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物探与化探  2021, Vol. 45 Issue (1): 127-132    DOI: 10.11720/wtyht.2021.2507
  方法研究·信息处理·仪器研制 本期目录 | 过刊浏览 | 高级检索 |
基于相对熵的时差相位差自动识别校正方法
王东凯1, 苗永康1, 金昌昆1, 周海廷2
1.中国石化胜利油田分公司 物探研究院,山东 东营 257022
2.中国石化胜利油田分公司 勘探开发研究院,山东 东营 257022
Timelag and phaselag automatic recognition and correction method based on relative entropy
WANG Dong-Kai1, MIAO Yong-Kang1, JIN Chang-Kun1, ZHOU Hai-Ting2
1. Geophysical Research Institute of SINOPEC Shengli Oilfield, Dongying 257022, China
2. Shengli Oilfield Exploration and Development Research Institute, Dongying 257022, China
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摘要 

针对地震资料处理中存在的时差、相位差问题,提出了一种时差、相位差自动识别校正方法。该方法以希尔伯特变换和相对熵算法为理论基础,以KL散度为判别准则,全过程数据驱动,自动化实现时差、相位差的识别与校正, 有效降低人工识别成本,避免人为因素带来的误差。文中详细阐述了相关原理及实施过程,并通过数值模拟结果验证了该方法的正确性和有效性。连片、多分量实际资料的应用分析表明,相较于人工识别及理论值校正,该方法可以有效提高识别及校正精度,增强处理对象的一致性,改善剖面质量,为后续处理及解释工作提供技术保障。

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关键词 相对熵时差相位差KL散度    
Abstract Aim

ing at the problem of timelag and phaselag in the processing of seismic data, an automatic recognition and correction (ARC) method is proposed. The method is based on Hilbert transform and relative entropy algorithm. Kullback-Leibler divergence is used as the criterion. The whole process is data driven, and the recognition and correction of timelag and phaselag are realized automatically, which effectively reduces the cost of artificial identification and avoids errors caused by human factors. In this paper, the related principles and implementation process are expounded in detail, and the correctness and effectiveness of the method are verified by numerical simulation results. The application analysis of merged and multi-component actual seismic data shows that compared with manual identification and theoretical value correction, this method can effectively improve the accuracy of recognition and correction, enhance the consistency of events, improve the quality of the sections, and provide technical support for subsequent processing and interpretation.

Key wordsrelative entropy    timelag    phaselag    Kullback-Leibler divergence
收稿日期: 2019-10-30      修回日期: 2020-09-10      出版日期: 2021-02-20
ZTFLH:  P631.4  
基金资助:国家科技重大专项(2017ZX05072);山东省非教育系统公派留学项目——高级科研人才访学计划(201802001)
作者简介: 王东凯(1987-),男,副研究员,现主要从事地震资料处理方法研究工作。
引用本文:   
王东凯, 苗永康, 金昌昆, 周海廷. 基于相对熵的时差相位差自动识别校正方法[J]. 物探与化探, 2021, 45(1): 127-132.
WANG Dong-Kai, MIAO Yong-Kang, JIN Chang-Kun, ZHOU Hai-Ting. Timelag and phaselag automatic recognition and correction method based on relative entropy. Geophysical and Geochemical Exploration, 2021, 45(1): 127-132.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2021.2507      或      https://www.wutanyuhuatan.com/CN/Y2021/V45/I1/127
Fig.1  同步识别校正方法流程
Fig.2  数值模拟验证
a—合成道数据与校正结果;b—相位扫描过程中的KL散度极值曲线;c—A-A相对熵与A-C相对熵曲线对比;d—A-A相对熵与A-D相对熵曲线对比
Fig.3  连片实际资料应用本文方法前(a)后(b)效果对比
Fig.4  多分量实际资料应用本文方法前(a)后(b)效果
Fig.5  校正前后振幅谱曲线
Fig.6  多分量实际资料应用理论值校正(a)与本文方法(b)校正结果对比
[1] 邬达理, 郑伟建, 金晓雷, 等. 复杂三维地震联片处理技术及其应用实例分析[J]. 石油物探, 2001,40(1):9-19.
[1] Wu D L, Zheng W J, Jin X L, et al. Unified seismic data processing of multiple 3D surveys and case study[J]. Geophysical Prospecting for Petroleum, 2001,40(1):9-19.
[2] 王西文, 刘全新, 吕焕通, 等. 相对保幅的地震资料连片处理方法研究[J]. 石油物探, 2006,45(2):105-120.
[2] Wang X W, Liu Q X, Lyu H T, et al. Relative amplitude method to merging processing of 3-D seismic data from multi-area[J]. Geophysical Prospecting for Petroleum, 2006,45(2):105-120.
[3] 云美厚, 丁伟, 王开燕, 等. 地震资料一致性处理方法研究与初步应用[J]. 石油物探, 2006,45(1):65-69.
[3] Yun M H, Ding W, Wang K Y, et al. Study and primary application on consistency processing of seismic data[J]. Geophysical Prospecting for Petroleum, 2006,45(1):65-69.
[4] 刘成斋. 胜利油田三维地震数据连片处理[J]. 石油地球物理勘探, 2004,39(5):579-585.
[4] Liu C Z. Data processing joining serveral 3-D seismic surveying blocks together in Shengli Oilfield[J]. Oil Geophysical Prospecting, 2004,39(5):579-585.
[5] 邬达理. 匹配滤波法在大炮检距资料处理中的应用[J]. 石油物探, 2004,43(6):599-601.
[5] Wu D L. The application of matching filter method in cannon offset data processing[J]. Geophysical Prospecting for Petroleum, 2004,43(6):599-601.
[6] 李继光, 耿林, 顾庆雷, 等. 互相关时差分析技术及其应用——以胜利油田三维地震资料连片处理为例[J]. 石油物探, 2010,49(1):23-29.
[6] Li J G, Geng L, Gu Q L, et al. Crosscorrelation moveout analysis and its application: case study on 3-D multi-surveys merged processing inn Shengli Oilfield[J]. Geophysical Prospecting for Petroleum, 2010,49(1):23-29.
[7] 周兴元. 常相位校正[J]. 石油地球物理勘探, 1989,24(2):119-129.
[7] Zhou X Y. Constant phase correction[J]. Oil Geophysical Prospecting, 1989,24(2):119-129.
[8] 陈必远, 陈明伟, 易维启. 时空变分频常相位校正[J]. 石油地球物理勘探, 1997,32(1):103-108.
[8] Chen B Y, Chen M W, Yi W Q. Time and space and subsection frequency phase correction[J]. Oil Geophysical Prospecting, 1997,32(1):103-108.
[9] 单联瑜, 王希萍, 李振春, 等. 相位校正判别准则的改进及应用效果分析[J]. 石油物探, 2008,47(3):219-224.
[9] Shan L Y, Wang X P, Li Z C, et al. Improvement of discriminant criteria for phase correction and its application effect[J]. Geophysical Prospecting for Petroleum, 2008,47(3):219-224.
[10] Li Z C, Wang X P, Han W G, et al. A review of phase correction techniques in seismic data processing[J]. Progress in Geophysics, 2008,23(3):768-774.
[11] 李强, 尚新民, 赵胜天, 等. 非一致性时移地震资料叠前互约束处理技术[J]. 物探与化探, 2011,35(1):97-102.
[11] Li Q, Shang X M, Zhao S T, et al. Mutual constraint processing technology for inconsistency time lapse seismic data[J]. Geophysical and Geochemical Exploration, 2011,35(1):97-102.
[12] Liu Z D, Lu Q T, Dong S X, et al. Research on velocity and acceleration geophones and their acquired information[J]. Applied Geophysics, 2012,9(2):149-158.
doi: 10.1007/s11770-012-0324-6
[13] 尚新民. 时延地震处理中的近地表静校正技术[J]. 物探与化探, 2014,38(1):162-166.
doi: 10.11720/j.issn.1000-8918.2014.1.30
[13] Shang X M. Static correction in time-lapse seismic data processing[J]. Geophysical and Geochemical Exploration, 2014,38(1):162-166.
[14] 尚新民. 地震资料相位差异分析方法与应用[J]. 物探与化探, 2014,38(4):711-716.
doi: 10.11720/wtyht.2014.4.14
[14] Shang X M. The method and application of seismic data phase difference analysis[J]. Geophysical and Geochemical Exploration, 2014,38(4):711-716.
[15] Kullback S, Leibler R A. On information and sufficiency[J]. The Annals of Mathematical Statistics, 1951,22(1):79-86.
doi: 10.1214/aoms/1177729694
[16] Lamberti P W, Majter A P. Non-logarithmic Jensen-Shannon divergence[J]. Physica A, 2003,329(1-2):81-90.
doi: 10.1016/S0378-4371(03)00566-1
[17] Goodfellow I, Bengio Y, Courville A. Deep learning[M]. Cambridge: MIT Press, 2016, 71-73.
[18] Wang D K, Liu H S, Tong S Y, et al. Ocean-bottom cable data multiple suppression based on equipoise pseudo-multichannel matching filter[J]. Applied Geophysics, 2015,12(2):179-186.
doi: 10.1007/s11770-015-0489-9
[19] 李继光, 王东凯. 海底电缆鬼波压制及陷频补偿方法研究[J]. 热带海洋学报, 2018,37(2):100-104.
[19] Li J G, Wang D K. Research on ghost suppression and notch compensation of dual-sensor ocean bottom cable data[J]. Journal of Tropical Oceanography, 2018,37(2):100-104.
[20] Wang D K, Tong S Y, Liu H S, et al. Notch effect and frequency compensation of dual-sensor OBC data in shallow water[J]. Journal of Earth Science, 2015,26(4):508-514.
doi: 10.1007/s12583-015-0559-2
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