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基于频率—慢度域叠前地震记录的合成与并行方法研究
The study of generating prestack synthetic seismograms and its parallel method in frequency-slowness domain
【摘要】 正演模拟是叠前弹性波反演的基础.采用慢度法计算层状介质的叠前地震记录,分别对频率和慢度进行积分变换得到时-空域的地震道集,并对在慢度积分过程中产生的计算噪音提出了解决方案.为得到高精度合成地震记录,需将地层细分,但地层层数很多时,计算量较大;而对地层粗分虽然会大大加快运算速度,但合成记录会丢失很多信息,文中给出了地层的划分原则.该方法能够计算出包括转换波和多次反射在内的全地震响应.但在提高合成记录精度的同时,也导致计算量增大、计算效率降低,因此,本文对基于慢度法全波场模拟进行了并行算法设计,采用计算域分割、工作池并行技术,建立了慢度法全波场正演模拟的并行算法,使得弹性波正演问题求解更加高效,为充分利用叠前地震资料进行叠前反演提供了研究基础.
【Abstract】 Forward modeling is the basis of prestack elastic-wave inversion.The slowness method is adopted to compute the prestack synthetic seismograms in layered medium,and the seismic data gathers in time-space domain can be resulted from integral transformation for frequency and slowness separately.At one time,some means are put forward about computing noise which is generated in the course of slowness integral.Layers need to be fractionized to get high precision synthetic seismograms,whereas its computation complexity is beyond the capability.If Layers are partitioned roughly with accelerating the computing speed,much information of synthetic seismograms will be lost.Thus,partition principle of layers is brought forward.The method could compute a complete seismic response including mode conversions and multiple reflections.However,high precision synthetic seismograms cause to increase massive computation complexity and depress computation efficiency massively.Hence,parallel algorithm of full wave-field forward modeling is designed on the basis of slowness method,which adopts parallel technique of segmenting computation domain and work pool.And,its parallel algorithm is established so that the problem of elastic-wave forward modeling is solved more effectively,making the foundation for prestack inversion with prestack seismic data well for further study.
【Key words】 frequency-slowness domain; prestack synthetic seismograms; slowness method; parallel algorithm design;
- 【文献出处】 地球物理学进展 ,Progress in Geophysics , 编辑部邮箱 ,2007年05期
- 【分类号】P631.4
- 【被引频次】4
- 【下载频次】126