Seismic processing using Parallel 3D FMM

This thesis develops and tests 3D Fast Marching Method (FMM) algorithm and apply these to seismic simulations. The FMM is a general method for monotonically advancing fronts, originally developed by Sethian. It calculates the first arrival time for an advancing front or wave. FMM methods are used fo...

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Main Author: Borlaug, Idar
Format: Others
Language:English
Published: Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap 2007
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8792
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spelling ndltd-UPSALLA1-oai-DiVA.org-ntnu-87922013-01-08T13:26:25ZSeismic processing using Parallel 3D FMMengBorlaug, IdarNorges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskapInstitutt for datateknikk og informasjonsvitenskap2007ntnudaimSIF2 datateknikkKomplekse datasystemerThis thesis develops and tests 3D Fast Marching Method (FMM) algorithm and apply these to seismic simulations. The FMM is a general method for monotonically advancing fronts, originally developed by Sethian. It calculates the first arrival time for an advancing front or wave. FMM methods are used for a variety of applications including, fatigue cracks in materials, lymph node segmentation in CT images, computing skeletons and centerlines in 3D objects and for finding salt formations in seismic data. Finding salt formations in seismic data, is important for the oil industry. Oil often flows towards gaps in the soil below a salt formation. It is therefore, important to map the edges of the salt formation, for this the FMM can be used. This FMM creates a first arrival time map, which makes it easier to see the edges of the salt formation. Herrmann developed a 3D parallel algorithm of the FMM testing waves of constant velocity. We implemented and tested his algorithm, but since seismic data typically causes a large variation of the velocities, optimizations were needed to make this algorithm scale. By optimising the border exchange and eliminating much of the roll backs, we delevoped and implemented a much improved 3D FMM which achieved close to theoretical performance, for up to at least 256 nodes on the current supercomputer at NTNU. Other methods like, different domain decompositions for better load balancing and running more FMM picks simultaneous, will also be discussed. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8792Local ntnudaim:3732application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic ntnudaim
SIF2 datateknikk
Komplekse datasystemer
spellingShingle ntnudaim
SIF2 datateknikk
Komplekse datasystemer
Borlaug, Idar
Seismic processing using Parallel 3D FMM
description This thesis develops and tests 3D Fast Marching Method (FMM) algorithm and apply these to seismic simulations. The FMM is a general method for monotonically advancing fronts, originally developed by Sethian. It calculates the first arrival time for an advancing front or wave. FMM methods are used for a variety of applications including, fatigue cracks in materials, lymph node segmentation in CT images, computing skeletons and centerlines in 3D objects and for finding salt formations in seismic data. Finding salt formations in seismic data, is important for the oil industry. Oil often flows towards gaps in the soil below a salt formation. It is therefore, important to map the edges of the salt formation, for this the FMM can be used. This FMM creates a first arrival time map, which makes it easier to see the edges of the salt formation. Herrmann developed a 3D parallel algorithm of the FMM testing waves of constant velocity. We implemented and tested his algorithm, but since seismic data typically causes a large variation of the velocities, optimizations were needed to make this algorithm scale. By optimising the border exchange and eliminating much of the roll backs, we delevoped and implemented a much improved 3D FMM which achieved close to theoretical performance, for up to at least 256 nodes on the current supercomputer at NTNU. Other methods like, different domain decompositions for better load balancing and running more FMM picks simultaneous, will also be discussed.
author Borlaug, Idar
author_facet Borlaug, Idar
author_sort Borlaug, Idar
title Seismic processing using Parallel 3D FMM
title_short Seismic processing using Parallel 3D FMM
title_full Seismic processing using Parallel 3D FMM
title_fullStr Seismic processing using Parallel 3D FMM
title_full_unstemmed Seismic processing using Parallel 3D FMM
title_sort seismic processing using parallel 3d fmm
publisher Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap
publishDate 2007
url http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8792
work_keys_str_mv AT borlaugidar seismicprocessingusingparallel3dfmm
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