ISSN 1004-4140
CN 11-3017/P
DUAN C X, LIANG Y, FAN X H, et al. Research on high resolution seismic date processing method based on adaptive VMD[J]. CT Theory and Applications, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01. (in Chinese).
Citation: DUAN C X, LIANG Y, FAN X H, et al. Research on high resolution seismic date processing method based on adaptive VMD[J]. CT Theory and Applications, 2022, 31(2): 135-148. DOI: 10.15953/j.1004-4140.2022.31.02.01. (in Chinese).

Research on High Resolution Seismic Date Processing Method Based on Adaptive VMD

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  • Received Date: January 06, 2021
  • Available Online: January 24, 2022
  • Published Date: March 31, 2022
  • With the deepening of exploration and development, due to the limitation of the resolution of the conventional seismic data, it is difficult to meet the needs of exploration and development. Since the attenuation degree of different frequency components of seismic signals is different, the frequency decomposing technology can be applied to perform differential compensation on each frequency component to improve the resolution of seismic data. However, the conventional frequency division technology generally not only holds low frequency division accuracy but also shows modal aliasing, thus it cannot be well applied to seismic data processing. To solve these problems, this paper proposes a high-resolution processing method for seismic data based on adaptive variational modal decomposition (VMD). The multi-objective bat algorithm is applied to the variational modal decomposition, and the VMD parameters are optimized by the fitness function constructed using power spectrum entropy, energy difference, and sample entropy. The model test results show that the optimized VMD method holds high frequency division accuracy and strong anti-noise ability, and also can avoids modal aliasing, When the optimized VMD method is applied to high-resolution processing of seismic data, the model and actual data test results show that the resolution of processed seismic data is effectively improved.
  • [1]
    李振春, 王清振. 地震波衰减机理及能量补偿研究综述[J]. 地球物理学进展, 2007,22(4): 1147−1152.

    LI Z C, WANG Q Z. A review of research on mechanism of seismic attenuation and energy compensation[J]. Progress in Geophysics, 2007, 22(4): 1147−1152. (in Chinese).
    [2]
    周发祥, 宁鹏鹏, 刘斌, 等. 吸收衰减对地震分辨率的影响[J]. 石油地球物理勘探, 2008,43(S2): 84−87.

    ZHOU F X, NING P P, LIU B, et al. Influence of attenuation by absorption on seismic resolution[J]. Oil Geophysical Prospecting, 2008, 43(S2): 84−87. (in Chinese).
    [3]
    严宁, 程梦英. 地震资料处理中信噪比与反褶积的关系探究[J]. 中国石油和化工标准与质量, 2019,39(3): 122−123.
    [4]
    YUAN Y J, LI Y C, ZHOU S C. Multichannel statistical broadband wavelet deconvolution for improving resolution of seismic signals[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 59(2): 1772−1783.
    [5]
    JIANG Y M, CAO S Y, CHEN S Y, et al. A blind nonstationary deconvolution method for multichannel seismic data[J]. Exploration Geophysics, 2021, 52(3): 245−257. doi: 10.1080/08123985.2020.1807319
    [6]
    WANG Y H. Inverse Q-filter for seismic resolution enhancement[J]. Geophysics, 2006, 71(3): V51. doi: 10.1190/1.2192912
    [7]
    LIU G C, LI C, RAO Y, et al. Oriented pre-stack inverse Q filtering for resolution enhancements of seismic data[J]. Geophysical Journal International, 2020, 223(1): 488−501. doi: 10.1093/gji/ggaa329
    [8]
    SANGWAN P, KUMAR D. A robust approach to estimate Q from surface seismic data and inverse Q filtering for resolution enhancement[J]. First Break, 2021, 39(2): 35−43. doi: 10.3997/1365-2397.fb2021009
    [9]
    余锋. 反Q滤波在提高地震资料分辨率中的研究与应用[J]. 能源技术与管理, 2017,42(1): 153−154.
    [10]
    HAO Y J, HUANG H D, GAO J, et al. Inversion-based time-domain inverse Q filtering for seismic resolution enhancement[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(12): 1934−1938. doi: 10.1109/LGRS.2019.2914092
    [11]
    边国柱, 张立群. 地震数据的谱白化处理[J]. 石油物探, 1986,(2): 26−33.

    BIAN G Z, ZHANG L Q. Spectral whitening of seismic data[J]. Geophysical Prospecting for Petroleum, 1986, (2): 26−33. (in Chinese).
    [12]
    LI F, LIU R, LOU Y, et al. Revisit seismic attenuation attributes: Influences of the spectral balancing operation on seismic attenuation analysis[J]. Interpretation, 2021, 9(3): 1−50.
    [13]
    李曙光, 徐天吉, 甘其刚, 等. 频率域小波变换分频处理在川西地震勘探中的应用[J]. 石油物探, 2010,49(5): 500−503.
    [14]
    刘瑞, 何文章, 吴爱弟, 等. 基于多小波变换提高地震数据的分辨率[J]. 数学的实践与认识, 2011,41(20): 43−47.

    LIU R, HE W Z, WU A D, et al. Improving the Resolution ratio of seismic data by multiwavelets transformation[J]. Mathematics in Practice and Theory, 2011, 41(20): 43−47. (in Chinese).
    [15]
    路鹏飞, 郭爱华, 赵宝银, 等. 利用小波分析技术提高老爷庙油田地震资料分辨率[J]. 石油地球物理勘探, 2012,47(2): 272−276.

    LU P F, GUO A H, ZHAO B Y, et al. Seismic data reslution improvement in Laoyemiao by wavelet analysis[J]. Oil Geophysical Prospecting, 2012, 47(2): 272−276. (in Chinese).
    [16]
    余景奎. 提高分辨率处理的几种途径[J]. 特种油气藏, 2005,(5): 38−41.

    YU J K. Several ways of improving resolution[J]. Special Oil and Gas Reservoirs, 2005, (5): 38−41. (in Chinese).
    [17]
    余鹏, 李振春. 分频技术在储层预测中的应用[J]. 勘探地球物理进展, 2006, 29(6): 419-423.

    YU P, LI Z C. Application of frequency-divided technique in reservoir prediction[J]. Progress in Exploration Geophysics. 2006, 29(6): 419-423. (in Chinese).
    [18]
    马朋善, 王继强, 刘来祥, 等. Morlet小波分频处理在提高地震资料分辨率中的应用[J]. 石油物探, 2007,(3): 283−287.

    MA P S, WANG J Q, LIU L X, et al. Application of morlet wavelet frequency-division processing in enhancing the seismic data resolution[J]. Geophysical Prospecting for Petroleum, 2007, (3): 283−287. (in Chinese).
    [19]
    杨忠民, 黄大云. 小波变换在提高资料的信噪比和分辨率中的应用[J]. 石油地球物理勘探, 1994,29(5): 623−629.

    YANG Z M, HUANG D Y. Application of wavelet transform in improving both signal/noise ratio resolution of seimic data[J]. Oil Geophysical Prospecting, 1994, 29(5): 623−629. (in Chinese).
    [20]
    袁修贵, 宋守根, 张建贵, 等. 多分辨迭后地震记录频率振幅补偿方法[J]. 中南工业大学学报(自然科学版), 2001,(3): 224−226.

    YUAN X G, SONG S G, ZHANG J G, et al. Treatment of stacked seismic data with multiresolution frequency-amplitude compensation[J]. Journal of Central South University (Science and Technology), 2001, (3): 224−226. (in Chinese).
    [21]
    刘喜武, 年静波, 刘洪. 基于广义S变换的吸收衰减补偿方法[J]. 石油物探, 2006,(1): 9−14.

    LIU X W, NIAN J B, LIU H. Generalized S-transform based compensation for stratigraphic absorption of seismic attenuation[J]. Geophysical Prospecting for Petroleum, 2006, (1): 9−14. (in Chinese).
    [22]
    孙雷鸣, 万欢, 陈辉, 等. 基于广义S变换地震高分辨率处理方法的改进及在流花11-1油田的应用[J]. 中国海上油气, 2011,23(4): 234−237.

    SUN L M, WAN H, CHEN H, et al. An improved method of seismic high-resolution processing based on generalized S transform and its application in LH11-1 oilfield[J]. China Offshore Oil and Gas, 2011, 23(4): 234−237. (in Chinese).
    [23]
    黄捍东, 冯娜, 王彦超, 等. 广义S变换地震高分辨率处理方法研究[J]. 石油地球物理勘探, 2014,49(1): 82−88.

    HUAN H D, FENG N, WANG Y C, et al. High-resolution seismic processing based on generalized S transform[J]. Oil Geophysical Prospecting, 2014, 49(1): 82−88. (in Chinese).
    [24]
    DRAGOMIRETSKIY K, ZOSSO D. Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531−544. doi: 10.1109/TSP.2013.2288675
    [25]
    何元, 曹思远, 崔震, 等. 变分模态分解及其在地震去噪中的应用[C]//中国地球物理学会, 2014: 1.
    [26]
    徐智, 唐刚, 刘伟, 等. 基于变分模态分解参数优化的地震随机噪声去除方法[J]. 北京化工大学学报(自然科学版), 2019,46(5): 60−68. DOI: 10.13543/j.bhxbzr.2019.05.009.

    XU Z, CAO S Y, LIU W, et al. Seismic random noise removal based on variational mode decomposition with parameter optimization[J]. Journal of Beijing University of Chemical Technology (Natural Science), 2019, 46(5): 60−68. DOI: 10.13543/j.bhxbzr.2019.05.009. (in Chinese).
    [27]
    江馀, 张军华, 韩宏伟, 等. 优化变分模态分解方法消除强反射影响−以东营凹陷沙四段滩坝砂目标处理为例[J]. 石油地球物理勘探, 2020,55(1): 147−152, 166. DOI: 10.13810/j.cnki.issn.1000-7210.2020.01.017.

    JIANG Y, ZHANG J H, HAN H W, et al. Elimination of strong reflection influence based on optimized variational mode decomposition method: A case study of the target processing of beach bar sand of Es4 in Dongying Sag[J]. Oil Geophysical Prospecting, 2020, 55(1): 147−152, 166. DOI: 10.13810/j.cnki.issn.1000-7210.2020.01.017. (in Chinese).
    [28]
    龙丹, 牛聪, 周怀来, 等. 基于VMD算法在地震数据时频分析中的应用[J]. 地球物理学进展, 2020,35(1): 0166−0173. DOI: 10.10.6038/pg2020CC0462.

    LONG D, NIU C, ZHOU H L, et al. Application of VMD algorithm in time-frequency analysis of seimic data[J]. Progress in Geophysics, 2020, 35(1): 0166−0173. DOI: 10.10.6038/pg2020CC0462. (in Chinese).
    [29]
    YANG X S. A new metaheuristic bat-inspired algorithm[M]. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Springer, Berlin, Heidelberg, 2010: 65-74.
    [30]
    YANG X S. Bat algorithm for multi-objective optimisation[J]. International Journal of Bio-Inspired Computation, 2011, 3(5): 267−274. doi: 10.1504/IJBIC.2011.042259
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