2nd SEG/DGS Workshop Near Surface Modeling and Imaging のご案内
http://www.seg.org/events/upcoming-seg-meetings/2016/ns-modelling-imaging-20162nd SEG/DGS Workshop
Near Surface Modeling and Imaging
CALL FOR CONTRIBUTIONS
Submission Deadline: 24 August 2015
Submit your abstract now!
Date 6-7 March 2016
Location InterContinental Regency Bahrain Manama, Bahrain
Sponsored by: Society of Exploration Geophysicists of Japan
Please send us an email mailto: firstname.lastname@example.org?subject=2016
Near Surface Workshop: Call for Papers
The first edition of the workshop held in 2014 was well attended by geoscientists from a wide geographic area including North America, Europe, Asia, Africa, and the Middle East. A broad range of near-surface disciplines was represented from academia and industry covering aspects of engineering and hydrocarbon exploration. The workshop led to a greater understanding of the importance of knowledge sharing among various disciplines in the modeling and imaging of the near surface. The workshop also explored emerging and underdeveloped techniques including ground-penetrating radar, full-waveform inversion, and surface waves. The need for further understanding of guided waves, anisotropy, velocity inversions, and the creation of an inclusive near surface model was identified.
The objective of the upcoming 2016 Workshop http://www.seg.org/events/upcoming-seg-meetings/2016/ns-modelling-imaging-2016 is to follow up on 2014 discussions and to share recent case studies and advancements in emerging technologies addressing the near surface modeling, imaging and characterization challenges.
We invite contributions related to near-surface characterization which include:
challenging case histories
seismic methods (refraction, tomography, etc.)
extreme gradients and velocity inversion
joint inversion of seismic and nonseismic data
dynamic corrections, datuming, and imaging
time versus depth imaging
emerging technologies (FWI, interferometry, passive seismic, etc.)
refraction and reflection tomography: bridging the gap between shallow and deep
prospect-generation risk assessment
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