| 改进的多道预测算子压制浅水多次波方法 |
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| 引用本文： | 周小鹏,刘伊克,李鹏.改进的多道预测算子压制浅水多次波方法[J].地球物理学报,2019,62(2):667-679. |
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| 作者姓名： | 周小鹏 刘伊克 李鹏 |
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| 作者单位： | 1.中国科学院地质与地球物理研究所, 油气资源研究重点实验室, 北京 100029;2.中国科学院大学, 北京 100049;3.中国科学院地球科学研究院, 北京 100029;4.中国石油集团东方地球物理勘探有限责任公司, 河北涿州 072750 |
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| 基金项目： | 国家自然科学基金项目（41730425，41430321）和国家油气重大专项（2017ZX05008-007）联合资助. |
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| 摘 要： | 在浅水情况下,由于观测数据中缺少近偏移距信息,水层多次波的压制面临挑战.利用多道预测算子压制水层多次波是浅水环境下压制多次波的重要方法之一,这种方法先从输入数据中估计出多道预测算子,再将预测算子和输入数据做褶积预测出水层相关多次波.然而,估计的多道预测算子很容易受噪声污染,从而影响多次波模型的精度.所以,我们提出了改进的多道预测算子压制浅水多次波方法.该方法先从数据中估计出多道预测算子,并利用估计的算子构建出精确的水层模型;然后,通过计算算子的走时信息、估计振幅信息、合成新算子三个步骤来修正原始的多道预测算子.修正的算子不仅不受噪声影响,还含有精确的走时信息、可靠的振幅信息;最后,该方法用修正的算子来预测多次波,并结合自适应相减,将预测的多次波从输入数据中去除.通过合成数据和实际资料的验证表明,相比于原始的多道预测算子压制多次波方法,改进的方法能够取得更好的压制效果.
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| 关 键 词： | 浅水 多次波压制 水层多次波 自适应相减 |
| 收稿时间： | 2018-04-23 |
Improved shallow water demultiple method with multichannel prediction operators |
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| ZHOU XiaoPeng,LIU YiKe,LI Peng.Improved shallow water demultiple method with multichannel prediction operators[J].Chinese Journal of Geophysics,2019,62(2):667-679. |
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| Authors: | ZHOU XiaoPeng LIU YiKe LI Peng |
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| Institution: | 1.Key Laboratory of Petroleum Resource Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;2.University of Chinese Academy of Sciences, Beijing 100049, China;3.Institutions of Earth Science, Chinese Academy of Sciences, Beijing 100029, China;4.Research and Develop center of BGP, CNPC, Zhuozhou Hebei 072750, China |
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| Abstract: | Shallow water demultiple faces difficulties because of missing near offsets in the input data. Attenuating water-layer related multiples with multichannel prediction operators has become one of the most important shallow water demultiple techniques. This method first estimates the multichannel prediction operators from the input data, then predicts the water-layer related multiples by convolving the estimated operators with the input data. However, the estimated multichannel prediction operators are easily contaminated with noise, which affects the accuracy of the multiple model. Therefore, we have proposed an improved shallow water demultiple method with multichannel prediction operators. The proposed method first estimates the multichannel prediction operators from the input data as well and constructs an accurate water-layer model; then modifies the estimated operators based on 3 procedures, including calculating the traveltime information of the water-bottom, estimating the waveform information, and constructing the new operators. The modified operators are used to predict the water-layer related multiples. The water-layer related multiple free data can be obtained by adaptively subtracting the predicted multiples from the input data. Numerical examples with a synthetic dataset and a shallow water field dataset show that our proposed method can achieve a superior performance as compared to the method with original multichannel prediction operators. |
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| Keywords: | Shallow water Multiple suppression Water-layer related multiples Adaptive subtraction |
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