Frequency-dependent seismic reflection coefficient for discriminating gas reservoirs

Xu, Dingbang; Wang, Yanghua; Gan, Qigan; Jianming, Tang

doi:10.1088/1742-2132/8/4/003

Cited by 16 publications

(5 citation statements)

References 18 publications

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“…Seismic quality factor, Q, also contributes to the observable reflectivity of an interface, although only significantly where the Q-contrast exceeds an order of magnitude (Bourbié and Nur, 1984;Odebeatu et al, 2006). Two proposed mechanisms for Q to contribute to the apparent reflectivity of an interface are (a) frequency dependency of the reflection coefficient, since different frequency components of a wavelet propagate at different velocities in dispersive materials (Xu et al, 2011), and (b) introduction of a phase lag into the recorded waveform (Lines et al, 2008), since the reaction time of a high-to-low-Q interface is frequency-dependant (Quintal et al, 2009;Morozov, 2011). Q-based reflectivity is undoubtedly an important consideration in quantitative seismic interpetatoin but, at this stage of analysis, we assume small Q-contrasts allowing the associated reflectivity contributions to be neglected.…”

Section: Reflection Coefficients and Amplitude-versus-angle Responsesmentioning

confidence: 99%

Thin-layer effects in glaciological seismic amplitude-versus-angle (AVA) analysis: implications for characterising a subglacial till unit, Russell Glacier, West Greenland

et al. 2012

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Abstract. Seismic amplitude-versus-angle (AVA) methods are a powerful means of quantifying the physical properties of subglacial material, but serious interpretative errors can arise when AVA is measured over a thinly-layered substrate. A substrate layer with a thickness less than 1/4 of the seismic wavelength, λ, is considered "thin", and reflections from its bounding interfaces superpose and appear in seismic data as a single reflection event. AVA interpretation of subglacial till can be vulnerable to such thin-layer effects, since a lodged (non-deforming) till can be overlain by a thin (metre-scale) cap of dilatant (deforming) till. We assess the potential for misinterpretation by simulating seismic data for a stratified subglacial till unit, with an upper dilatant layer between 0.1-5.0 m thick (λ / 120 to > λ / 4, with λ = 12 m). For dilatant layers less than λ / 6 thick, conventional AVA analysis yields acoustic impedance and Poisson's ratio that indicate contradictory water saturation. A thin-layer interpretation strategy is proposed, that accurately characterises the model properties of the till unit. The method is applied to example seismic AVA data from Russell Glacier, West Greenland, in which characteristics of thin-layer responses are evident. A subglacial till deposit is interpreted, having lodged till (acoustic impedance = 4.26 ± 0.59 × 10 6 kg m −2 s −1 ) underlying a water-saturated dilatant till layer (thickness < 2 m, Poisson's ratio ∼ 0.5). Since thin-layer considerations offer a greater degree of complexity in an AVA interpretation, and potentially avoid misinterpretations, they are a valuable aspect of quantitative seismic analysis, particularly for characterising till units.

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Section: Reflection Coefficients and Amplitude-versus-angle Responsesmentioning

confidence: 99%

Thin-layer effects in glaciological seismic amplitude-versus-angle (AVA) analysis: implications for characterising a subglacial till unit, Russell Glacier, West Greenland

et al. 2012

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“…Ekone et al modeled the porosity using acoustic impedance and log data from the EK field in the Niger Delta (NO et al). Xu et al has used the frequency-dependent seismic reflex coefficient for the Discrimination of Gas Reservoirs (Xu et al 2011). Banik et al estimated pore pressure in the Gulf of Mexico employing acoustic impedance based on seismic data (Bjørlykke et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Geomechanical model and wellbore stability analysis utilizing acoustic impedance and reflection coefficient in a carbonate reservoir

Bagheri

Tanha

Ardejani

et al. 2021

J Petrol Explor Prod Technol

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One of the most important oil and gas drilling studies is wellbore stability analysis. The purpose of this research is to investigate wellbore stability from a different perspective. To begin, vertical stress and pore pressure were calculated. The lowest and maximum horizontal stress were calculated using poroelastic equations. The strike-slip to normal fault regime was shown by calculated in situ stress values. The 1-D geomechanical model was utilized to investigate the failure mechanisms and safe mud window estimation using the Mohr–Coulomb failure criterion. Using density and sonic (compressional and shear slowness) logs, the acoustic impedance (AI) and reflection coefficient (RC) logs were determined subsequently. The combination of layers with different AI indicates positive and negative values for the RC, zones prone to shear failure or breakout, and the mud weight in these zones should be increased, according to the interpretation of the AI and RC readings and the results of the geomechanical model. Furthermore, the zones with almost constant values of AI log and values close to zero for RC log are stable as homogeneously lithologically, but have a lower tensile failure threshold than the intervals that are sensitive to shear failure, and if the mud weight increases, these zones are susceptible to tensile failure or breakdown. Increased porosity values, which directly correspond with the shear failure threshold and inversely with the tensile failure threshold, cause AI values to decrease in homogenous zones, but have no effect on the behavior of the RC log. This approach can determine the potential zones to kick, loss, shear failure, and tensile failure in a short time.

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“…The implementation process of the FAVO inversion method can be briefly summarized as the following key steps: ① calculating the time-frequency spectrum of seismic traces using spectral decomposition techniques such as short-time Fourier transform [24], wavelet transform [25], S transform [26]; ② performing the spectral balancing technique to eliminate the overprint effect of wavelets; thus, we can obtain the time-frequency spectrum of the reflection coefficient [27]; ③ by selecting the key frequency points for calculation, the velocity dispersion properties can be estimated by the Smith-Gidlow approximation. Since then, based on different approximations and spectral decomposition methods [5,9,28], the ability of FAVO inversion to identify fluids has been verified on actual data.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation

Chen

et al. 2020

Geofluids

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Wave-induced fluid flow is the main cause of seismic attenuation and dispersion. So the estimated velocity dispersion information can be used to identify reservoir fluid and effectively reduce the risk of reservoir drilling. Using equivalence of dispersion and attenuation between poroelastic and viscoelastic media, we developed the method of FAVO (frequency-dependent amplitude variation with offset) dispersion quantitative estimation based on the analytical solution of 1D viscoelastic wave equation. Compared with the current single-interface velocity dispersion estimation method, the new nonlinear approach uses the analytical solution of 1D viscoelastic wave equation as the forward modeling engine. This method can conveniently handle the attenuation and generate the full-wave field response of a layered medium. First, the compound matrix method (CMM) was applied to rapidly obtain the analytical solution by vectorization. Further, we analyzed the seismic response characteristics through the model data to clarify the effectiveness of the forward modeling method. Then, the more reliable P-wave velocity, S-wave velocity, and density were recovered based on prestack viscoelastic waveform inversion (PVWI). Combining with the inversion results, the derivative matrix was calculated to perform nonlinear velocity dispersion estimation. Finally, the new estimation method was tested with the model and actual data. The experiments show that the developed method is clearly superior to the single-interface dispersion estimation method in accuracy and resolution. This approach can be used as a new choice reservoir fluid identification.

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Frequency-dependent seismic reflection coefficient for discriminating gas reservoirs

Cited by 16 publications

References 18 publications

Thin-layer effects in glaciological seismic amplitude-versus-angle (AVA) analysis: implications for characterising a subglacial till unit, Russell Glacier, West Greenland

Thin-layer effects in glaciological seismic amplitude-versus-angle (AVA) analysis: implications for characterising a subglacial till unit, Russell Glacier, West Greenland

Geomechanical model and wellbore stability analysis utilizing acoustic impedance and reflection coefficient in a carbonate reservoir

Nonlinear FAVO Dispersion Quantification Based on the Analytical Solution of the Viscoelastic Wave Equation

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