Retrieving the Reflection events from passive signals

<p>To create virtual shot gather from passive signals it is essential to cross-correlate all the signals with the reference trace. Since surface sources dominate the origin of seismic noise, the correlated sections are highly dominated by surface waves. If the target is surface wave inversion general cross-correlation will suit the target. But if the extraction of body waves from those signals is the main objective, coherent ground roll events mask the body waves making it difficult to extract them. To tackle this issue a frequency-spatial nonCoherent filter (FX-NCF) plus a post-correlation processing module are introduced. FX-NCF is a prediction filter and the filter operator is a function of frequency, station interval and the slope of the interested event. In the frequency domain, the filter is looking for the prediction of n-th trace coherence spectrum from the (n-1)-th signal’s coherence spectrum by minimizing the objective function. Hybrid norms used to minimize the error. The coherence spectrum of each trace is the coherency between the reference signal and the desired trace. Applying the FX-NCF on 2D real recorded passive signals shows its superiority over general cross-correlation, deconvolution interferometry, cross-coherence and multi-taper-method-coherence-estimation methods in highlighting surface and body waves also improving the signal-to-noise (S/N) ratio. To show the necessity of post correlation processing (before applying on real recorded signals) to highlight reflection events, hyperbolic Radon transform (HRT) as a suitable post-correlation module applied on correlated section due to applied FX-NCF on simulated passive signals from a simple 2D synthetic model. The result encouraged us to apply the same hybrid modules (FX-NCF plus HRT) on real recorded passive signals to reconstruct wanted reflection events.</p>

Turbulence coherence and its impact on wind-farm power fluctuations

Using a physics-based approach, we infer the impact of the coherence of atmospheric turbulence on the power fluctuations of wind farms. Application of the random-sweeping hypothesis reveals correlations characterized by advection and turbulent diffusion of coherent motions. Those contribute to local peaks and troughs in the power spectrum of the combined units at frequencies corresponding to the advection time between turbines, which diminish in magnitude at high frequencies. Experimental inspection supports the results from the random-sweeping hypothesis in predicting spectral characteristics, although the magnitude of the coherence spectrum appears to be over-predicted. This deviation is attributed to the presence of turbine wakes, and appears to be a function of the turbulence approaching the first turbine in a pair.

Distinct α- and β-band rhythms over rat somatosensory cortex with similar properties as in humans

We demonstrate distinct α- (7–14 Hz) and β-band (15–30 Hz) rhythms in rat somatosensory cortex in vivo using epidural electrocorticography recordings. Moreover, we show in rats that a genuine β-rhythm coexists alongside β-activity that reflects the second harmonic of the arch-shaped somatosensory α-rhythm. This demonstration of a genuine somatosensory β-rhythm depends on a novel quantification of neuronal oscillations that is based on their rhythmic nature: lagged coherence. Using lagged coherence, we provide two lines of evidence that this somatosensory β-rhythm is distinct from the second harmonic of the arch-shaped α-rhythm. The first is based on the rhythms' spatial properties: the α- and β-rhythms are demonstrated to have significantly different topographies. The second is based on the rhythms' temporal properties: the lagged phase-phase coupling between the α- and β-rhythms is demonstrated to be significantly less than would be expected if both reflected a single underlying nonsinusoidal rhythm. Finally, we demonstrate that 1) the lagged coherence spectrum is consistent between signals from rat and human somatosensory cortex; and 2) a tactile stimulus has the same effect on the somatosensory α- and β-rhythms in both rats and humans, namely suppressing them. Thus we not only provide evidence for the existence of genuine α- and β-rhythms in rat somatosensory cortex, but also for their homology to the primate sensorimotor α- and β-rhythms.