Full waveform inversion with extrapolated low frequency data

The availability of low frequency data is an important factor in the success of full waveform inversion (FWI) in the acoustic regime. The low frequencies help determine the kinematically relevant, low-wavenumber components of the velocity model, which are in turn needed to avoid convergence of FWI to spurious local minima. However, acquiring data below 2 or 3 Hz from the field is a challenging and expensive task. In this paper we explore the possibility of synthesizing the low frequencies computationally from high-frequency data, and use the resulting prediction of the missing data to seed the frequency sweep of FWI. As a signal processing problem, bandwidth extension is a very nonlinear and delicate operation. It requires a high-level interpretation of bandlimited seismic records into individual events, each of which is extrapolable to a lower (or higher) frequency band from the non-dispersive nature of the wave propagation model. We propose to use the phase tracking method for the event separation task. The fidelity of the resulting extrapolation method is typically higher in phase than in amplitude. To demonstrate the reliability of bandwidth extension in the context of FWI, we first use the low frequencies in the extrapolated band as data substitute, in order to create the low-wavenumber background velocity model, and then switch to recorded data in the available band for the rest of the iterations. The resulting method, EFWI for short, demonstrates surprising robustness to the inaccuracies in the extrapolated low frequency data. With two synthetic examples calibrated so that regular FWI needs to be initialized at 1 Hz to avoid local minima, we demonstrate that FWI based on an extrapolated [1, 5] Hz band, itself generated from data available in the [5, 15] Hz band, can produce reasonable estimations of the low wavenumber velocity models

Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data

The availability of low frequency data is an important factor in the success of full waveform inversion (FWI) in the acoustic regime. The low frequencies help determine the kinematically relevant, low-wavenumber components of the velocity model, which are in turn needed to avoid convergence of FWI to spurious local minima. However, acquiring data below 2 or 3 Hz from the field is a challenging and expensive task. In this paper we explore the possibility of synthesizing the low frequencies computationally from high-frequency data, and use the resulting prediction of the missing data to seed the frequency sweep of FWI. To demonstrate the reliability of bandwidth extension in the context of FWI, we first use the low frequencies in the extrapolated band as data substitute, in order to create the low-wavenumber background velocity model, and then switch to recorded data in the available band for the rest of the iterations. The resulting method, extrapolated FWI (EFWI), demonstrates surprising robustness to the inaccuracies in the extrapolated low frequency data. With a synthetic Marmousi model, we demonstrate that FWI based on an extrapolated [1,5] Hz band, itself generated from data available in the [5,15] Hz band, can produce reasonable estimations of the low wavenumber velocity models

A short note on phase and amplitude tracking for seismic event separation

We propose a method for decomposing a seismic record into atomic events defined by a smooth phase and a smooth amplitude. The method uses an iterative refinement-expansion tracking scheme to minimize the highly nonconvex objective function. We demonstrate the proposed method on a noisy synthetic record from the shallow Marmousi model. Finally, we show an application of our method to low frequency extrapolation on the same record. This note is a short version of Li and Demanet (2015).TOTAL (Firm)United States. Air Force. Office of Scientific ResearchUnited States. OffNational Science Foundation (U.S.

Extrapolated full-waveform inversion: An image-space approach

The primary factor that prevents full waveform inversion from universal success is the band-limited nature of seismic data, resulting in a gap between the low wavenumber background velocity model and the high wavenumber seismic images. In this paper, we propose to bridge the wavenumber gap in the extended image space, where full kinematic information in the data is preserved in spite of the inaccuracy of the background migration velocity model, and where the wavenumber range of the extended image is extrapolated using total-variation constrained deconvolution. This explicit wavenumber extrapolation is nested within least-squares reverse time migration iterations to ensure that the resulting extended images match the recorded band-limited data. We then synthesize reflection data using extended Born modeling with the extrapolated images. Numerical experiments show that although the total variation projection has limited the high frequencies that can be recreated by extended Born modeling, the low frequencies are reliably extrapolated at all offsets, given a reasonable starting velocity model. When the initial model is too crude, the proposed frequency extrapolation breaks down near the complex structures. Keywords: data reconstruction; deconvolution; full-waveform inversion; least-squares migrationUnited States. Air Force Office of Scientific Research (Grant FA9550-12-1-0328)United States. Air Force Office of Scientific Research (Grant FA9550-15-1-0078)United States. Office of Naval Research (Grant N00014-16-1-2122)National Science Foundation (U.S.) (Grant DMS-1255203

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than I% in most of climate regions although it could be as large as 10%

Internship Experience and Organizational Attractiveness: A Realistic Job Fit Perspective

Although job seekers often rely on indirect or inaccurate information to assess the attractiveness of potential employers, internship experience provides more realistic and accurate information, which may influence organizational attractiveness. Through the ex-ante and ex-post (i.e., pre-internship and post-internship) research design with a sample of Japanese undergraduate students in a university-sponsored internship program, we found that, although organizational attractiveness on average declined after the internship, skill variety and feedback from employees in the internship job were positively related to perceived needs-supplies (NS) fit beyond the effect of its pre-internship level. The NS fit, in turn, was related to organizational attractiveness beyond the effect of its pre-internship level. Moreover, some of the above mediating effects were stronger for interns with high social skill and/or high self-esteem. Our findings highlight the importance of the effect of internships on college students’ school-to-work transition