Yin Xingyao

Research on seismic fluid identification driven by rock physics

Seismic fluid identification works as an effective approach to characterize the fluid feature and distribution of the reservoir underground with seismic data. Rock physics which builds bridge between the elastic parameters and reservoir parameters sets the foundation of seismic fluid identification, which is also a hot topic on the study of quantitative characterization of oil/gas reservoirs. Study on seismic fluid identification driven by rock physics has proved to be rewarding in recognizing the fluid feature and distributed regularity of the oil/gas reservoirs. This paper summarizes the key scientific problems immersed in seismic fluid identification, and emphatically reviews the main progress of seismic fluid identification driven by rock physics domestic and overseas, as well as discusses the opportunities, challenges and future research direction related to seismic fluid identification. Theoretical study and practical application indicate that we should incorporate rock physics, numerical simulation, seismic data processing and seismic inversion together to enhance the precision of seismic fluid identification.

Dispersion-dependent attribute and application in hydrocarbon detection

Previous work has demonstrated that seismic velocity dispersion is often related to a hydrocarbon-saturated reservoir with a high value of attenuation. The velocity dispersion properties can be used as new hydrocarbon indicators if they can be estimated quantitatively from seismic data. In this context, based on the assumption that the reflection coefficient of the interface between dispersive media varies with frequency, we propose an approximation of the reflection coefficient which involves the dispersion-dependent attributes indicating the level and gradient of P-wave velocity dispersion. We develop a new generalization of an AVO inversion scheme to extract the dispersion-dependent attributes from multi-frequency prestack seismic data obtained by the Morlet wavelet decomposition method. The method test and real application show that the dispersion-dependent attributes have the potential to be useful in the discrimination of hydrocarbon accumulation. However, the hydrocarbon detection quality of the dispersion-dependent attributes can be degraded by the inverse Q-filtering procedure which compensates the high-frequency amplitudes.

Predicting oil and gas reservoir and calculating thickness of reservoir from seismic data using neural network

Neural networks have been developed and widely used in oil and gas exploration. Combining the neural networks with traditional seismic prospecting methods, we put forward a new method to predict oil and gas reservoirs and calculate the thickness of the reservoirs. This method is applied in oilfields and the results are satisfactory.

Application of wavelet analysis in distinguishing seismic sequence

Wavelets are a relatively recent development in applied mathematics. With the local time-frequency of wavelet transforms, we can deal much more with the signal reflected by thin-mutual strata. Therefore, we have put forward a method to distinguish the seismic sequence using the wavelet analysis theory. Through the seismic sequence analysis using wavelet transforms, we can obtain vertical and horizontal phase profiles from real seismic data. We will distinguish deposition cycle and material components in the vertical phase profile, and compare and track deposition sequence and structure interface horizontally in the horizontal phase profile.

Noise suppressing by wavelet transform in seismic data processing

This paper gives a new approach to suppress noise in seismic data. According to the time-frequency local characteristics of wavelet transform and the optimal filtering characteristics of KL transform, we have advanced this approach. On the basis of the fact that the noise energy is different from reflection energy in each frequency range, prestack seismic data is divided into different frequency band by wavelet transform first, and then it is filtered by KL transform. Synthetic and real data processing results show that the method can desirably eliminate noise.

Approximate PP Reflection Coefficient in TTI Media

The transversely-isotropic (TI) media is the most common anisotropic media in sedimentary rock. When formations rotate, because of folding and thrusting, the symmetry axis of TI media is tilted instead of vertical or horizontal, which yields so-called transversely-isotropic (TTI) media with tilted symmetry axis. In this paper, based on plane wave theory, we derived the exact and approximate expressions of reflection coefficient of plane waves in two elastic TTI media under welded contact condition by generalizing the expressions of Aki and Richards, and Ruger. Based on displacement wave function, we established the Zeoppritz equation for incident qP wave in TTI media using boundary conditions of displacement continuity and strain continuity. According to weak anisotropy approximation and the theory of media decomposition, we derived the approximate reflection coefficient for incident qP wave in TTI media. The expressions have definite geophysical meanings and higher accuracy. The approximate expression of PP reflection coefficient indicates that VTI has no influence on its intercept, but has influence on the gradient, while TTI has influence on both the intercept and gradient. Keyword: TTI media, reflection coefficient, weak anisotropy approximation, AVO

Estimation of porosity and saturation by Markov Chain Monte Carlo prestack seismic inversion

Porosity and saturation are important parameters to describe the reservoir properties. Here, we develop a method to inverse porosity and saturation within a Bayesian framework using Markov Chain Monte Carlo (MCMC) method. First, we discuss the changes of P-wave velocity, S-wave velocity, density due to changes in porosity and saturation. Then, we build a three-layer model to do the inversion making use of the full Knott-Zoeppritz equation to get the seismic AVO data. The advantages of MCMC methods are: (1) the accuracy of solution is improved with the prior information joined in, and the uncertainty is greatly reduced; (2) solving the nonlinear problem directly, so the process of inversion is to do the seismic forward in each iteration; (3) the dependence of results and initial values is not strong, because the algorithm are not use the objective function with a single optimal solution; (4) optimization process can jump out of local optimum, and ultimately obtain the global optimal solution. By testing a layered model, shows the MCMC method based on Metropolis-Hastings algorithm is available and can obtain good results by random searching solution space.

Using Wavelet Transform to Extract Seismic Attributes

Seismic attributes have been widely used since their introduction and have already become a valid analytical tool for lithology prediction and reservoir characterization; wavelet transform based on the matching pursuit analysis approach using a specific type of Gabor-atoms, it can extract useful seismic attributes that reflect reservoir property, and can be used to divide favorable reservoir area; model and real data application shows that the proposed method is simple and effective and can be easily used