D. Dagnino

Fine-scale thermohaline ocean structure retrieved with 2-D prestack full-waveform inversion of multichannel seismic data: Application to the Gulf of Cadiz (SW Iberia)

This work demonstrates the feasibility of 2D time-domain, adjoint-state acoustic full-waveform inversion (FWI) to retrieve high-resolution models of ocean physical parameters such as sound speed, temperature and salinity. The proposed method is first described and then applied to pre-stack multi-channel seismic (MCS) data acquired in the Gulf of Cadiz (SW Iberia) in 2007 in the framework of the Geophysical Oceanography project. The inversion strategy flow includes specifically-designed data pre-conditioning for acoustic noise reduction, followed by the inversion of sound speed in the shotgather domain. We show that the final sound speed model has a horizontal resolution of ∼ 70m, which is two orders of magnitude better than that of the initial model constructed with coincident eXpendable Bathy Thermograph (XBT) data, and close to the theoretical resolution of O(λ). Temperature (T) and salinity (S) are retrieved with the same lateral resolution as sound speed by combining the inverted sound speed model with the thermodynamic equation of seawater and a local, depth-dependent T-S relation derived from regional conductivity-temperature-depth (CTD) measurements of the National Oceanic and Atmospheric Administration (NOAA) database. The comparison of the inverted T and S models with XBT and CTD casts deployed simultaneously to the MCS acquisition shows that the thermohaline contrasts are resolved with an accuracy of 0.18oC for temperature and 0.08 PSU for salinity. The combination of oceanographic and MCS data into a common, pseudo-automatic inversion scheme allows to quantitatively resolve submeso-scale features that ought to be incorporated into larger-scale ocean models of oceans structure and circulation. This article is protected by copyright. All rights reserved.

Quantum simulation of conductivity plateaux and fractional quantum Hall effect using ultracold atoms

We analyze the role of impurities in the fractional quantum Hall effect using a highly controllable system of ultracold atoms. We investigate the mechanism responsible for the formation of plateaux in the resistivity/conductivity as a function of the applied magnetic field in the lowest Landau level regime. To this aim, we consider an impurity immersed in a small cloud of an ultracold quantum Bose gas subjected to an artificial magnetic field. We consider scenarios corresponding to experimentally realistic systems with gauge fields induced either by rotation or by appropriately designed laser fields. Systems of this kind are adequate to simulate quantum Hall effects in ultracold atom setups. We use exact diagonalization for few atoms and, to emulate transport equations, we analyze the time evolution of the system under a periodic perturbation. We provide a theoretical proposal to detect the up-to-now elusive presence of strongly correlated states related to fractional filling factors in the context of ultracold atoms. We analyze the conditions under which these strongly correlated states are associated with the presence of the resistivity/conductivity plateaux. Our main result is the presence of a plateau in a region, where the transfer between localized and non-localized particles takes place, as a necessary condition to maintain a constant value of the resistivity/conductivity as the magnetic field increases.

Waveform-Preserving Processing Flow of Multichannel Seismic Reflection Data for Adjoint-State Full-Waveform Inversion of Ocean Thermohaline Structure

This paper presents a specific data processing flow to be applied to marine multichannel seismic reflection data collected by a streamer in order to use them to perform prestack adjoint waveform inversion of ocean’s thermohaline properties. The overall goal is to increase the signal-to-noise ratio (SNR) of the weak reflections generated at the small impedance contrasts within the water layer while preserving the direct wave. The processing flow focuses on increasing the SNR of the shot gather records by forcing noise amplitudes to fall inside a range of physical plausible values for water layer reflections. This processing step is applied in two independent branches of the workflow; one dealing with the water layer reflections and the second with the direct wave, which are separated by applying a singular value decomposition. To test the performance of the processing flow, we combine actual noise field recordings with a synthetic seismic data set. We apply the proposed data processing flow to quantify differences between noise-free and processed record sections, and we then compare with the results obtained by applying a Butterworth filter (BF). For offsets smaller than 1500 m, the BF processing produces a signal with SNR < 0.1; the proposed workflow allows to retrieve the seismic signal with 0.1 < SNR < 2.4. For offsets larger than 1500 m, the BF processing allows obtaining the SNR up to 1.4, while the proposed workflow increases the SNR up to 5. We finally demonstrate that the processed data can be used to perform waveform inversion with an accuracy of ~0.02 m/s.

Comparison of Objective Functionals in Seismic Full Waveform Inversion

The FWI method is a powerful tool that allows one to obtain high-resolution information from the subsurface. However, the method is highly non-linear as in the convergence to the solution it might get trapped in local-minima. Among other techniques, it becomes crucial a suitable choice of the objective function. We have selected five objective functions to perform a comparative study under a common 2D-acoustic FWI scheme: the L2-nom, cross-correlation travel time (CCTT), non-integration-method (NIM), envelope and phase objective functions. We test with a 2D-canonical model the susceptibility of the functions to the initial model perturbations. To complete de study with a more realistic synthetic example we test the functions with the Marmousi model. The L2-norm and phase objective functions give the highest resolution images and the CCTT, NIM and envelope objective functions lead to smooth models. However in realistic initial conditions, L2 and phase misfits fail in recovering the velocity model in contrast to the CCTT, NIM and envelope functions that maintain a more consistent behavior.