【摘要】 背景噪声地震学利用地震台站记录的背景噪声信号计算台站之间的互相关信息，以此推演地质结构信息，近年来广泛应用于地球结构和油气勘探等领域。地震噪声数据处理往往需要通过预处理计算来减少仪器、地震信号的干扰，这一过程需进行多种信号处理计算。随着我国地震台站布设的推广，地震波形文件持续积累，预处理计算的耗时大大增加。针对计算耗时问题，基于图形处理器异构计算平台，提出了一种并行地震噪声预处理算法。并行算法在台站、时间和分段3个维度设计了并行计算框架，针对预处理中的计算过程实现了计算核函数，并且通过分批计算实现了对大批量文件的自适应处理。实验结果表明，并行预处理算法取得了约95倍的加速比，且具备良好的并行性。更多还原

【Abstract】 Ambient noise seismology uses the ambient noise signals recorded by seismic stations to calculate the cross-correlation between stations, and thereby derive information about geological structures. In recent years, it has been widely used in fields such as Earth structure and oil and gas exploration. Seismic noise data processing often requires preprocessing calculations to reduce interference from instruments and seismic signals, which involves various signal processing calculations. As seismic stations are increasingly deployed in China, the continuous accumulation of seismic waveform files has greatly increased the time required for preprocessing calculations. To address the issue of computational time, a parallel seismic noise preprocessing algorithm has been proposed based on a graphics processing unit(GPU) heterogeneous computing platform. The parallel algorithm designed a parallel computing framework in three dimensions: stations, time, and segments. It implemented computational kernel functions for the calculation process in preprocessing and achieved adaptive processing of large batches of files through batch calculations. Experimental results show that the parallel preprocessing algorithm achieved an acceleration ratio of about 95 times, with good acceleration ratio and parallelism.更多还原