Efficient seismic volume compression using the lifting scheme

Faouzi M. Khene; Samir H. Abdul-Jauwad

doi:10.1117/12.408582

4 December 2000 Efficient seismic volume compression using the lifting scheme

Faouzi M. Khene, Samir H. Abdul-Jauwad

Proceedings Volume 4119, Wavelet Applications in Signal and Image Processing VIII; (2000) https://doi.org/10.1117/12.408582
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

An advanced seismic compression technique is proposed to mange seismic data in a world of ever increasing data volumes in order to maintain productivity without compromising interpretation results. A separable 3D discrete wavelet transform using long biorthogonal filters is used. The computation efficiency of the DWT is improved by factoring the wavelet filters using the lifting scheme. In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. The proposed technique is tested on a seismic volume from the Stratton field in South Texas. The resulting 3-level multiresolution decomposition yields 21 detail sub-volumes and a unique low-resolution sub-volume. The detail wavelet coefficients are quantized with an adaptive threshold uniform scalar quantizer. The scale-dependent thresholds are determined with the Stein unbiased risk estimate principle. As the approximation coefficients represents a smooth low-resolution version of the input data they are only quantized using a uniform scalar quantizer. Finally, a run-length plus a Huffman encoding are applied for binary coding of the quantized coefficients.

Citation Download Citation

Faouzi M. Khene and Samir H. Abdul-Jauwad "Efficient seismic volume compression using the lifting scheme", Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); https://doi.org/10.1117/12.408582

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KEYWORDS

Wavelets

Discrete wavelet transforms

Optical filters

Wavelet transforms

3D acquisition

3D image processing

Receivers

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