Browsing by Author "Liang, Chen 1989-"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Seismic Spectral Bandwidth Extension and Reflectivity Decomposition(2018-05) Liang, Chen 1989-; Castagna, John P.; Chesnokov, Evgeni M.; Zheng, Yingcai; Ebrom, Daniel A.Various post-processing methods can be applied to seismic data to extend spectral bandwidth for resolution enhancement. Frequency-invention techniques produce spectrally-broadened seismic sections but arbitrarily create high frequencies without a physical basis, and thus, do not improve actual seismic resolution. On the other hand, under the assumption of sparsity, layer frequency responses can be extrapolated to frequencies outside the band of the original data using spectral periodicities determined from within the original seismic bandwidth. This can be accomplished by harmonic extrapolation. For blocky-earth structures, synthetic tests show that such spectral extrapolation can readily double the bandwidth, even in the presence of noise. Wedge models illustrate the resulting resolution enhancement. Tests of the frequency-invention methods and harmonic extrapolation on field-seismic data demonstrate that the frequency-invention methods modify the original seismic band such that the original data cannot be recovered by simple bandpass filtering, while harmonic extrapolation can be filtered back to the original band with good fidelity. Harmonic extrapolation exhibits acceptable ties between real and synthetic seismic data outside the original seismic band, while the frequency-invention methods have unfavorable well ties in the cases studied. Based upon sparse inversion, any seismogram can be decomposed according to the size of the inverted reflection coefficients producing the seismogram. Reflection coefficients can be sorted by the amplitudes and new seismic traces can be created including only reflection coefficients within certain amplitude ranges. By this reflectivity decomposition, subtle impedance variations occurring beneath nearby strong reflectors can be revealed seismically when only events caused by small reflection coefficients are passed. Doing impedance inversion on the weak-reflectivity trace shows impedance anomalies better than when weak events are covered by a nearby strong reflector. Amplitude maps for Canyon and Cisco formations in the Midland basin demonstrate that the prospective events can map out geologically better on the volume of weak-reflectivity traces, providing greatly improved visualization for the porous zones that are hidden in the original seismic data. Furthermore, quantitative analysis suggests that seismic attributes derived from reflectivity decomposition provide significantly improved correlation to the actual rock properties at well locations.Item Spectral Bandwidth Extension: Invention versus Harmonic Extrapolation(2014-05) Liang, Chen 1989-; Castagna, John P.; Chesnokov, Evgeni M.; Hilterman, Fred J.; Ebrom, Daniel A.There are valid and invalid post-processing methods to extend seismic bandwidth for resolution enhancement. Some methods attempt to invent high frequencies without a physical basis, while inversion-based methods extrapolate the spectra in reasonable ways. Frequency invention methods can extend the original seismic spectrum to desired spectral bandwidths. However, those spectral components they invent do not provide new effective information for enhancing resolution. Matching pursuit decomposition has been successfully applied to analyze the available spectrum of seismic data. Consequently, missing spectral components can be directly extrapolated from zero frequency all the way to the Nyquist frequency. Alternatively, the spectral information within the limited band can be modeled as an autoregressive process. Higher and lower frequencies outside the band can thus be predicted by designing a Wiener prediction filter. Spectral decomposition by matching pursuit on the band-limited seismic trace stabilizes the predictions to recover a broad-band reflectivity sequence. Further, continuous wavelet transform can be employed to spectrally decompose the band-limited signal into discrete sub-bands from which missing high and low frequencies could be extrapolated locally using multi-channel operators. Conventional sparse spike deconvolution attempts to retrieve a reflectivity sequence comprising isolated sparse delta functions, which may restore the missing part of the spectrum.