纵波方位属性裂缝检测技术综合研究

Fractured oil and gas reservoir is an important type of oil and gas reservoir, which is taking a growing part of current oil and gas production in the whole world. Thus these technologies targeted at exploration of fractured oil and gas reservoirs are drawing vast attentions. It is difficult to accurately predict the fracture development orientation and intensity in oil and gas exploration. Focused on this problem, this paper systematically conducted series study of seismic data processing and P-wave attributes fracture detection based on the structure of ZX buried mountain, and obtained good results. This paper firstly stimulated the propagation of P-wave in weak anisotropic media caused by vertical aligned cracks, and analyzed the rule of P-wave attributes’ variation associated with observed azimuth, such as travel-time, amplitude and AVO gradient and so on, and quantitatively described the sensitive degree of these attributes to anisotropy of fracture medium. In order to further study the sensitive degree of these attributes to anisotropy of fractures, meanwhile, this paper stimulated P-wave propagation through different types and different intensity anisotropic medium respectively and summarized the rule of these attributes’ variation associated with observed azimuth in different anisotropic medium. The results of these studies provided reliable references for predicting orientation, extensity and size of actual complicated cracked medium by P-wave azimuth attributes responses. In the paper, amounts of seismic data processing methods are used to keep and recover all kinds of attributes applied for fracture detection, which guarantee the high accurate of these attributes, thus then improve the accurate of fracture detection. During seismic data processing, the paper adopted the three dimensional F-Kx-Ky field cone filter technique to attenuate ground roll waves and multiple waves, then enhances the S/N ratio of pre-stack seismic data; comprehensively applying geometrical spread compensation, surface consistent amplitude compensation, residual amplitude compensation to recover amplitude; common azimuth processing method effectively preserves the azimuthal characteristics of P-wave attributes; the technique of bend ray adaptive aperture pre-stack time migration insures to obtain the best image in each azimuth. Application of these processing methods guaranteed these attributes’ accuracy, and then improved the accuracy of fracture detection. After comparing and analyzing a variety of attributes, relative wave impedance (relative amplitude) attribute is selected to inverse the orientation of fracture medium; attenuation gradient and corresponding frequency of 85% energy are selected to inverse the intensity of fracture medium; then obtained the fracture distribution characteristics of lower Paleozoic and Precambrian in ZX ancient buried mountains. The results are good accord with the characteristics of faults system and well information in this area.

保重心脉冲压缩滤波及其在速度自动拾取中的应用

To pick velocity automatically is not only helpful to improve the efficiency of seismic data process, but also to provide quickly the initial velocity for prestack depth migration. In this thesis, we use the Viterbi algorithm to do automatic picking, but the velocity picked usually is immoderate. By thorough study and analysis, we think that the Viterbi algorithm has the function to do quickly and effectually automatic picking, but the data provided for picking maybe not continuous on derivative of its curved surface, viz., the curved face on velocity spectrum is not slick. Therefore, the velocity picked may include irrational velocity information. To solve the problem above, we develop a new method to filter signal by performing nonlinear transformation of coordinate and filter of function. Here, we call it as Gravity Center Preserved Pulse Compressed Filter (GCPPCF). The main idea to perform the GCPPCF as follows: separating a curve, such as a pulse, to several subsection, calculating the gravity center (coordinate displacement), and then assign the value (density) on the subsection to gravity center. When gravity center departure away from center of its subsection, the value assigned to gravity center is smaller than the actual one, but non other than gravity center anastomoses fully with its subsection center, the assigned value equal to the actual one. By doing so, the curve shape under new coordinate breadthwise narrows down compare to its original one. It is a process of nonlinear transformation of coordinate, due to gravity center changing with the shape of subsection. Furthermore, the gravity function is filter one, because it is a cause of filtering that the value assigned from subsection center to gravity center is obtained by calculating its weight mean of subsetion function. In addition, the filter has the properties of the adaptive time delay changed filter, owing to the weight coefficient used for weight mean also changes with the shape of subsection. In this thesis, the Viterbi algorithm inducted, being applied to auto pick the stack velocity, makes the rule to integral the max velocity spectrum ("energy group") forward and to get the optimal solution in recursion backward. It is a convenient tool to pick automatically velocity. The GCPPCF above not only can be used to preserve the position of peak value and compress the velocity spectrum, but also can be used as adaptive time delay changed filter to smooth object curved line or curved face. We apply it to smooth variable of sequence observed to get a favourable source data ta provide for achieving the final exact resolution. If there is no the adaptive time delay-changed filter to perform optimization, we can't get a finer source data and also can't valid velocity information, moreover, if there is no the Viterbi algorithm to do shortcut searching, we can't pick velocity automatically. Accordingly, combination of both of algorithm is to make an effective method to do automatic picking. We apply the method of automatic picking velocity to do velocity analysis of the wavefield extrapolated. The results calculated show that the imaging effect of deep layer with the wavefield extrapolated was improved dominantly. The GCPPCF above has achieved a good effect in application. It not only can be used to optimize and smooth velocity spectrum, but also can be used to perform a correlated process for other type of signal. The method of automatic picking velocity developed in this thesis has obtained favorable result by applying it to calculate single model, complicated model (Marmousi model) and also the practical data. The results show that it not only has feasibility, but also practicability.