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基于双聚型CFP技术的AVP属性提取

Common Focus Point AVP Attribute Extraction Based on Bifocal Version of CFP Technology

【作者】 蒋雪峰

【导师】 刘成斋; 李振春;

【作者基本信息】 中国石油大学 , 地球探测与信息技术, 2010, 硕士

【摘要】 共聚焦点(CFP)偏移技术是一种基于等时原理,将Kirchhoff积分法的一步偏移分成两步聚焦(即激发聚焦和检波聚焦)来完成的叠前地震成像方法。在CFP偏移中,通过时-空域的零走时成像原理和Radon域的零截距时间成像原理分别实现共聚型的CFP偏移和双聚型的CFP偏移。进而分别实现构造成像和岩性成像。要提取AVP属性,需要通过Radon域零截距时间成像原理实现双聚型CFP偏移。文中共聚型成像的过程中,应用了波场延拓理论来生成共聚焦点(CFP)道集,基于波动方程的傅里叶有限差分法进行了CFP偏移成像,并且结合基于射线理论的CFP偏移技术,利用差异时移分析,相位误差的对称性,实现了速度模型的扫描更新。基于共聚焦点技术进行的AVP属性分析是共聚焦点技术在地震属性分析领域的一个大的突破,在处理实际资料或复杂模型时,对第二步聚焦结果进行滤波处理,以提高反射率函数的质量,并最终应用双聚型CFP偏移方法得到了目标区域各聚焦点的AVP属性。模型试算和实际数据试处理表明了CFP-AVP属性分析方法具有一定的有效性和实用性。

【Abstract】 Common focus point migration technology is a kind of prestack seismic imaging method based on the principle of equal travel time and it separates Kirchhoff integral into two focusing steps. During the common focusing point migration, we can realize the confocal version of CFP migration by the principle of zero traveltime in the time-space domain,and realize the bifocal version of CFP migration by the principle of zero intercept time in the radon domain,and then respectively achieve the structure imaging and lithologic imging. To extract the AVP attribute, It order us use bifocal version of CFP migration is implemented by the zero intercept time imaging principle in Radon domain.During the confocal version of CFP migration process. we create the common focus point gather based on the wavefield continuation theory, and realize the CFP migration applying the Fourier finite difference method which is based on the wave equation. Combining the CFP migration based on the radial theory, we use the differential time shift analysis, symmetry property of phase errors to realize the updating of the velocity model. Using the CFP technology to do the Amplitude Versus P analysis is a big breakthrough in the seismic attribute analysis field, make use of the filter processing to the second focus step, and improve the quality of the reflectivity function, and at last using the bifocal version of CFP migration we get the AVP attribute of the focus points of the target. Tests on model and real data show the validity and the practicability of this CFP-AVP analysis method.

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