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Frequency Dependent AVO Inversion Using Spectral Decomposition Techniques

Posted on:2011-05-12Degree:DoctorType:Dissertation
Country:ChinaCandidate:X Y WuFull Text:PDF
GTID:1100360308475239Subject:Earth Exploration and Information Technology
Abstract/Summary:PDF Full Text Request
The transmission of seismic waves in porous elastic media saturated with fluids can be described using Gassmann model. Fluid substitution using Gassmann theory lies at the heart of most seismic fluid-detection methods. While Gassmann has proven to provide an excellent approximation, the elastic behaviour of fluid saturated rocks is often frequency-dependent, Considerable effort has been expended on laboratory studies and theoretical investigations with the goal of understanding this frequency dependence. Real seismic data may have this frequency dependence in certain frequency regime due to fluids saturation. It is attractive to try to use this property to discriminate different fluids with seismic data. But this is not accounted for in Gassmann theory and current AVO analysis. Using this frequency dependent property, I integrate modern spectral decomposition and AVO inversion together. First, I study different kinds of spectral decomposition techniques, and then extend Smith & Gidlow (1987)'s two-term approximate formula to frequency domain for frequency dependent AVO inversion. The purpose is to extract the dispersive property from pre-stack reflection data.In the respect of rock physics, classical theories on the transmission of seismic waves in fluids saturated media are summarized including Gassmann theory, Biot theory and BISQ theory. Chapman model for the description of dispersive medium and numerical modeling is outlined in detail. In the respect of theoretical models and real seismic data processing, the development of modern spectral decomposition techniques and its application in the research of seismic wave dispersion. Three methods including Short Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT) and Wigner-Ville Distribution (WVD) based methods are carried out and compared with each other. Eventually CWT and SPWVD is used for synthetic model and real seismic data processing because of their high resolution and fast calculating speed. Based on spectral decomposition methods, a new seismic attribute for the description of seismic dispersion is presented by extending Smith & Gidlow's AVO inversion formula using Taylor series expansion in the frequency domain, and then the derivative of change rate of velocities of P wave and S wave, namely the magnitude of dispersions are obtained using least-squares method. At last, this new method is used for synthetic model and real seismic data processing.The main work and achievement of this thesis contain: (1)Analyze and compare different kinds of spectral decomposition methods including STFT, CWT, as well as WVD based methods. STFT produces time-frequency spectrum by taking Fourier transform over a chosen time window, which leads to a tradeoff between time localization and frequency resolution. Continuous wavelet transform decomposes signals to time-scale domain through stretch and shrink of wavelet function. It possesses high temporal resolution at high frequencies, but Morlet wavelet for seismic signal analysis is not orthogonal wavelet function, which leads to low temporal resolution at low frequencies;(2)Focus on the research of Wigner-Ville distribution based methods. Use smoothed functions in time and frequency domain, namely smoothed pseudo Wigner-Ville distribution (SPWVD) to eliminate the cross-terms in multi-component signal. Discuss the impact for resolution at different smoothed window lengths, and find that giving a length of the zero-phase wavelet to time domain smoothed function and a length of twice as long as the time domain smoothed function to the frequency domain smoothed function, I get higher temporal and frequency resolutions for the processing of synthetic model and real seismic data;(3)Use reassignment algorithm to further enhance the energy concentration in time-frequency domain. This algorithm is able to suppress cross-terms and significantly improve energy concentration simultaneously and has high temporal resolution at low frequencies. But high resolution is at the cost of computational time. It is not suitable for massive seismic data processing. Whereas SPWVD is a "cost-effective" approach, which does not need a large amount of calculation for obtain of higher resolutions than STFT and CWT. Eventually, I use these methods for detection of "low frequency shadow" caused by deep buried gas with post-stack seismic data in west Sichuan Depression and determination of igneous reservoir border in Dagang Oilfield;(4)Present a new frequency dependent seismic attribute for description of seismic dispersion in fluids saturated reservoir. According to Smith & Gidlow's two-term AVO approximate formula, I replace the reflection coefficient with spectral amplitude at different frequencies, and consider spectral amplitude as a function of frequency dependent. And then expand the AVO approximate formula into Taylor series and use the least square inversion for the calculation of derivatives. I derive a set of frequency dependent AVO inversion formula based on modern spectral decomposition techniques. It can be used for quantitative description of magnitude of dispersion of seismic wave;(5)Use Aniseis package to generate ClassⅢAVO synthetic models at elastic case and dispersive case, incorporate CWT and SPWVD for the frequency dependent AVO inversion process of synthetic models. I study the frequency dependent AVO characteristics under different timescale parameter, Crack density, as well as fluid substitution and find that time scaleτbetween 5×10-3s and 5×10-2s gives rise to high seismic dispersion. Seismic wave dispersion is more obvious whenτhas a value of 5×10-3s, whereas dispersion is unconspicuous at low-frequency (τ=10-6s) and high-frequency (τ=100s) cases. For different crack density, higher crack density gives rise to higher magnitude of dispersion of seismic wave;(6)Apply frequency dependent AVO inversion to real seismic data processing; calculate the magnitude of dispersion of two seismic sections in certain oilfield of North Sea. I combine modern spectral analysis techniques with frequency dependent AVO inversion. First, I use SPWVD for post-stack seismic data to find out the frequency anomalies. Then I extract the pre-stack CMP gathers at the location of frequency anomalies for frequency dependent AVO inversion. The result shows that the frequency anomalies caused by elastic interfaces disappear and those caused by dispersive interfaces are reserved. Another advantage of this method is that I get a more reliable result which cannot obtain by only dealing with post-stack seismic data because of the stacking-caused "frequency shadows", rather than the real earth response.The dispersion and attenuation of seismic wave in fractured porous reservoir is a hot and difficult research area in seismic exploration. At present, considerable progress of rock physics modeling has been achieved in describing the characteristics of seismic dispersion. However, there are still certain contradictions between theoretical predictions and actual observations. The theory of seismic wave transmission in fluids saturated media are still being developed and consummated. Fluid-related dispersion and attenuation gives rise to a frequency-dependent reflection coefficient, this thesis extends this idea and deduces Smith & Gidlow's AVO inversion formula to frequency domain, combines spectral decomposition techniques for quantitative description of magnitude of seismic dispersion in reservoirs. But it needs more practical seismic data processing to validate and refine the method and theory.
Keywords/Search Tags:frequency dependent AVO inversion, spectral decomposition, magnitude of dispersion, Wigner-Ville distribution, wavelet transform
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