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RESEARCH ON MEASUREMENT METHOD OF SIMILARITY OF SEISMIC RECORDS WITH WAVELET ATTRIBUTES

Xiucheng Wei

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Abstract

In order to improve precise of measurement of faults by 3-D data with low frequency (primary frequency in 15 Hz~30 Hz), this paper discusses a method combined wavelet attribute with coherency. When horizontal distance of faults are very small and wave shape of seismic records near the faults are very similar, coherency method can not show the faults clearly itself. Focusing on the problem, we analysis several kinds of methods of measuring similarity and, at last, propose coherency one based on wavelet attributes to improve capacity of fault detection. The applications show that the method is reasonable and utilitarian. The method not only describes similarity more precisely, but also provides a way of accurate analysis to quantitative parameters of seismic exploration.

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What this paper is about

In order to improve precise of measurement of faults by 3-D data with low frequency (primary frequency in 15 Hz~30 Hz), this paper discusses a method combined wavelet attribute with coherency. When horizontal distance of faults are very small and wave shape of seismic records near the faults are very similar, coherency method can not show the faults clearly itself. Focusing on the problem, we analysis several kinds of methods of measuring similarity and, at last, propose coherency one based on wavelet attributes to improve capacity of fault detection. The applications show that the method is reasonable and utilitarian. The method not only describes similarity more precisely, but also provides a way of accurate analysis to quantitative parameters of seismic exploration.

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Available abstract

In order to improve precise of measurement of faults by 3-D data with low frequency (primary frequency in 15 Hz~30 Hz), this paper discusses a method combined wavelet attribute with coherency. When horizontal distance of faults are very small and wave shape of seismic records near the faults are very similar, coherency method can not show the faults clearly itself. Focusing on the problem, we analysis several kinds of methods of measuring similarity and, at last, propose coherency one based on wavelet attributes to improve capacity of fault detection. The applications show that the method is reasonable and utilitarian. The method not only describes similarity more precisely, but also provides a way of accurate analysis to quantitative parameters of seismic exploration.

Key concepts: Wavelet, Similarity (geometry), Computer science, Data mining, Fault (geology), Algorithm, Pattern recognition (psychology), Geology

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