岩性油气藏 ›› 2015, Vol. 27 ›› Issue (4): 77–83.doi: 10.3969/j.issn.1673-8926.2015.04.011

• 技术方法 • 上一篇    下一篇

基于S变换的低信噪比微震信息提取方法研究

王 鹏1,常 旭2,桂志先1,王一博2   

  1. 1. 油气资源与勘探技术教育部重点实验室(长江大学),武汉 430100 ;2. 中国科学院 地质与地球物理研究所,北京 100029
  • 出版日期:2015-07-20 发布日期:2015-07-20
  • 作者简介:王鹏( 1982- ),男,博士,讲师,主要从事水力压裂微震监测信号处理与微震震源定位的教学与科研工作。 地址:( 430100 )湖北省武汉市蔡甸区长江大学地球物理与石油资源学院。 E-mail : wangpengga163@163.com
  • 基金资助:

    国家自然科学基金项目“页岩气开发中的微地震反演”(编号: 41230317 )和“页岩气压裂监测的微地震震源位置与各向异性参数联合反演”(编号:41274112)联合资助

Microseismic information extraction in low signal-to-noise ratio microseismic signal based on S-transform

Wang Peng1, Chang Xu2, Gui Zhixian1, Wang Yibo2   

  1. 1. Key Laboratory of Exploration Technologies for Oil and Gas Resources , Ministry of Education , Yangtze University ,Wuhan 430100 , China ; 2. Institute of Geology and Geophysics , Chinese Academy of Science , Beijing 100029 , China
  • Online:2015-07-20 Published:2015-07-20

摘要:

低孔、低渗储层,特别是页岩气储层,已成为当前勘探开发的热点。 压裂是这类储层的主要开发手段,而微震监测可对压裂过程和压裂效果进行直观评价。微震信号的检测与信息提取是微震监测的基础,在实际监测环境下,接收到的信号其信噪比较低,难以直接提取微震信息。 因此,提出利用 S 变换对低信噪比微震数据进行时频分析的方法,并发现微震横波成分的抗噪能力较强。利用这一特征,对实际低信噪比微震监测数据进行处理,实现了对微震信号的有效提取。

关键词: 地面激光雷达, 数字露头, 层序界面, 沉积旋回, 砂体特征, 延长组, 鄂尔多斯盆地

Abstract:

Low porosity and permeability reservoirs, especially shale gas reservoirs, have been the focus of current oil and gas exploration and development. Fracturing is the main stimulation method for this kind of reservoirs. Moreover, microseismic monitoring is an effective tool of the fracturing processing monitoring and evaluation, and it is based on the microseismic detection and information extraction. However, it is difficult to record satisfied microseismic signal under complex geological conditions. This paper analyzed the characteristics of low signal-to-noise ratio microseismic signal using timefrequency analysis based S-transform. According to the time-frequency analysis of contaminated signals, S-wave component of microseismic events has a robust feature of anti-noise. Using the characteristics above, a satisfied result is achieved in the real microseismic monitoring processing with low signal-to-noise ratio.

Key words: ground-based Lidar, digital outcrop , sequence boundary, sedimentary cycle , sandbody characteristics , YanchangFormat ion , OrdosBasin

[ 1 ] 黄籍中 . 四川盆地页岩气与煤层气勘探前景分析[ J ] . 岩性油气藏, 2009 , 21 ( 2 ): 116-120.

Huang Jizhong. Exploration prospect of shale gas and coal-bed methane in Sichan Basin [ J ] . Lithologic Reservoirs , 2009 , 21 ( 2 ): 116-120.

[ 2 ] 张小龙,张同伟,李艳芳,等 . 页岩气勘探和开发进展综述[ J ] . 岩性油气藏, 2013 , 25 ( 2 ): 116-122.

Zhang Xiaolong , Zhang Tongwei , Li Yangfang , et al. Research advance in exploration and development of shale gas [ J ] . Lithologic Reservoirs , 2013 , 25 ( 2 ): 116-122.

[ 3 ] Agarwal R G , Carter R D , Pollock C B. Evaluation and performance prediction of low-permeability gas wells stimulated by massive hydraulic fracturing  [ J ] .Journalofpetroleum Technology , 1979 , 31 ( 3 ): 362-372.

[ 4 ] 刘伟,贺振华,李可恩,等 . 地球物理技术在页岩气勘探开发中的应用和前景[ J ] . 煤田地质与勘探, 2013 , 41 ( 6 ): 68-73.

Liu Wei , He Zhenhua , Li Keen , et al. Application and prospective of geophysics in shale gas development [ J ] . Coal Geology & Exploration , 2013 , 41 ( 6 ): 68-73.

[ 5 ] Daniels J , Waters G , Le Calvez J , et al. Contacting more of the Barnett Shale through an integration of real-time microseismic monitoring , petrophysics , and hydraulic fracture design [ R ] . SPE Annual Technical Conference and Exhibition , 2007.

[ 6 ] Maxwell S C , Rutledge J , Jones R , et al. Petroleum reservoir characterization using downhole microseismic monitoring [ J ] . Geophysics ,2010 , 75 ( 5 ): 75A129-75A137.

[ 7 ] 梁兵,朱广生 . 油气田勘探开发中的微震监测方法[ M ] . 北京:石油工业出版社, 2004.

Liang Bing , Zhu Guangsheng. Microseismic monitoring method in oil & gas exploration and development [ M ] . Beijing : Petroleum Industry Press , 2004.

[ 8 ] Warpinski N R. Interpretation of hydraulic fracture mapping experiments [ R ] . In University of Tulsa Centennial Petroleum Engineering Symposium , 1994 : 291-300.

[ 9 ] 叶根喜,姜福兴,杨淑华 . 时窗能量特征法拾取微地震波初始到时的可行性研究[ J ] . 地球物理学报, 2008 , 51 ( 5 ): 1574-1581.


Ye Genxi , Jiang Fuxing , Yang Shuhua. Possibility of automatically picking first arrival of microseismic wave by energy eigenvalue method [ J ] . Chinese J. Geophys. ( in Chinese ), 2008 , 51 ( 5 ): 1574-1581.

[ 10 ] de Meersman K , Van Der Baan M , Kendall J M. Signal extraction and automated polarization analysis of multicomponent array data [ J ] . Bulletin of the Seismological Society of America , 2006 , 96 ( 6 ):2415-2430.

[ 11 ] Eisner L , Abbott D , Barker W B , et al. Noise suppression for detection and location of microseismic events using a matched filter [ R ] . 78th SEG meeting , Las Vegas , Nevada , USA , Expanded Ab-stracts , 2008 : 1431-1435.

[ 12 ] Song F , Kuleli H S , Toksoz M N , et al. An improved method for hydrofracture-induced microseismic event detection and phase picking[ J ] . Geophysics ,2010 , 75 ( 6 ): A47-A52.

[ 13 ] 庞锐,刘百红,孙成龙 . 时频分析技术在地震勘探中的应用综述[ J ] . 岩性油气藏, 2013 , 25 ( 3 ): 92-97.

Pang Rui , Liu Baihong , Sun Chenglong. Review on time-frequency analysis technique and its application in seismic exploration [ J ] . Lithologic Reservoirs , 2013 , 25( 2 ): 92-97.

[ 14 ] Tobback T , Steeghs P , Drijkoningen G G , et al. Decomposition of seismic signals via time-frequency representations [ R ] . 1996 SEG Annual Meeting , 1996.

[ 15 ] Huerta-Lopez C , Shin Y , Powers E J , et al. Time-frequency analysis of earthquake records [ C ] . Proceedings , 12th World Conference on EarthquakeEngineering , Auckland , NewZealand , February , 2000.


[ 16 ] Gabarda S , Cristobal G. Detection of events in seismic time series by time-frequency methods [ J ] . Signal Processing , IET , 2010 , 4 ( 4 ):413-420.

[ 17 ] Rutledge J T , Phillips W S. Hydraulic stimulation of natural fractures as revealed by induced microearthquakes , Carthage Cotton Valleygasfield , eastTexas [ J ] .Geophysics , 2003 , 68 ( 2 ): 441-452.

[ 18 ] Moriya H. Phase-only correlation of time-varying spectral representations of microseismic data for identification of similar seismic events [ J ] . Geophysics , 2011 , 76 ( 6 ): WC37-WC45.

[ 19 ] Gabor D. Theory of communication [ J ] . J IEE , 1946 , 93 : 429-457.

[ 20 ] Cohen L. Time-frequency analysis ( Vol. 778 )[ M ] . New Jersey : Prentice Hall PTR , 1995.

[ 21 ] Stockwell R G , Mansinha L , Lowe R P. Localization of the complex spectrum : the S transform [ J ] . Signal Processing , IEEE Transactions on , 1996 , 44 ( 4 ): 998-1001.

[ 22 ] Pinnegar C R , Mansinha L. The S-transform with windows of arbitrary and varying shape [ J ] . Geophysics , 2003 , 68 ( 1 ): 381-385.

[ 23 ] 高静怀,陈文超,李幼铭,等 . 广义 S 变换与薄互层地震响应分析[ J ] . 地球物理学报, 2003 , 46 ( 4 ): 526-532.

Gao Jinghuai , Chen Wenchao , Li Yaming , et al. Generalized S transform and seismic response analysis of thin interbeds [ J ] . Chinese J. Geophys. ( in Chinese ), 2003 , 46 ( 4 ): 526-532.

[ 24 ] 高静怀,满蔚仕,陈树民,等 . 广义 S 变换域有色噪音与信号识别方法[ J ] . 地球物理学报, 2004 , 47 ( 5 ): 869-875.

Gao Jinghuai , Man Weishi , Chen Shumin , et al. Recognition of signals from colored noise background in generalized S-transform domain [ J ] .ChineseJ.Geophys. ( inChinese ), 2004 , 47 ( 5 ): 869-875.

[ 25 ] 刘丽娟,王山山 . 广义 S 变换窗函数的分析和改进[ J ] . 岩性油气藏, 2007 , 19 ( 2 ): 76-79.

Liu Lijuan , Wang Shanshan. Analysis and improvement of window function of generalized S-transform [ J ] . Lithologic Reservoirs , 2007 ,19 ( 2 ): 76-79.

[ 26 ] 赵淑红,朱光明 . S 变换时频滤波去噪方法[ J ] . 石油地球物理勘探, 2007 , 42 ( 4 ): 402-406.

Zhao Shuhong , Zhu Guangming. Time-frequency filtering to denoise by S transform [ J ] . OGP , 2007 , 42 ( 4 ): 402-406.

[ 27 ] Nakajima H , Kobayashi K , Higuchi T. A fingerprint matching algorithm using phase-only correlation [ J ] . IEICE Transactions on Fundamentals of Electronics , Communications and Computer Sciences , 2004 , 87 ( 3 ): 682-691.

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