时频分析技术在蓬莱气区深层高频噪声压制中的应用

doi:10.11720/wtyht.2025.2533

Abstract
Figure/Table
References
Related Citation (12)

Download: PDF (7721 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

Seismic waves, particularly their high-frequency components, will undergo energy attenuation during subsurface propagation. This results in a low signal-to-noise ratio (SNR) within the high-frequency band, significantly reducing the accuracy of seismic exploration for deep oil and gas. To enhance the SNR of deep seismic data, this study employed the time-frequency analysis technique to describe the time variations of signal frequency based on the non-stationary characteristics of seismic signals. Accordingly, this study proposed a method for suppressing deep high-frequency noise based on time-frequency analysis. Considering the stable and similar time-frequency characteristics of effective signals and the uncertain and random high-frequency interference, this study proposed an adaptive threshold selection strategy based on correlation analysis. This strategy involves extracting the time-frequency characteristics of effective signals from an advantageous frequency band and comparing them with the time-frequency characteristics within the high-frequency band. Subsequently, feature-constrained attenuation was applied to time-frequency spectra in the high-frequency band, thereby suppressing high-frequency noise. Theoretical models and actual data processing results demonstrate that the proposed method can effectively suppress high-frequency noise and significantly enhance the SNR of deep seismic data.

Key words： signal-to-noise ratio (SNR) high-frequency noise time-frequency analysis feature-constrained deep oil and gas Penglai gas area

Received: 12 December 2023 Published: 07 August 2025

ZTFLH:

P631.4

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Song HAN
	Cong TANG
	Xuan ZHANG
	Ming ZENG
	Hao-Tian PENG
	Wen-Zheng LYU
	Zhi-Hui TU
	Ke-Rui LI
	Hai-Hua ZHU

Cite this article:

Song HAN,Cong TANG,Xuan ZHANG, et al. Application of time-frequency analysis in the suppression of deep high-frequency noise in the Penglai gas area[J]. Geophysical and Geochemical Exploration, 2025, 49(4): 888-895.

URL:

https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2025.2533 OR https://www.wutanyuhuatan.com/EN/Y2025/V49/I4/888

The typical frequency divided profile of deep noise in the gas exploration area

Comparison of noise reduction effect of typical single shot curvelet transform with deep noise in expansive gas exploration area

Schematic of high-frequency noise suppressing method by time-frequency analysis

Test of theoretical model

Analysis of raw seismic trace deniosing by time-frequency method

Comparison of record denoising by conventional denoising and time-frequency method

Stack profile comparison denoised by conventional denoising and time-frequency method

[1]	石昕, 戴金星, 赵文智. 深层油气藏勘探前景分析[J]. 中国石油勘探, 2005, 10(1):1-10,1.
[1]	Shi X, Dai J X, Zhao W Z. Analysis of deep oil and gas reservoirs exploration prospect[J]. China Petrleum Exploration, 2005, 10(1):1-10,1.
[2]	杨雨, 文龙, 宋泽章, 等. 川中古隆起北部蓬莱气区多层系天然气勘探突破与潜力[J]. 石油学报, 2022, 43(10):1351-1368,1394.
[2]	Yang Y, Wen L, Song Z Z, et al. Breakthrough and potential of natural gas exploration in multi-layer system of Penglai gas area in the north of central Sichuan paleo-uplift[J]. Acta Petrolei Sinica, 2022, 43(10):1351-1368,1394.
[3]	张自力, 乔艳萍, 豆霜, 等. 四川盆地蓬莱气区震旦系灯影组二段岩溶古地貌与控储模式[J]. 石油与天然气地质, 2024, 45(1):200-214.
[3]	Zhang Z L, Qiao Y P, Dou S, et al. Karst paleogeomorphology and reservoir-controlling model of the second member of Sinian Dengying Formation in Penglai gas area,Sichuan Basin[J]. Oil & Gas Geology, 2024, 45(1):200-214.
[4]	于常青, 杨午阳, 杨文采. 关于油气地震勘探的基础研究问题[J]. 岩性油气藏, 2007, 19(2):117-120.
[4]	Yu C Q, Yang W Y, Yang W C. About basic research of petroleum seismic prospecting[J]. Lithologic Reservoirs, 2007, 19(2):117-120.
[5]	杨德宽, 郑泽继, 胡立新, 等. 对深层地震勘探中随机噪声的一点认识[J]. 石油物探, 2000, 39(3):50-61,72.
[5]	Yang D K, Zheng Z J, Hu L X, et al. Some cognitions on random noise in deep-layer seismic exploration[J]. Geophysical Prospecting for Petrole, 2000, 39(3):50-61,72.
[6]	朱伟强, 李卫忠, 王成礼, 等. 济阳坳陷深层地震资料处理技术及应用[J]. 石油物探, 2002, 41(2):161-168.
[6]	Zhu W Q, Li W Z, Wang C L, et al. Technology and application of deep seismic data processing in Jiyang Depression[J]. Geophysical Prospecting for Petroleum, 2002, 41(2):161-168.
[7]	刘建芳, 华伟, 王士昆, 等. 江苏低信噪比地区深层地震资料处理方法研究[J]. 石油物探, 2008, 47(6):583-587,18.
[7]	Liu J F, Hua W, Wang S K, et al. Deep seismic data processing method used in low S/N ratio area of Jiangsu oilfield[J]. Geophysical Prospecting for Petroleum, 2008, 47(6):583-587,18.
[8]	孙文涵. 深层地震资料噪声压制与衰减补偿方法研究[D]. 青岛: 中国石油大学(华东), 2020.
[8]	Sun W H. Research on noise suppression and attenuation compensation methods for deep seismic data[D]. Qingdao: China University of Petroleum (East China), 2020.
[9]	宗涛, 孟鸿鹰, 贾玉兰, 等. 小波包f-x域前后向预测去噪[J]. 地球物理学报, 1998, 41(S1):337-346.
[9]	Zong T, Meng H Y, Jia Y L, et al. Denoising method based on wavelet packet and forward-backward prediction in f-x domain[J]. Chinese Journal of Geophysics, 1998, 41(S1):337-346.
[10]	刘葵, 刘招君, 朱建伟, 等. 时频分析在石油地球物理勘探中的应用[J]. 世界地质, 2000, 19(3):282-285.
[10]	Liu K, Liu Z J, Zhu J W, et al. Application of time-frequency analysis in geology[J]. World Geology, 2000, 19(3):282-285.
[11]	邹文, 陈爱萍, 顾汉明. 联合时频分析技术在地震勘探中的应用[J]. 勘探地球物理进展, 2004(4):246-250,259.
[11]	Zou W, Chen A P, Gu H M. Joint time-frequency analysis and its application in seismic prospecting[J]. Progress in Exploration Geophysics, 2004(4):246-250,259.
[12]	M 波特诺夫. 基于短时傅里叶分析的数字信号和系统的时频表示[J]. IEEE: 声学、语音和信号处理,1980.
[12]	Portnoff M. Time-frequency represent-ation of digital signals and systems based on short-time Fourier analysis[J]. IEEE: Acoustics, Speech and Signal Processing,1980.
[13]	施倩, 陈大鹏. 联合时频分析[J]. IEEE:信号处理,1999.
[13]	Qian S, Chen D P. Time-frequency analysis[J]. IEEE:Signal Processing Magazine,1999.
[14]	杨海涛, 朱仕军, 杨爱国, 等. S变换时变滤波在去噪处理中的应用研究[J]. 西南石油大学学报:自然科学版, 2009, 31(6):56-58,208.
[14]	Yang H T, Zhu S J, Yang A G, et al. Application research on time variable filtering with S-transform in denoising processing[J]. Journal of Southwest Petroleum University:Science & Technology Edition, 2009, 31(6):56-58,208.
[15]	李军华. 基于小波变换理论的地震资料去噪方法研究及应用[J]. 能源技术与管理, 2017, 42(5):175-177.
[15]	Li J H. Research and application of seismic data denoising method based on wavelet transform theory[J]. Energy Technology and Management, 2017, 42(5):175-177.
[16]	韦红, 白清云, 张鹏志, 等. 基于反褶积广义S变换的双相介质理论油水识别法在渤海S油田馆陶组的应用[J]. 物探与化探, 2021, 45(6):1394-1401.
[16]	Wei H, Bai Q Y, Zhang P Z, et al. The application of seismic oil-water identification method to Guantao Formation of Bohai S oil field[J]. Geophysical and Geochemical Exploration, 2021, 45(6):1394-1401.
[17]	张金强. 基于正则化理论的时频分析方法及应用[J]. 物探与化探, 2023, 47(4):965-974.
[17]	Zhang J Q. A regularization theory-based method for time-frequency analysis and its applications[J]. Geophysical and Geochemical Exploration, 2023, 47(4):965-974.
[18]	李雪英, 孙丹, 侯相辉, 等. 基于广义S变换、经验模态分解叠前去噪方法的比较[J]. 地球物理学进展, 2011, 26(6):2039-2045.
[18]	Li X Y, Sun D, Hou X H, et al. Comparison of generalized S transform and empirical mode decomposition in high frequency seismic noise suppression[J]. Progress in Geophysics, 2011, 26(6):2039-2045.
[19]	胡瑞卿, 何俊杰, 李华飞, 等. 时频域变分模态分解地震资料去噪方法[J]. 石油地球物理勘探, 2021, 56(2):257-264,210.
[19]	Hu R Q, He J J, Li H F, et al. Seismic data de-noising method based on VMD in time-frequency domain[J]. Oil Geophysical Prospecting, 2021, 56(2):257-264,210.
[20]	邵丹, 李桐林, 韩立国, 等. 基于时频分析与分数阶最优控制网络的地震数据噪声压制[J]. 地球物理学报, 2023, 66 (4):1718-1731.
[20]	Shao D, Li T L, Han L G, et al. Noise suppression of seismic data based on time-frequency analysis and fractional order optimal control network[J]. Chinese Journal of Geophysics, 2019, 66 (4):1718-1731.
[21]	高尔兹奇克 A, 阿达姆奇克 A, 马林诺夫斯基 M. 利用曲线去噪技术对二维和三维地震数据的应用—实际考虑[J]. 应用地球物理学, 2014,105:78-94.
[21]	Górszczyk A, Adamczyk A, Malinowski M. Application of curvelet denoising to 2D and 3D seismic data:Practical considerations[J]. Journal of Applied Geophysics, 2014,105:78-94.
[22]	赵娴, 李玥, 庄广海. 基于轮廓波变换的二维 TFPF 用于地震随机噪声衰减[J]. 应用地球物理学, 2016,129:158-166.
[22]	Zhao X, Li Y, Zhuang G H. 2-D TFPF based on Contourlet transform for seismic random noise attenuation[J]. Journal of Applied Geophysics, 2016,129:158-166.
[23]	刘成明, 王德利, 王通, 等. 基于Shearlet变换的地震随机噪声压制[J]. 石油学报, 2014, 35(4):692-699.
[23]	Liu C M, Wang D L, Wang T, et al. Random seismic noise attenuation based on the Shearlet transform[J]. Acta Petrolei Sinica, 2014, 35(4):692-699.
[24]	刘洋, Fomel Sergey, 刘财, 等. 高阶seislet变换及其在随机噪声消除中的应用[J]. 地球物理学报, 2009, 52(8):2142-2151.
[24]	Liu Y, Sergey F, Liu C, et al. High-order seislet transform and its application of random noise attenuation[J]. Chinese Journal of Geophysics, 2009, 52(8):2142-2151.