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- Volume 27, Issue 9, 2009
First Break - Volume 27, Issue 9, 2009
Volume 27, Issue 9, 2009
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News Feature: Impact of global financial crisis on Russian oil and gas geophysics
More LessProfessor Nicolay A. Savostyanov (President, EurAsian Geophysical Society) takes a sobre look at the effect of the world economic recession on oil and gas geophysics-related activities in Russia.
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Full azimuth: realizing the benefits
Authors P. Taylor, D. Hill, J. Kapoor and N. MoldoveanuPaul Taylor, David Hill, Jerry Kapoor and Nick Moldoveanu consider the potential for improvements in seismic imaging, and the understanding of anisotropy made possible through designing processing workflows that honour and exploit a full range of individual source-receiver azimuths.
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Shear wave splitting applications for fracture analysis and improved imaging: some onshore examples
Authors R. Bale, B. Gratacos, B. Mattocks, S. Roche, K. Poplavskii and X. LiRichard Bale, Bruno Gratacos, Bruce Mattocks, Steve Roche, Kostya Poplavskii and Xinxiang Li1 explain the value of shear wave splitting for reservoir characterization when using multi-component land seismic data. They illustrate the technique with data examples from the US and Canada.
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Seismic data regularization with the anti-alias anti-leakage Fourier transform
Authors M. Schonewille, A Klaedtke, A Vigner, J Brittan and T MartinMichel Schonewille, Andreas Klaedtke, Alan Vigner, John Brittan and Tony Martin present a solution to a problem with regularly sampled data found in the use of the anti-alias anti-leakage Fourier transform (ALFT).
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Simple net pay estimation from seismic: a modelling study
By R. SimmAmplitude scaling techniques are a simple way of removing the effect of tuning on seismic maps and predicting net pay thickness in low-impedance hydrocarbon-bearing sands. This modelling study addresses net pay prediction in layered sand/shale reservoirs using reflectivity and band-limited impedance approaches. It is demonstrated that net pay prediction using band-limited impedance is more accurate than reflectivity. These techniques, however, are only appropriate in specific geological circumstances. Prior to application, it is advisable to evaluate potential accuracy through modelling as well as to consider the benefit of amplitude-versus-offset projections.
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Magic of smart averaging
By D. KrilovVarious methods of averaging or smoothing data fields are commonly used to suppress random noise and enhance anomaly characteristics for interpretation. A new approach, termed smart averaging, which reduces uncertainty in determination of anomaly size and location is introduced in this article. In this procedure, computation of each output value is considered to be an optimization problem based upon some criterion, or set of criteria, with different benefits for interpretation (e.g., sharp anomaly delineation, smoothing without suppressing anomalies, or reducing random noise or noise peaks without affecting anomaly characteristics). A subset of averaging window parameters (location, shape, and size) is tested for each grid point before some optimal window parameters are found, based upon some chosen criterion. Smart averaging can be useful in various data processing applications for interpretation purposes, such as data interpolation, image resolution and analysis, and correlation of well logs.
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Volumes & issues
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Volume 42 (2024)
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Volume 41 (2023)
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Volume 40 (2022)
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Volume 39 (2021)
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Volume 38 (2020)
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Volume 37 (2019)
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Volume 36 (2018)
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Volume 35 (2017)
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Volume 34 (2016)
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Volume 33 (2015)
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Volume 32 (2014)
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Volume 31 (2013)
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Volume 30 (2012)
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Volume 29 (2011)
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Volume 28 (2010)
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Volume 27 (2009)
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Volume 26 (2008)
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Volume 25 (2007)
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Volume 24 (2006)
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Volume 23 (2005)
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Volume 22 (2004)
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Volume 21 (2003)
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Volume 20 (2002)
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Volume 19 (2001)
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Volume 18 (2000)
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Volume 17 (1999)
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Volume 16 (1998)
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Volume 15 (1997)
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Volume 14 (1996)
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Volume 13 (1995)
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Volume 12 (1994)
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Volume 11 (1993)
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Volume 10 (1992)
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Volume 9 (1991)
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Volume 8 (1990)
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Volume 7 (1989)
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Volume 6 (1988)
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Volume 5 (1987)
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Volume 4 (1986)
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Volume 3 (1985)
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Volume 2 (1984)
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Volume 1 (1983)