<i>L</i>1-<i>L</i>2范数联合约束稀疏脉冲反演的应用

王宇; 韩立国; 周家雄; 李海鹏

Volume 34 Issue 5

Sep. 2009

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WANG Yu, HAN Li-guo, ZHOU Jia-xiong, LI Hai-peng, 2009. Application of Combined Norm Constrained Sparseness Spike Inverse. Earth Science, 34(5): 835-840.

Citation:

WANG Yu, HAN Li-guo, ZHOU Jia-xiong, LI Hai-peng, 2009. Application of Combined Norm Constrained Sparseness Spike Inverse. Earth Science, 34(5): 835-840.

WANG Yu, HAN Li-guo, ZHOU Jia-xiong, LI Hai-peng, 2009. Application of Combined Norm Constrained Sparseness Spike Inverse. Earth Science, 34(5): 835-840.

Citation:

WANG Yu, HAN Li-guo, ZHOU Jia-xiong, LI Hai-peng, 2009. Application of Combined Norm Constrained Sparseness Spike Inverse. Earth Science, 34(5): 835-840.

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Application of Combined Norm Constrained Sparseness Spike Inverse

1.
China National Of f shore Oil Company Ltd-Zhan jiang, Zhan jiang 524057, China
2.
College of Geoex ploration Science and Technology, Jilin University, Chang chun 130026, China

Received Date: 2009-01-23
Publish Date: 2009-09-25

Abstract

Abstract

Sparse-spike deconvolution is an inverse issue which estimates the time and the amplitudes of the sparseness reflectivity (spikes) from the noisy seismic traces.Sparseness spike inverse is highly non-linear optimization problem that can be solved using the L1-L2 norm constrained method introduced in this paper.This method is characterized with its application of the log-barrier interior point to solve the sparseness inverse problem which is higher in terms of resolution and faster than conventional optimization methods.Resultsfrom the synthetic and real 3D data show that the physically meaningful high-resolution sparse-spike profile can be derived from the band-limited noisy data.Real data show that the method improves seismic resolution and estimates the thickness of thin bed which can reduce the uncertainty of resource estimation and oil field production.
- reflection coefficient inverse,
- sparse-constrained inverse,
- interior point algorithm,
- norm

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References(15)

References

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