Can thin beds be identified using statistical phase estimation?

Edgar, J.A.; Selvage, J.I.

doi:10.3997/1365-2397.2011009

Cited by 5 publications

(5 citation statements)

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“…Castagna and Swan (1997) introduced the class IV AVO concept, these reflections have a negative normal incident reflection coefficient but a decrease in amplitude with offset, and such reflections can show phase reversals. Numerous examples of phase reversals have been published in the literature (Widess, 1973;Ross and Kinman, 1995;Castagna et al, 1998;Roden et al, 2005;van der Baan et al, 2010;Edgar and Selvage, 2011).…”

Section: Introductionmentioning

confidence: 99%

Interpretation of phase reversals in seismic reflections from attenuating targets

Wu¹,

Chapman

Angerer

2014

Geophysical Journal International

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Phase reversals are commonly observed during exploration seismic amplitude-versus-offset analysis, and usually modelled with the Zoeppritz equations. In practice, when multiple fluids are present we often deal with reflections from interfaces having a contrast in both elastic and anelastic properties. In this paper, we present a new phenomenological model for phase reversals in cases in which velocity dispersion and attenuation are present. We demonstrate strong qualitative differences in behaviour between the elastic and anelastic cases, influencing both the amplitude and phase of the reflection coefficient. Analysis of seismic data showing a phase reversal from a gas reservoir in the Vienna basin shows a striking agreement with the modelling. We conclude that the influence of fluid-induced dispersion on reflection data is a significant and measurable phenomenon in cases of practical interest, that recognition of the phenomena may be used as a novel fluid indicator and that frequencydependent rock physics analysis may be an important tool for both industrial geophysics and seismic monitoring of CO 2 storage.

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Section: Introductionmentioning

confidence: 99%

Interpretation of phase reversals in seismic reflections from attenuating targets

Wu¹,

Chapman

Angerer

2014

Geophysical Journal International

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“…We chose a pick location similar to that used by Edgar and Selvage (2011). A minimum time window length of twice the dominant wavelet period of roughly two times 50 ms at the base basalt was selected for signal analysis.…”

Section: Apparent Phase Changes In the Vertical Seismic Profile: Resultsmentioning

confidence: 99%

Effect of flood basalt stratigraphy on the phase of seismic waveforms recorded offshore Faroe Islands

2015

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The generation of short-period multiples between highly heterogeneous layers of basalt flows can strongly alter transmitted seismic wavefields. These layers filter and modify penetrating waves, producing apparent attenuation and phase changes in the observed waveforms. We investigated the waveform and apparent phase changes of the primary seismic signal using mainly the maximum kurtosis approach. We compared the seismic recordings from two short-offset vertical seismic profiles (VSPs) with synthetic seismograms, generated from sonic logs in the same wells, and we found that short-period multiples cause a rapid broadening of the primary arrivals and strong apparent phase changes within a short depth interval below the top of the basalt flows. Relatively large uncertainties were associated with estimating constant phase shifts of the seismic arrivals within the topmost 250 m of the basalt sequences, where complex scattering occurred. Within this interval of the Brugdan I well, a phase-only compensation of the first arrivals with a frequency-independent, combined scattering, and intrinsic attenuation operator was unfeasible. At a greater depth, we found that the phase shifts, predicted by a VSP-derived effective Q value, were similar to those estimated from the VSP signals using the kurtosis method. Thus, phase-only compensation with a combined scattering and intrinsic attenuation operator could work well depending on the seismic signal bandwidth and the distribution, depth, and magnitude of the impedance contrasts in the basalt sequence.

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“…Standard corrections at the data processing stage are unlikely to account fully for these effects. However, it is possible that geologic reasons exist for nonstationary wavelet phase, such as the presence of thin beds tuning the wavelet and producing an apparent 90 phase rotation (Edgar and Selvage, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Where nonstationary phase is estimated, without further information about the subsurface (such as a well log), it is not unambiguously possible to attribute the cause of time-dependent phase to any individual factor: It may be a remnant from acquisition and processing, it could be geologic, or it might be natural instability of the statistical method (Edgar and Selvage, 2010). However, a well-constrained, nonstationary Figure 8.…”

Section: Discussionmentioning

confidence: 99%

“…Reliability of wavelet estimation phase analysis has potential as an interpretational tool. For instance, it has been shown to highlight subtle variations in the local geology such as thin beds, pinch outs, meandering channels, carbonate reefs and variations in coal sequences (van der Baan and Fomel, 2009;van der Baan et al, 2010;Edgar and Selvage 2011).…”

Section: V67mentioning

confidence: 99%

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How Reliable is Statistical Wavelet Estimation?

Edgar

Baan

2011

Proceedings

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Well logs often are used for the estimation of seismic wavelets. The phase is obtained by forcing a well-derived synthetic seismogram to match the seismic, thus assuming the well log provides ground truth. However, well logs are not always available and can predict different phase corrections at nearby locations. Thus, a wavelet-estimation method that reliably can predict phase from the seismic alone is required. Three statistical wavelet-estimation techniques were tested against the deterministic method of seismic-to-well ties. How the choice of method influences the estimated wavelet phase was explored, with the aim of finding a statistical method which consistently predicts a phase in agreement with well logs. It was shown that the statistical method of kurtosis maximization by constant phase rotation consistently is able to extract a phase in agreement with seismic-to-well ties. A statistical method based on a modified mutual-information-rate criterion was demonstrated to provide frequency-dependent phase wavelets where the deterministic method could not. Time-varying statistical wavelets also were estimated with good results -a challenge for deterministic approaches because of the short logging sequence. It was concluded that statistical techniques can be used as quality control tools for the deterministic methods, as a way of extrapolating phase away from wells, or to act as standalone tools in the absence of wells.

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Can thin beds be identified using statistical phase estimation?

Cited by 5 publications

References 0 publications

Interpretation of phase reversals in seismic reflections from attenuating targets

Interpretation of phase reversals in seismic reflections from attenuating targets

Effect of flood basalt stratigraphy on the phase of seismic waveforms recorded offshore Faroe Islands

How Reliable is Statistical Wavelet Estimation?

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