S54B-01
Velocity Based Modulus Calculations
A new set of equations are derived for the modulus of elasticity E and the bulk modulus K which are dependent only upon the seismic wave propagation velocities Vp, Vs and the density ρ. The three elastic moduli, E (Young's modulus), the shear modulus μ (Lamé's second parameter) and the bulk modulus K are found to be simple functions of the density and wave propagation velocities within the material. The shear and elastic moduli are found to equal the density of the material multiplied by the square of their respective wave propagation-velocities. The bulk modulus may be calculated from the elastic modulus using Poisson's ratio. These equations and resultant values are consistent with published literature and values in both magnitude and dimension (N/m2) and are applicable to the solid, liquid and gaseous phases. A 3D modulus of elasticity model for the Parkfield segment of the San Andreas Fault is presented using data from the wavespeed model of Thurber et al. [2006]. A sharp modulus gradient is observed across the fault at seismic depths, confirming that "variation in material properties play a key role in fault segmentation and deformation style" [Eberhart-Phillips et al., 1993] [EPM93]. The three elastic moduli E, μ and K may now be calculated directly from seismic pressure and shear wave propagation velocities. These velocities may be determined using conventional seismic reflection, refraction or transmission data and techniques. These velocities may be used in turn to estimate the density. This allows velocity based modulus calculations to be used as a tool for geophysical analysis, modeling, engineering and prospecting.
S54B-02
PP/PS Wavefield separation by independent component analysis
In blind signal separation one seeks to retrieve the original source signals that are observed as a linear mixture on an array of sensors. No a priori information is available about waveforms or polarisations of the desired source signals -- hence the term blind. Blind signal separation can be achieved using independent component analysis (ICA) which is a rapidly emerging technology in the field of advanced signal processing. It separates a set of observed signals into the statistically most independent components by appealing to higher-order statistics. ICA retrieves the original source signals blindly if they are statistically independent without the need of further a priori information. There are many promising applications of ICA in geophysical signal analysis. ICA can be used to separate P- and S-waves in 3-component seismic reflection data without knowledge of P- and S-wave near-surface velocities or density. Multi-trace recordings are first transformed to the tau-p domain (i.e., intercept time versus horizontal slowness). It is next assumed that a thin laterally homogeneous layer exists at the surface such that all incoming P-waves with the same slowness have the same incidence angle. The same is then true for all incoming S-wave energy as well. Wavefield separation is then achieved by exploiting statistical differences between P- and S-waves only. An inverse tau-p transform yields finally the desired PP and PS wavefields in the time-offset domain. The usual problems of amplitude indeterminacy and signal identification that occur in ICA are overcome by examining the inner products of the independent comp onents with the original observations to ensure that the retrieved P- and S-waves have the appropriate signs and energies. Mode identification is realised by comparing current polarisations with forward predicted ones for each mode while maximising the coherence with previously determined modes. The ICA wavefield separation technique is exact in a laterally inhomogeneous an isotropic Earth with a homogeneous anisotropic near-surface layer if only upgoing waves are present.
S54B-03
Statistical Analysis of Common Image Point Gathers at and near the Core-Mantle Boundary
Remote sensing of the core-mantle boundary region is at the cutting edge of seismological research. We developed statistical method to produce the best estimates of the variations in Earth deep interior from the common image point gathers (Wang et al 2006, van der Hilst et al 2007) using a data-driven approach, in which the image gathers are modeled nonparametrically using mixed effects models. In this framework, the random noise in the signal is allowed to have white and coherent components, and the latter are estimated from the data through generalized cross validation. This methodology, a flexible type of Tikhonov regularization, can be used with different types of correlated noise and with the typically sparsely and unevenly sampled image gathers owing to the geographic distribution of sources and receivers. With synthetic data we show that conventional images deteriorate substantially, in some cases to the point at which weak reflectors can no longer be detected, due to effects of uneven sampling, wave phenomena that are not accounted for in the underlying single scattering approximation, or errors in the assumed background wave speed model. We demonstrate that even in these circumstances, our method can yield adequate estimates of the true model. Our method produces robust images of the core-mantle boundary beneath Central America and suggests the presence of several significant structures in the D double prime region, in particular between 100 and 200 and between 270 and 320 km above the CMB proper.
S54B-04
Hunting the Strike of a Dipping Interface With Receiver Function Moveout and Polarity Variations
P-to-S converted waves that originate at interfaces within Earth's crust and mantle (Ps phases) suffer directional variations in amplitude and polarity that depend on the dip of the interface and the presence of elastic anisotropy in the surrounding rock. The moveout of the Ps phase revealed by receiver-function analysis of data covering a range of backazimuths should constrain the dip and strike of a dipping interface, but Ps amplitude and polarity variations can cloud the determination. We report a simple technique for utilizing directional variation in Ps phase attributes that helps constrain its moveout, offering a way to distinguish a dipping-interface effect from an anisotropic one, e.g. in a subduction-zone environment. The radial and transverse components of Ps are both affected, in a similar way, by converting interface dip and anisotropic axis of symmetry tilt. In both cases a phase-shifted two-lobed back-azimuthal pattern of Ps amplitude on the radial and transverse RFs is expected. (Horizontal-axis anisotropy predicts a four-lobed pattern.) The relationship between radial and transverse RFs can be exploited in stacking to enhance signals, with one phase-relationship "correct" for anisotropy and interface dip, and the opposite phase-relationship "unmodelled." The low amplitude of the RF stack for the "unmodelled" phase is an indicator of the success in finding "correct" stacking rules. We employ a parameter search over interface strike and moveout values to find a minimum in the "unmodelled" RF stack. In cases tested, this minimum correlates well with the known strike and dip of a subduction-zone interface beneath a station of interest, even where the anisotropic symmetry axis is known to deviate from the slab dip e.g., station COR in Cascadia and station CUC in Calabria. Relating the optimal Ps moveout to slab dip depends on the assumed velocity model, though we observe that the optimal stacking moveout increases with slab dip, as expected.
S54B-05
Robust Canonical Coherence for Quasi-Cyclostationary Processes: Geomagnetism and Seismicity in Peru
Preliminary results suggesting a connection between long-period, geomagnetic fluctuations and long-period, seismic fluctuations are presented. Data from the seismic detector, NNA, situated in ~Naña, Peru, is compared to geomagnetic data from HUA, located in Huancayo, Peru. The high-pass filtered data from the two stations exhibits quasi-cyclostationary pulsation with daily periodicity, and suggests correspondence. The pulsation contains power predominantly between 2000 μ Hz and 8000 μ Hz, with the geomagnetic pulses leading by approximately 4 to 5 hours. A many data section, multitaper, robust canonical coherence analysis of the two, three component data sets is performed. The method, involving an adaptation, suitable for quasi-cyclostationary processes, of the technique presented in "Robust estimation of power spectra", (by Kleiner, Martin and Thomson, Journal of the Royal Statistical Society, Series B Methodological, 1979) is described. Simulations are presented exploring the applicability of the method. Canonical coherence is detected, predominantly between the geomagnetic field and the vertical component of seismic velocity, in the band of frequencies between 1500 μ Hz and 2500 μ Hz. Subsequent group delay estimates between the geomagnetic components and seismic velocity vertical at frequencies corresponding to large canonical coherence are computed. The estimated group delays are 8 min between geomagnetic east and seismic velocity vertical, 16 min between geomagnetic north and seismic velocity vertical and 11 min between geomagnetic vertical and seismic velocity vertical. Possible coupling mechanisms are discussed.
S54B-06
Blind source deconvolution for deep Earth seismology
We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.
S54B-07
Slowness-Azimuth Corrections for IMS Primary Arrays in China
As the primary stations of CTBT seismic network, Hailar (ps12) and Lanzhou (ps13) arrays had been established for 6 years till the end of this year. In this study, the slowness-azimuth correction was used for the two arrays to improve the location accuracy. The slowness-azimuth correction is to compare the azimuth and slowness obtained from the waveform processing using array techniques to the theoretical values based on the event locations and the velocity model. We used earthquakes recorded by the two arrays from 2003 to 2006 and the event locations from NEIC earthquake catalogue and iasp91 velocity model were chosen as reference events and velocity model here. The two arrays were corrected by the using of teleseismic P phases and the major regional and local phases based on the NEIC earthquake catalogue list. Hailar array shows small corrections and random in orientation while Lanzhou array shows bigger corrections and systematic bias was found that the array shows positive residuals for event paths from South-East and negative residuals for event paths from North- West that may be attributed to local structure. After correction, the two arrays clearly improved the single array location abilities and the standard deviations of azimuth and slowness residuals drop from 10.2 to 5.8 deg and from 1.3 to 0.6 s/deg respectively for Hailar array. For Lanzhou array, these values drop from 26.4 to 11.5 deg and from 3.1 to 1.2 s/deg respectively. The variation ranges of azimuth and slowness residuals is from 105.9 to 53.5 deg and from 12.4 to 4.4 s/deg for Hailar array, while for Lanzhou array, these numbers drop from 167.9 to 64.0 deg and from 14.0 to 6.1 s/deg respectively after correction.