimization algorithm to obtain the sparsest migrated image corresponding to the recorded data. Imaging multiples may illuminate subsurface zones, which are not easily illuminated by conventional seismic imaging using primary reflections only. I then develop an L2-norm (i.e. least-squares) inversion technique to image internally multiply scattered seismic waves to obtain highly resolved images delineating vertical faults that are otherwise not easily imaged by primaries. Seismic interferometry is conventionally based on the cross-correlation and convolution of seismic traces to transform seismic data from one acquisition geometry to another. The conventional interferometric transformation yields virtual data that suffers from low temporal resolution, wavelet distortion, and correlation/convolution artifacts. I therefore incorporate a least-squares datuming technique to interferometrically transform vertical-seismic-profile surface-related multiples to surface-seismic-profile primaries. This yields redatumed data with high temporal resolution and less artifacts, which are subsequently imaged to obtain highly resolved subsurface images. Tests on synthetic examples demonstrate the efficiency of the proposed techniques, yielding highly resolved migrated sections compared with images obtained by imaging conventionally redatumed data. I further advance the recently developed cost-effective Generalized Interferometric Multiple Imaging procedure, which aims to not only image first but also higher-order multiples as well. I formulate this procedure as a linearized inversion framework and solve it as a least-squares problem. Tests of the least-squares Generalized Interferometric Multiple imaging framework on synthetic datasets and demonstrate that it could provide highly resolved migrated images and delineate vertical fault planes compared with the standard procedure. The results support the assertion that this linearized inversion framework can illuminate subsurface zones that are mainly illuminated by internally scattered energy.

California Polytechnic State University, San Luis Obispo is currently working towards developing a Computational Fluid Dynamics (CFD) database for future code validation efforts. Cal Poly will complete a wind tunnel test on the Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA) in the National Full-Scale Aerodynamics Complex (NFAC) 40 foot by 80 foot wind tunnel at NASA Ames Research Center in the summer of 2011. The development of two measurement techniques is discussed in this work, both with the objective of making measurements on AMELIA for CFD validation. First, the work on the application of the Fringe-Imaging Skin Friction (FISF) technique to AMELIA is discussed. The FISF technique measures the skin friction magnitude and direction by applying oil droplets on a surface, exposing them to flow, measuring their thickness, and correlating their thickness to the local skin friction. The technique has the unique ability to obtain global skin friction measurements. A two foot, nickel plated, blended wing section test article has been manufactured specifically for FISF. The model is illuminated with mercury vapor lamps and imaged with a Canon 50D with a 546 nm bandpass filter. Various tests are applied to the wing in order to further characterize uncertainties related with the FISF technique. Human repeatability has uncertainties of ±2.3% of fringe spacing and ±2.0° in skin friction vector direction, while image post processing yields ±25% variation in skin friction coefficient. A method for measuring photogrammetry uncertainty is developed. The effect of filter variation and test repeatability was found to be negligible. A validation against a Preston tube was found to have 1.8% accuracy. Second, the validation of a micro flow measurement device is investigated. Anemometers have always had limited capability in making near wall measurements, driving the design of new devices capable of measurements with increased wall proximity. Utilizing a thermocouple boundary layer rake, wall measurements within 0.0025 inches of the surface have been made. A Cross Correlation Rake (CCR) has the advantage of not requiring calibration but obtaining the same proximity and resolution as the thermocouple boundary layer rake. The flow device utilizes time of flight measurements computed via cross correlation to calculate wall velocity profiles. The CCR was designed to be applied to AMELIA to measure flow velocities above a flap in a transonic flow regime. The validation of the CCR was unsuccessful. Due to the fragile construction of the CCR, only one data point at 0.10589 inches from the surface was available for validation. The subsonic wind tunnel’s variable frequency drive generated noise which could not be filtered or shielded, requiring the use of a flow bench for validation testing. Since velocity measurements could not be made in the flow bench, a comparison of a fast and slow velocity was made. The CCR was not able to detect the difference between the two flow velocities. Currently, the CCR cannot be applied on AMELIA due to the unsuccessfully validation of the device.