Time filter

Source Type

San Mateo, CA, United States

Guitton A.,Geo Imaging Solutions Inc. | Claerbout J.,Stanford University
Geophysical Prospecting

With the pyramid transform, 2D dip spectra can be characterized by 1D prediction-error filters (pefs) and 3D dip spectra by 2D pefs. These filters, contrary to pefs estimated in the frequency-space domain (ω, x), are frequency independent. Therefore, one pef can be used to interpolate all frequencies. Similarly, one pef can be computed from all frequencies, thus yielding robust estimation of the filter in the presence of noise. This transform takes data from the frequency-space domain (ω, x) to data in a frequency-velocity domain (ω, u=ω·x) using a simple mapping procedure that leaves locations in the pyramid domain empty. Missing data in (ω, x)-space create even more empty bins in (ω, u)-space. We propose a multi-stage least-squares approach where both unknown pefs and missing data are estimated. This approach is tested on synthetic and field data examples where aliasing and irregular spacing are present. © 2010 European Association of Geoscientists & Engineers. Source

Kaelin B.,Geo Imaging Solutions Inc. | Carvajal C.,Geo Imaging Solucoes Tecnologicas em Geociencias Ltda
SEG Technical Program Expanded Abstracts

Reverse time migration (RTM) has become the favorite imaging methods in areas of complex geology. However, RTM is also known for producing low frequency artifacts, where sharp velocity contrasts are present. We show that the imaging condition applied with time-shift gathers offers an excellent opportunity to remove artifacts based on properties of wave propagation. © 2011 Society of Exploration Geophysicists. Source

Claerbout J.F.,Stanford University | Guitton A.,Geo Imaging Solutions Inc.
75th European Association of Geoscientists and Engineers Conference and Exhibition 2013 Incorporating SPE EUROPEC 2013: Changing Frontiers

Predictive deconvolution does not yield Ricker wavelets as source wavelets. Analytic theory here tells how to fix it. The theory is not inverse theory. It is computable in N. log(N) time. Results here confirm better seismogram polarities. Copyright © (2012) by the European Association of Geoscientists & Engineers All rights reserved. Source

Claerbout J.,Stanford University | Guitton A.,Geo Imaging Solutions Inc.
Geophysical Prospecting

Ricker-compliant deconvolution spikes at the center lobe of the Ricker wavelet. It enables deconvolution to preserve and enhance seismogram polarities. Expressing the phase spectrum as a function of lag, it works by suppressing the phase at small lags. A by-product of this decon is a pseudo-unitary (very clean) debubble filter where bubbles are lifted off the data while onset waveforms (usually Ricker) are untouched. © 2014 European Association of Geoscientists & Engineers. Source

Guitton A.,Geo Imaging Solutions Inc. | Claerbout J.,Stanford University

Being disturbed by the discrepancy between the Ricker wavelet and minimum phase wavelets, we wondered if a sparseness criterion could get us deconvolved data with the event polarity being more clearly evident. Five data sets found it does. The sparseness criterion we used is a hyperbolic penalty function. It ranged from l2 at small residuals to l1 at large residuals. The main pitfall was that introducing negative filter lags introduced a null space (obviously so for Gaussian data). The null space demanded a regularization. We found a formulation in the domain of the Fourier transform of a log spectrum, in which a Ricker-style regularization appeared. Curiously, this regularization eliminated the leg jumps. A quasi-Newton solver was faster than that of our earlier work, a combination of conjugate directions with a Newton solver. © 2015 Society of Exploration Geophysicists. Source

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