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PVM based 3-D Kirchhoff depth migration using dynamically computed travel-times: An application in seismic data processing

机译:基于PVM的3-D Kirchhoff深度偏移的动态计算旅行时间:在地震数据处理中的应用

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Seismic depth migration is an image reconstruction technique used to generate realistic images of the Earth's interior from surface recordings of sound waves reflected by buried geological structures. Migration algorithms that have been developed for digitally recorded seismic data are computationally intensive and are typically implemented on massively parallel architecture. In this paper we describe a highly accurate method of computing seismic travel- times and study the feasibility of a PVM-based SPMD parallelization of a migration algorithm based on this method. The parallel algorithm developed in this study is coarse grained and utilizes a simple geometrical decomposition of the input problem. We show that near linear speedup can be achieved on a homogeneous cluster and the algorithm can be ported to a variety of platforms, i.e. clusters of Sun workstations, Cray Y-MP. nCUBE-2, Cray T3E and SGI Origin 2000. The performance of the scheme on different computational platforms ulti- mately depends on a number of different factors, e.g., machine architecture, machine speed, network configuration etc. For a simple test case that was studied in this research, the per- formances of modest PVM clusters were found to be encouraging. This underscores the ad- vantages of adopting a strategy based on parallelizing computationally intensive tasks and also demonstrates the suitability of the travel-time scheme for developing coarsely parallel applications.
机译:地震深度偏移是一种图像重建技术,用于从埋藏的地质结构反射的声波的表面记录中生成地球内部的逼真的图像。为数字记录的地震数据开发的迁移算法计算量大,通常在大规模并行体系结构上实现。在本文中,我们描述了一种计算地震传播时间的高精度方法,并研究了基于PVM的SPMD并行化基于该方法的偏移算法的可行性。在这项研究中开发的并行算法是粗粒度的,并利用了输入问题的简单几何分解。我们展示了可以在同构集群上实现近乎线性的加速,并且该算法可以移植到各种平台上,即Sun工作站集群Cray Y-MP。 nCUBE-2,Cray T3E和SGI Origin2000。该方案在不同计算平台上的性能最终取决于许多不同的因素,例如,机器体系结构,机器速度,网络配置等。在这项研究中进行的研究发现,适度的PVM群集的性能令人鼓舞。这强调了采用基于并行化计算密集型任务的策略的优势,并且还证明了旅行时间方案对开发粗略并行应用程序的适用性。

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