Application of Wavelet Spectral Decomposition for Geological Interpretation of Seismic Data

Butorin, Alexander

doi:10.17265/2328-2193/2016.05.004

Cited by 1 publication

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“…The spectral content of seismic data is dependent on the layer thicknesses and on the dominant frequency of the wave field (Butorin, 2016). Variations in spectral content occur due to variations in bed thickness/tuning effects, attenuation/dispersion of the seismic reflection signals and changes in pore-fill, in particular the presence of gas (Partyka et al, 1999;Chapman et al, 2006;Odebeatu et al, 2006;Zhang et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Continuous Wavelet Transform Based Spectral Decomposition of 3d Seismic Data for Reservoir Characterization in Oyi Field, se Niger Delta

Ehirim¹,

Akpan²

2017

American Journal of Applied Sciences

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Continuous Wavelet Transform (CWT) is one of the most used wavelet transform based spectral decomposition methods in the direct detection of hydrocarbons and as an indicator of stratigraphic variability due to its optimal time-frequency resolution and variable time window requirements. CWT based spectral decomposition was applied on a 3D Post Stack Time Migrated (PSTM) seismic data acquired over a producing field using morlet wavelet and a time varying analysis window. Frequency amplitude slices of 10 Hz to 50 Hz were extracted from a 1625 ms HD1 seismic horizon and analyzed for possible hydrocarbon indications and stratigraphy. Hydrocarbon filled reservoir sands were delineated as low frequency high amplitude spectral anomalies between 20 Hz to 30 Hz frequency band coincident with the locations of producing wells in the field. Also, high frequency high amplitude spectral anomaly were delineated at predominantly 50 Hz frequency indicating a thin-bed with probable hydrocarbon saturation particularly gas, suspected to be a bypass hydrocarbon zone. Result also shows amplitude diminution with increasing frequency attributed to local variations in lithology. Therefore, appropriate application of this method will improve reservoir characterization and enhanced bed thickness definition, de-risk prospects and minimize dry well drilling in the field.

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