Seismic:Reflection:MCS

Processed 3-D multi-channel seismic data volume for the East Pacific Rise 9°42'-9°57'N from the MGL0812 survey (classical time processing by H. Carton)
This data set is a time-processed 3-D multi-channel seismic data volume for the East Pacific Rise 9°42'-9°57'N. It is in SEG-Y format and extends for about 27.5 km (along-axis) by 18 km (across-axis) and from 0 to 6.5 seconds two-way travel time on the vertical axis. Seismic reflection events imaged in 3-D by this volume are the seafloor, the axial magma lens, off-axis magma lenses, and the oceanic Moho. The volume was built from multi-channel seismic lines acquired across the East Pacific Rise crest between 9°42'-9°57'N during the MGL0812 seismic survey on R/V Langseth in 2008 (chief scientists: J.C. Mutter, S.M. Carbotte, J.P. Canales, M.R. Nedimovic). A time processing sequence was applied, which includes 3-D geometry definition, spherical divergence correction, filtering, resampling to 4 ms, trace editing, flexible binning, preparation of a 3-D stacking velocity model (for seafloor, magma lens events and Moho; this processing sequence does not include the layer 2A event), normal move-out correction, stacking, post-stack signal enhancement (noise attenuation, predictive deconvolution), cross-line interpolation (from 6.25 x 37.5m bin size to 6.25 x 18.75m bin size), muting of first seafloor multiple, and 3-D Kirchhoff post-stack time migration (see separate file for processing details). Funding was provided by NSF awards OCE03-27872 and OCE03-27885.
Carton, Hélène
Investigator
LDEO
Carbotte, Suzanne
Investigator
LDEO
Mutter, John
Investigator
LDEO
Canales, JuanPablo
Investigator
WHOI
Nedimovic, Mladen
Investigator
Dalhousie
Device Info
Seismic: MCS
LDEO
Platform
Marcus G. Langseth (Array)
LDEO
Awards
Data DOI
Quality
2
The data have been processed/modified to a level beyond that of basic quality control (e.g. final processed sonar data, photo-mosaics).
Data Files
References
Acquisition Information
Documents
Data Citation Information
ISO/XML Metadata
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