基于TK能量的峰值频率在沉积旋回划分中的应用

doi:10.11720/wtyht.2020.1465

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Abstract

Sedimentary cycle analysis plays an important role in stratigraphic theory research and petroleum exploration and development.Qualitative division of logging curves is a conventional method for dividing sedimentary cycles,which is more accurate at wellbore locations,but the division of sedimentary cycles in non-wellbore locations mainly depends on geological knowledge and has strong subjectivity.Seismic data contain abundant information related to sedimentary cycles.Sedimentary cycles can be divided by using time-frequency attribute curves.In this paper,the generalized S-transform method with better time-frequency resolution is used to calculate the time-frequency attribute curve,and the method is applied to four sedimentary cycle models:normal cycle,inverse cycle,normal-inverse cycle and inverse-normal cycle.The results of cycles division of the model validate the validity of the peak frequency attributes of time-frequency spectrum in the division of sedimentary cycles;However,in the practical application of seismic data,the time resolution of time-frequency spectrum is not high.Teager-Kaiser energy spectrum based on time-frequency spectrum improves the time positioning and focusing of time-frequency analysis results.The division of sedimentary cycles based on Teager-Kaiser energy spectrum attributes can better depict the changes of geological structure and thin interbedded structure.The method is applied to the Jurassic sedimentary cycle division of an oil field in Xinjiang.The results of the division are in good agreement with those of the well data,which verifies the reliability of the method.

Key words： sedimentary cycle time-frequency analysis generalized S transform Teager-Kaiser energy peak frequency

Received: 30 September 2019 Published: 29 December 2020

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	Articles by authors
	Wen HE
	Jia-Ming CAI
	Zhi-Hua SONG
	Hai-Yin LI
	Hao ZHANG
	Kong-Zhi HUANG
	Yan-Bin GUAN

Cite this article:

Wen HE,Jia-Ming CAI,Zhi-Hua SONG, et al. Sedimentary cycle division using peak frequency of time-frequency Teager-Kaiser energy[J]. Geophysical and Geochemical Exploration, 2020, 44(6): 1336-1344.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2020.1465 OR https://www.wutanyuhuatan.com/EN/Y2020/V44/I6/1336

Normal cycle model and its seismic response
a—velocity model;b—reflection coefficient;c—synthetic;d—time-frequency spectrum

Inverse cycle model and its seismic response
a—velocity model;b—reflection coefficient;c—synthetic;d—time-frequency spectrum

Inverse-normal cycle model and its seismic response
a—velocity model;b—reflection coefficient;c—synthetic;d—time-frequency spectrum

Normal-inverse cycle model and its seismic response
a—velocity model;b—reflection coefficient;c—synthetic;d—time-frequency spectrum

Inverse-normal cycle model and its peak frequency mirror image、normal-inverse cycle model and its peak frequency mirror image
a—inverse-normal cycle model;b—peak frequency mirror image of model a;c—normal-inverse cycle model;d—peak frequency mirror image of model c

TK energy spectrum test of cycle model

Seismic profile、seismic trace time-frequency spectrum cross well and peak frequency curve
a—seismic profile;b—seismic trace time-frequency spectrum cross well;c—peak frequency curve cross well

T-K energy spectrum、T-K peak frequency curve and its frequency-division curve
a—T-K energy spectrum;b—T-K peak frequency curve;c—low frequency component of b;d—intermediate frequency component of b;e—high frequency component of b

Cross-well section interpretation results based on time depth calibration and previous results
a—geological stratification,lithology and cycle based on lithology division;b—short-term cycle;c—medium-term cycle;d—long-term cycle;e—seismic profile

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