Research and Application of Spectral Decomposition in Carbonate Reservoir and Fault Identification in MaiJie Let Gas Field, Amu Darya Basin

Hao Yu; Jin Song Li; Yan Zhang; Guang Cheng Xu

doi:10.4028/www.scientific.net/AMR.616-618.141

Paper Titles

Comprehensive Evaluation and Prediction of Geothermal Resources in Liaohe Basin
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Study on Fault Activity in Linnan Area of Huimin Depression, Bohai Bay Basin
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Fluid Flow of Daxing Conglomerate in Langgu Depression and its Controlling Effects on Reservoir
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Research and Application of Spectral Decomposition in Carbonate Reservoir and Fault Identification in MaiJie Let Gas Field, Amu Darya Basin
p.141

Research on Diagenetic Facies of Low Permeability Reservoir: A Case Study of the Yanchang Formation in Longdong Area, Ordos Basin
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Geological Characteristics of Difficult Reservoirs in Logging Interpretation
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Combination Distribution Characteristics and Corresponding Material Sources of Surface Clay Minerals in Beibu Gulf, China
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Shear Rheological Properties of Sericite-Greisen Phyllite
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 616-618Research and Application of Spectral Decomposition...

Research and Application of Spectral Decomposition in Carbonate Reservoir and Fault Identification in MaiJie Let Gas Field, Amu Darya Basin

Abstract:

Spectral decomposition is to convert seismic signals from the time domain to the frequency domain by mathematical transformation, and analyze amplitude and phase response characteristics of different scale geological bodies. Spectral decomposition could get higher resolution than conventional seismic data. In the identification of the fault system, it is fit for fault interpretation and plane combination of the sections. In the reservoir prediction, it can identify the shape and contour of the reservoir. This document analyzed algorithm and applicability of short time Fourier transform, continuous wavelet transform and S-transform. Using these three methods for carbonate reservoir identification in MaiJie let gas field, Amu Darya Basin, it proves that the frequency division section is more clearly than conventional seismic section in reservoir and fault description. And S-transform gets the best result.

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Periodical:

Advanced Materials Research (Volumes 616-618)

Pages:

141-144

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.616-618.141

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Online since:

December 2012

Authors:

Hao Yu, Jin Song Li, Yan Zhang, Guang Cheng Xu

Keywords:

Continuous Wavelet Transform, Fault and Reservoir Identification, Short Time Fourier Transform (STFT), Spectral Decomposition, S-Transform

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