不同工作条件下气枪震源产生的信号会存在细微差异，反褶积方法能在一定程度上消除由震源变化引起的记录信号变化。为了去除气枪震源子波信号，获取气枪源到台站之间的格林函数，通常需要选取一种恰当的方法对地震波形数据进行反褶积处理。频率域水准反褶积和时间域迭代反褶积是在接收函数等领域已被广泛使用的2种反褶积方法。本文以云南宾川主动源资料为例，对比了利用这2种方法处理气枪震源信号的效果，结果表明，在计算效率方面，频率域水准反褶积方法更具优势；在处理结果的信噪比方面，时间域迭代反褶积方法表现更好，P波初至也更清晰。此外，进一步讨论了在多炮资料的处理过程中反褶积和叠加等操作的顺序问题，最后提出了从气枪震源资料中提取气枪源到台站之间的格林函数的一般流程。

With its high repeatability，air-gun source has been used to monitor the temporal variations of subsurface structures. However，under different working conditions，there will be subtle differences of the air-gun source signals. To some extent，deconvolution can eliminate changes of the recorded signals due to source variations. Generally speaking，in order to remove the air-gun source wavelet signal and obtain the Green's functions between the air-gun source and stations，we need to select an appropriate method to perform the deconvolution process for seismic waveform data. Frequency domain water level deconvolution and time domain iterative deconvolution are two kinds of deconvolution methods widely used in the field of receiver functions，etc. We use the Binchuan(in Yunnan，China)air-gun data as an example to compare the performance of these two deconvolution methods in air-gun source data processing. The results indicate that frequency domain water level deconvolution is better in terms of computational efficiency；time domain iterative deconvolution is better in terms of the signal to noise ratio(SNR)，and the initial motion of P wave is also clearer. Besides，we further discuss the sequence issue of deconvolution and stack for multiple-shot air-gun data processing. Finally，we propose a general processing flow for the air-gun source data to extract the Green's functions between the air-gun source and stations.

中国地震局公益性行业科研专项(201508008)、中央高校基本科研业务费专项资金(WK2080000053)、云南省陈颙院士工作站专项经费(2014IC007)联合资助