scholarly journals Active seismic studies in valley glacier settings: strategies and limitations

2018 ◽  
Vol 64 (247) ◽  
pp. 796-810 ◽  
Author(s):  
JENNA M. ZECHMANN ◽  
ADAM D. BOOTH ◽  
MARTIN TRUFFER ◽  
ALESSIO GUSMEROLI ◽  
JASON M. AMUNDSON ◽  
...  

ABSTRACTSubglacial tills play an important role in glacier dynamics but are difficult to characterize in situ. Amplitude Variation with Angle (AVA) analysis of seismic reflection data can distinguish between stiff tills and deformable tills. However, AVA analysis in mountain glacier environments can be problematic: reflections can be obscured by Rayleigh wave energy scattered from crevasses, and complex basal topography can impede the location of reflection points in 2-D acquisitions. We use a forward model to produce challenging synthetic seismic records in order to test the efficacy of AVA in crevassed and geometrically complex environments. We find that we can distinguish subglacial till types in moderately crevassed environments, where ‘moderate’ depends on crevasse spacing and orientation. The forward model serves as a planning tool, as it can predict AVA success or failure based on characteristics of the study glacier. Applying lessons from the forward model, we perform AVA on a seismic dataset collected from Taku Glacier in Southeast Alaska in March 2016. Taku Glacier is a valley glacier thought to overlay thick sediment deposits. A near-offset polarity reversal confirms that the tills are deformable.

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. N43-N49 ◽  
Author(s):  
Jin Zhang ◽  
Yanguo Wang ◽  
David C. Nobes ◽  
Guangnan Huang ◽  
Hongxing Li

Inverse [Formula: see text] filtering can perform energy compensation and phase correction of seismic reflection data, but it has an instability problem due to its high-pass characteristics. Although improved methods, such as gain-limited inverse [Formula: see text] filtering and stabilized inverse [Formula: see text] filtering, overcome the instability to some extent, they are not suitable for compensating deep seismic reflection events with weak energy. Focusing on the enhancement of deep seismic events, we have developed a balanced filtering method based on the ratio of the phase-compensated signal to its analytic signal counterpart. The method is insensitive to the depth of seismic records, and it can make shallow and deep seismic records visible simultaneously. When tested on synthetic data and real seismic data, compared with other methods, the balanced filtering method improves the amplitude strength of the deep reflection events and the continuity of shallow and deep seismic events effectively, which makes the deep reflection data easier to interpret.


Geophysics ◽  
1999 ◽  
Vol 64 (6) ◽  
pp. 1939-1948 ◽  
Author(s):  
Kees Wapenaar ◽  
Aart‐Jan van Wijngaarden ◽  
Wim van Geloven ◽  
Taco van der Leij

The fine layering of the earth’s subsurface causes apparent amplitude‐variation‐with‐angle (AVA) effects in seismic reflection data. One can distinguish between reflection‐ and propagation‐related apparent AVA effects: the reflection of a package of thin layers is accompanied with angle‐dependent wavelet interference, whereas propagation through finely layered media causes angle‐dependent wavelet dispersion. Obviously, both types of apparent AVA effects hinder AVA inversion for the elastic parameters. Due to the band limitation of the seismic data, the reflection‐related interference effects cannot be removed. However, they can be equalized for all propagation angles by applying an angle‐dependent filter in the imaging step in angle‐dependent migration schemes. The underlying assumption is that the source function is known and that source directivity effects have been compensated prior to migration. The propagation‐related dispersion effects can be compensated for in the downward extrapolation process by means of inverse generalized primary propagators. Angle‐dependent migration, including the above mentioned modifications, yields an angle‐dependent reflectivity section in which the apparent AVA effects of fine layering are suppressed.


2006 ◽  
Vol 55 (3) ◽  
pp. 129-139 ◽  
Author(s):  
Avihu Ginzburg ◽  
Moshe Reshef ◽  
Zvi Ben-Avraham ◽  
Uri Schattner

Data Series ◽  
10.3133/ds496 ◽  
2009 ◽  
Author(s):  
Janice A. Subino ◽  
Shawn V. Dadisman ◽  
Dana S. Wiese ◽  
Karynna Calderon ◽  
Daniel C. Phelps

Data Series ◽  
10.3133/ds259 ◽  
2007 ◽  
Author(s):  
Arnell S. Harrison ◽  
Shawn V. Dadisman ◽  
Nick F. Ferina ◽  
Dana S. Wiese ◽  
James G. Flocks

Data Series ◽  
10.3133/ds308 ◽  
2007 ◽  
Author(s):  
Arnell S. Harrison ◽  
Shawn V. Dadisman ◽  
Christopher D. Reich ◽  
Dana S. Wiese ◽  
Jason W. Greenwood ◽  
...  

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