Frequency-dependent AVO Inversion Research Articles

A novel fluid identification method based on a high-precision spectral decomposition method

Abstract Time-frequency decomposition technology is an effective tool for analyzing non-stationary signals. Improving resolution of spectral decomposition techniques is important to extract more useful information from the received signal. The Wigner-Ville distribution (WVD) has been widely applied in seismic signal analysis, it can better analyze seismic signals due to many excellent mathematical properties, but this method has a drawback that cross terms interference exists in the analyzing of multicomponent signals, which severely limits its application. The combination of the complex-domain matching pursuit (CDMP) with this approach effectively solves this problem. However, the conventional CDMP-WVD does not take the influence of the scale parameter on the Morlet wavelet waveform into account, which reduces the time-frequency resolution of CDMP-WVD. Therefore, to correct the defect that the atomic waveforms change only with the frequency parameter, we propose an improved spectral decomposition method ICDMP-WVD that considers the scale parameter. In this study, we first analyze influences of the scale parameter on Morlet wavelet waveform and make the scale parameter a search parameter that improves the computational efficiency and time-frequency resolution of the traditional CDMP-WVD method. Accordingly, the seismic dispersion-dependent attributes are calculated via combing the improved CDMP-WVD algorithm and the frequency-dependent AVO inversion. We adopt a two-step frequency-dependent AVO inversion method to improve the stability of the conventional frequency-dependent AVO inversion. Theoretical data and real data application show that the approach in this study can identify gas reservoirs efficiently and accurately.

PP-Wave Reflection Coefficient Equation for HTI Media Incorporating Squirt Flow Effect and Frequency-Dependent Azimuthal AVO Inversion for Anisotropic Fluid Indicator

PP-Wave Reflection Coefficient Equation for HTI Media Incorporating Squirt Flow Effect and Frequency-Dependent Azimuthal AVO Inversion for Anisotropic Fluid Indicator

Frequency-Dependent AVO Inversion and Application on Tight Sandstone Gas Reservoir Prediction Using Deep Neural Network

Frequency-Dependent AVO Inversion and Application on Tight Sandstone Gas Reservoir Prediction Using Deep Neural Network

A New Fluid Mobility Calculation Method Based on Frequency-Dependent AVO Inversion

Fluid mobility (i.e., permeability to viscosity ratio) is a key parameter that can evaluate the reservoir permeability and delineate the fluid characteristic in hydrocarbon-saturated reservoirs. Based on the asymptotic representation for the frequency-dependent reflections in the fluid-saturated pore-elastic media and frequency-dependent AVO inversion, we propose a novel method for estimating fluid mobility from poststack seismic data. First, we establish the relationship between fluid mobility and frequency-dependent AVO analysis. Then, the fluid mobility is estimated using the theory of frequency-dependent AVO inversion. Tests on synthetic data reveal that the fluid mobility shows excellent imageability for the fluid-saturated reservoirs and can accurately delineate the spatial distribution shape of the gas-saturated reservoir. The application of field data examples demonstrates that the fluid mobility calculated by the proposed method produces less background interferences caused by elastic layers compared with the conventional frequency-dependent fluid indicator. The frequency-dependent fluid mobility takes into account the dispersion features associated with hydrocarbon reservoirs, and it provides a new way to detect the location of hydrocarbon reservoirs and characterize their spatial distribution.

Prediction of sweet spots in tight sandstone reservoirs based on anisotropic frequency-dependent AVO inversion

Abstract The frequency-dependent amplitude-versus-offset (FAVO) method has become a practical method for fluid detection in sand reservoirs. At present, most FAVO inversions are based on the assumption that reservoirs are isotropy, but the application effect is not satisfactory for fractured reservoirs. Hence, we analyse the frequency variation characteristics of anisotropy parameters in tight sandstone reservoirs based on a new petrophysical model, and propose a stepwise anisotropic FAVO inversion method to extract frequency-dependent attributes from prestack seismic field data. First, we combine the improved Brie's law with the fine-fracture model to analyse frequency-dependent characteristics of velocities and Thomsen anisotropy parameters at different gas saturations and fracture densities. Then, we derive an anisotropic FAVO inversion algorithm based on Rüger's approximation formula and propose a stepwise anisotropic FAVO inversion method to obtain the dispersions of anisotropy parameters. Finally, we propose a method that combines the inversion spectral decomposition with the stepwise anisotropy FAVO inversion and apply it to tight sand reservoirs in the Xinchang area. We use P-wave velocity dispersion and anisotropy parameter ε dispersion to optimise favourable areas. Numerical analysis results show that velocity dispersion of the P-wave is sensitive to fracture density, which can be used for fracture prediction in fractured reservoirs. In contrast, anisotropic parameter dispersion is sensitive to gas saturation and can be used for fluid detection. The seismic data inversion results show that velocity dispersion of the P-wave and anisotropic parameter dispersion are sensitive to fractured reservoirs in the second member of Xujiahe Group, which is consistent with logging interpretation results.

Fluid identification and effective fracture prediction based on frequency-dependent AVOAz inversion for fractured reservoirs

Fluid and effective fracture identification in reservoirs is a crucial part of reservoir prediction. The frequency-dependent AVO inversion algorithms have proven to be effective for identifying fluid through its dispersion property. However, the conventional frequency-dependent AVO inversion algorithms based on Smith & Gidlow and Aki & Richards approximations do not consider the acquisition azimuth of seismic data and neglect the effect of seismic anisotropic dispersion in the actual medium. The aligned fractures in the subsurface medium induce anisotropy. The seismic anisotropy should be considered while accounting for the seismic dispersion properties through fluid-saturated fractured reservoirs. Anisotropy in such reservoirs is frequency-related due to wave-induced fluid-flow (WIFF) between interconnected fractures and pores. It can be used to identify fluid and effective fractures (fluid-saturated) by using azimuthal seismic data via anisotropic dispersion properties. In this paper, based on Rüger's equation, we derived an analytical expression in the frequency domain for the frequency-dependent AVOAz inversion in terms of fracture orientation, dispersion gradient of isotropic background rock, anisotropic dispersion gradient, and the dispersion at a normal incident angle. The frequency-dependent AVOAz equation utilizes azimuthal seismic data and considers the effect of both isotropic and anisotropic dispersion. Reassigned Gabor Transform (RGT) is used to achieve high-resolution frequency division data. We then propose the frequency-dependent AVOAz inversion method to identify fluid and characterize effective fractures in fractured porous reservoirs. Through application to high-qualified seismic data of dolomite and carbonate reservoirs, the results show that the method is useful for identifying fluid and effective fractures in fluid-saturated fractured rocks.

Fluid discrimination incorporating viscoelasticity and frequency-dependent amplitude variation with offsets inversion

Frequency-dependent amplitude versus offset (FAVO) inversion is a popular method to estimate the frequency-dependent elastic parameters by using amplitude and frequency information of pre-stack seismic data to guide fluid identification. Current frequency-dependent AVO inversion methods are mainly based on elastic theory without the consideration of the viscoelasticity of oil/gas. A fluid discrimination approach is proposed in this study by incorporating the viscoelasticity and relevant FAVO inversion. Based on viscoelastic and rock physics theories, a frequency-dependent viscoelastic solid-liquid decoupling fluid factor is initially constructed, and its sensitivity in fluid discrimination is compared with other conventional fluid factors. Furthermore, a novel reflectivity equation is derived in terms of the viscoelastic solid-liquid decoupling fluid factor. Due to the introduction of viscoelastic theory, the proposed reflectivity is related to frequency, which is more widely applicable than the traditional elastic reflectivity equation directly derived from the elastic reflectivity equation on frequency. Finally, a pragmatic frequency-dependent inversion method is introduced to verify the feasibility of the equation for frequency-dependent viscoelastic solid-liquid decoupling fluid factor prediction. Synthetic and field data examples demonstrate the feasibility and stability of the proposed approach in fluid discrimination.

Anisotropic frequency-dependent characteristics of PP- and PS-waves in partially saturated double-porosity rocks

AbstractMost frequency-dependent AVO inversions are currently based on an approximate equation derived using an isotropic medium. However, actual reservoirs usually show anisotropy, such as shale reservoirs, tight sandstone reservoirs and fractured reservoirs. We propose a joint frequency-dependent AVO (JFAVO) inversion in an anisotropic medium based on a periodic layered double-porosity medium. This JFAVO will allow us to quantitatively study the influence of fluids on the dispersion of PP- and PS-wave velocities and anisotropic parameters. First, we used a double-porosity medium to analyse the frequency-dependent characteristics of velocities and anisotropy parameters. We found that the anisotropic parameters show obvious dispersions, similar to those of velocities. Then, we derived the JFAVO inversion based on Rüger's equation to extract the dispersion of velocities and anisotropic parameters. Finally, we analysed the stability and applicability of the inversion algorithm, and used three sets of models to analyse the sensitivity of dispersion properties to fluids. The numerical analysis results show that PP-wave velocity dispersion and anisotropic parameter δ dispersion are sensitive to fluids, whereas, the velocity dispersion of the PS-wave is not. When saturation exceeds 80%, the velocity dispersion and anisotropic parameter dispersion properties are not sensitive to fluids.

Rock Physical Modeling and Seismic Dispersion Attribute Inversion for the Characterization of a Tight Gas Sandstone Reservoir

Gas identification using seismic data is challenging for tight gas reservoirs with low porosity and permeability due to the complicated poroelastic behaviors of tight sandstone. In this study, the Chapman theory was used to simulate the dispersion and attenuation caused by the squirt flow of fluids in the complex pore spaces, which are assumed to consist of high aspect-ratio pores (stiff pores) and low aspect-ratio microcracks (soft pores). The rock physics modeling revealed that as the gas saturation varies, P-wave velocity dispersion and attenuation occurs at seismic frequencies, and it tends to move to high frequencies as the gas saturation increases. The velocity dispersion of the tight gas sandstone causes a frequency-dependent contrast in the P-wave impedance between the tight sandstone and the overlying mudstone, which consequently leads to frequency-dependent incidence reflection coefficients across the interface. In the synthetic seismic AVO modeling conducted by integrating the rock physics model and the propagator matrix method, the variations in the amplitudes and phases of the PP reflections can be observed for various gas saturations. The tests of the frequency-dependent AVO inversion of these synthetic data revealed that the magnitude of the inverted P-wave dispersion attribute can be used to indicate gas saturation in tight sandstone reservoirs. The applications of the frequency-dependent AVO inversion to the field pre-stacked seismic data revealed that the obtained P-wave dispersion attribute is positively correlated with the gas production from the pay zone at the well locations. Thus, the methods of the rock physics modeling and the frequency-dependent AVO inversion conducted in this study have good potential for the evaluation of the gas saturation in tight gas sandstone reservoirs.

Study of seismic attributes recognition method of high quality igneous rock reservoir

Aimed target area is deeply buried, complex lithology, dual media, reservoir development degree is controlled by a variety of factors, meanwhile, lateral thickness and lithofacies change rapidly, and strata formation is poor. Therefore, igneous rock reservoir has difficulty in predicting, since seismic is complicated to track trace, reservoir attribute analysis is hard to determine the time window, and inversion modeling requires sophisticated. By analyzing, the basalt in the target research area accounts for the principal component of the igneous rock, however, the igneous rocks with relatively developed reservoirs are mostly distributed in the trachyte breccia which has good productivity. The results of petrophysical study indicate that frequency-dependent AVO inversion method is an important means to identify fluid and reservoir prediction, notwithstanding it is difficult to distinguish high-quality reservoirs barely by P-wave impedance. Consequently, AVOF inversion method is appropriately proposed to identify igneous rock reservoir. Foremost, eliminating the effects of algorithm,frequency, spectrum balancing and other factors, then put the improved three-term Aki&Richards frequency-dependent AVO inversion method applying to distinguish igneous reservoir fluid and lithology, for the purpose of carrying out the identification of high-quality reservoirs.

Fluid Discrimination Based on Frequency-Dependent AVO Inversion with the Elastic Parameter Sensitivity Analysis

Fluid discrimination is an extremely important part of seismic data interpretation. It plays an important role in the refined description of hydrocarbon-bearing reservoirs. The conventional AVO inversion based on Zoeppritz’s equation shows potential in lithology prediction and fluid discrimination; however, the dispersion and attenuation induced by pore fluid are not fully considered. The relationship between dispersion terms in different frequency-dependent AVO equations has not yet been discussed. Following the arguments of Chapman, the influence of pore fluid on elastic parameters is analyzed in detail. We find that the dispersion and attenuation of Russell fluid factor, Lamé parameter, and bulk modulus are more pronounced than those of P-wave modulus. The Russell fluid factor is most prominent among them. Based on frequency-dependent AVO inversion, the uniform expression of different dispersion terms of these parameters is derived. Then, incorporating the P-wave difference with the dispersion terms, we obtain new P-wave difference dispersion factors which can identify the gas-bearing reservoir location better compared with the dispersion terms. Field data application also shows that the dispersion term of Russell fluid factor is optimal in identifying fluid. However, the dispersion term of Russell fluid factor could be unsatisfactory, if the value of the weighting parameter associated with dry rock is improper. Then, this parameter is studied to propose a reasonable setting range. The results given by this paper are helpful for the fluid discrimination in hydrocarbon-bearing rocks.

An Improved Scheme of Frequency-Dependent AVO Inversion Method and Its Application for Tight Gas Reservoirs

AVO inversion is a seismic exploration methodology used to predict the earth’s elastic parameters and thus rocks and fluid properties. It is built up on elastic theory and does not consider the seismic dispersion in real strata. Recent experiments and theory of rock physics have shown that in hydrocarbon-bearing rocks, especially in gas-bearing ones, the change of seismic velocity with frequency may be pretty remarkable for fluid flow in pore space. Some scholars proposed methods about seismic dispersion, such as frequency-dependent AVO inversion, to forecast oil and gas reservoirs underground. In this paper, we demonstrate an improved scheme of frequency-dependent AVO inversion, which is based on conventional Smith-Gidlow’s AVO equation, to extract seismic dispersion and predict the hydrocarbon underground. A simple model with gas-bearing reservoir is devised to validate the inversion scheme, and further analysis indicates that our scheme is more accurate and reasonable than the previous scheme. Our new scheme applied to the tight gas reservoirs in Fenggu area of western Sichuan depression of China finds that regions with high dispersion gradients correlate well with regions with prolific gas. Analysis and case studies show that our scheme of frequency-dependent AVO inversion is an efficient approach to predict gas reservoirs underground.

Using frequency-dependent AVO inversion to predict the “sweet spots” of shale gas reservoirs

Abstract Shale gas is an unconventional hydrocarbon resource with huge potential. Using geophysical methods to predict “sweet spots” is the key to commercial exploration of shale gas. At present AVO technology is one of most widely used geophysical techniques to find shale gas reservoirs with high abundance. However, the effects of the dispersion of actual mediums are neglected by conventional AVO inversion. Recent experiments have shown that in gas-bearing strata, the dispersion may be rather remarkable. In this paper, we develop a frequency-dependent AVO inversion scheme, which includes seismic dispersion in real rock medium, to predict the “sweet spots” of shale gas reservoirs. Application of the inversion has been made to the shale gas in the south of Jiaoshiba area to test the validity. Comparing the results of the frequency-dependent AVO inversion and well production, we find that regions with high dispersion gradients correlate well with places with high production of shale gas. Therefore we conclude that the frequency-dependent AVO may be a workable approach to detect the “sweet spots” of shale gas reservoirs.

Hydrocarbon identification by application of improved sparse constrained inverse spectral decomposition to frequency-dependent AVO inversion

Spectral decomposition based on sparse constrained inversion, as proposed in recent years, is a high-resolution time-frequency domain analysis method. However, the traditional inverse spectral decomposition (ISD) algorithm is based on an inverse wavelet transform (IWT) whose mother wavelet is a Ricker wavelet function instead of an adaptive wavelet, which causes poor continuity and instability of the ISD results. In this paper, we have extended ISD into other linear transforms and have developed an ISD based on inverse S transform (ISD-IST), which has higher continuity and stability due to the more adjustable and adaptable mother wavelet of the S transform. Comparison of conventional methods and the ISD-IST shows that the ISD (ISD-IWT and ISD-IST) methods have higher resolution and accuracy and can provide more reliable time-frequency phase spectra, and it further verifies the greater continuity and stability of ISD-IST over ISD-IWT. Frequency-dependent AVO (FAVO) inversion is regarded as a potential hydrocarbon identification technique (Wilson et al 2009 SEG Technical Program Expanded Abstracts pp 341–5). However, it is frequency-decomposition based, which means that inversion results can be greatly affected by the effect of time-frequency analysis (Wu et al 2010 SEG Technical Program Expanded Abstracts pp 425–9; Wu et al 2014 Geophys. Prospect. 62 1224–37). Combining the FAVO inversion and high-resolution time-frequency decomposition ISD allows better dispersion attributes to be obtained. Results from application in Southwest China demonstrate that the high frequency-resolution of ISD is helpful in the extraction of gas-induced frequency anomalies from post-stack data, and its high time-resolution helps to obtain high time-resolution gas-induced dispersion results from FAVO inversion. The results of FAVO-ISD not only agree better with well information, but also supply more credible boundary information for the reservoirs. ISD-IST can provide more continuous results and smoother boundary information for the gas reservoir than ISD-IWT.

Numerical Analysis of Velocity Dispersion in Multi-Phase Fluid-Saturated Porous Rocks

Seismic waves are subject to velocity dispersion when they propagate in fluid-saturated porous media. In this work, we explore the velocity dispersion behavior of P- and SV-waves in multi-phase fluid-saturated porous reservoirs while taking into account the effects of multi-phase pore fluids on the effective viscosities that control the wave-induced fluid flow. The effective viscosities associated with the hydrocarbon saturation of a synthetic sandstone reservoir saturated with different pore fluid mixtures are calculated using the Refutas model. We then analyze the frequency-dependent velocity, dispersion variation rate and characteristic frequency for different fluid saturation cases by employing Chapman’s dynamic equivalent-medium theory. The results demonstrate that the hydrocarbon proportions and types in multi-phase mixed pore fluids significantly affect the magnitude and characteristic frequencies of velocity dispersion features for both the P- and S-waves. The dispersion anomalies of SV-waves are in general larger than those of the P-waves. This indicates that the velocity dispersion anomalies of SV-waves are equally sensitive to fluid saturation as the P-waves and should not be neglected. The velocities at lower frequencies (e.g., 10 and 100 Hz) within the seismic frequency range show a more remarkable decrease with increasing hydrocarbon proportion than those at higher frequency (1000 Hz). The numerical examples help to improve the understanding of the frequency-dependent AVO inversion from seismic reflection data.

Carbonate reservoirs dominated by secondary storage space: Key issues and technical strategy

Carbonate reservoirs of the Tarim Basin in China are buried deeply, with strong later diagenesis, and seldom are controlled by geologic facies. The effective storage spaces are mainly dissolution caves and fractures with few primary pores. Fluid distribution in the reservoir is extremely complicated. All these characteristics make it a world-class challenge for oil and gas exploration and production. Conventional poststack methods ignore the complexity of the reservoir medium with low accuracy of prediction results, by which the location of the dissolution cave is determined roughly. Only faults and fracture zones can be described to a certain degree instead of quantifying the fracture detection. Aiming at the key problems of the complex carbonate reservoirs in the Tarim Basin, a series of techniques has been developed to improve the successful rate of reservoir prediction, including the following aspects: the wide-azimuth and high-density data-acquisition technique to improve the quality of the original seismic data; a series of migration techniques including prestack reverse time migration; and amplitude-preserved Q migration to improve the quality of seismic gathers and the imaging precision with the matching precision of AVO gathers. The target reservoir data dominant frequency increased by more than 15% and by nearly 20 Hz. In addition, the effective DEM-Gassmann rock-physics model is proposed for velocity prediction, by which relative error of estimated shear-wave velocity reaches to less than 5%. Furthermore, an advanced inversion algorithm is introduced to improve the accuracy of extracted elastic information. By using new prestack inversion and frequency-dependent AVO inversion, the tie rate of the dissolution-cave reservoir and fluid prediction increased by more than 15%. Furthermore, the fracture-prediction tie rate can be enhanced by 20% through limited-azimuth anisotropic inversion, on the basis of which the quantitative identification of fracture fluid for actual seismic data can be realized.