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Title: Reducing Disk Storage of Full-3D Seismic Waveform Tomography (F3DT) Through Lossy Online Compression

Journal Article · · Computers and Geosciences
 [1];  [2];  [3]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of Wyoming, Laramie, WY (United States)
  3. National Cheng Kung Univ., Tainan City (Taiwan)
+ Show Author Affiliations

Full-3D seismic waveform tomography (F3DT) is the latest seismic tomography technique that can assimilate broadband, multi-component seismic waveform observations into high-resolution 3D subsurface seismic structure models. The main drawback in the current F3DT implementation, in particular the scattering-integral implementation (F3DT-SI), is the high disk storage cost and the associated I/O overhead of archiving the 4D space-time wavefields of the receiver- or source-side strain tensors. The strain tensor fields are needed for computing the data sensitivity kernels, which are used for constructing the Jacobian matrix in the Gauss-Newton optimization algorithm. In this study, we have successfully integrated a lossy compression algorithm into our F3DT SI workflow to significantly reduce the disk space for storing the strain tensor fields. The compressor supports a user-specified tolerance for bounding the error, and can be integrated into our finite-difference wave-propagation simulation code used for computing the strain fields. The decompressor can be integrated into the kernel calculation code that reads the strain fields from the disk and compute the data sensitivity kernels. During the wave-propagation simulations, we compress the strain fields before writing them to the disk. To compute the data sensitivity kernels, we read the compressed strain fields from the disk and decompress them before using them in kernel calculations. Experiments using a realistic dataset in our California statewide F3DT project have shown that we can reduce the strain-field disk storage by at least an order of magnitude with acceptable loss, and also improve the overall I/O performance of the entire F3DT-SI workflow significantly. The integration of the lossy online compressor may potentially open up the possibilities of the wide adoption of F3DT-SI in routine seismic tomography practices in the near future.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1258513
Alternate ID(s):
OSTI ID: 1358859
Report Number(s):
LLNL-JRNL-678678
Journal Information:
Computers and Geosciences, Vol. 93; ISSN 0098-3004
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 25 works
Citation information provided by
Web of Science

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Cited By (3)

Data Reduction Techniques for Simulation, Visualization and Data Analysis: Survey on Scientific Data Reduction Techniques journal March 2018
Compression Challenges in Large Scale Partial Differential Equation Solvers journal September 2019
An Efficient Encoding Algorithm Using Local Path on Huffman Encoding Algorithm for Compression journal February 2019

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