Journal of Jilin University(Earth Science Edition) ›› 2020, Vol. 50 ›› Issue (4): 1219-1227.doi: 10.13278/j.cnki.jjuese.20190093

Previous Articles    

Time-Spectral Entropy Method for Picking Up Fracturing Microseismic Data

Tian Yanan, Wang Huanyu, Wang Xin, Huang Jiajun, Zhang Qiang   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2019-04-20 Published:2020-07-29
  • Supported by:
    Supported by National Natural Science Foundation of China (41730422)

Abstract: In the process of oil and gas field development, microseismic monitoring is an effective method to obtain the fracture distribution of hydraulic fracturing. Microseismic location imaging and crack interpretation need to use the location of effective microseismic signals; however,microseismic signals have the characteristics of low signal-to-noise ratio, and the traditional signal picking methods cannot effectively achieve the accurate picking at the first arrival time under the condition of low signal-to-noise ratio. In this paper, a new method based on time-spectral entropy for picking up the initial arrival point is proposed. This method first obtains the time-frequency spectrum of the signal containing noise through S transformation;then divides each sampling point in the spectrum into frames along the frequency direction, and calculates the approximate negative entropy value in each frame frequency band, with the smallest approximate negative entropy value as the negative entropy value of the point;finally, the approximate negative entropy values of all sampling points are compared in the time direction, and the time corresponding to the minimum value is the initial arrival position. In this study, a group of synthetic seismic data are used to verify the effect of the new method, and the results are compared with those obtained by the STA/LTA method. It is concluded that the two methods are both effective when the signal-to-noise ratio is -5 dB, but the time-spectral entropy method is better when the signal-to-noise ratio is -10 dB. Thus, the time-spectral entropy method is more suitable for the first arrival signal picking under low signal-to-noise ratio.

Key words: microseismic signals, time-frequency spectrum, frequency domain frame, negative entropy, arrival-time picking

CLC Number: 

  • P631.4
[1] 焦健, 南雄, 陈德山. 煤矿井下微震监测技术现状与发展[J]. 山东工业技术, 2018(20):85. Jiao Jian, Nan Xiong, Chen Deshan. Status and Development of Microseismic Monitoring Technology in Coal Mine[J]. Shandong Industrial Technology, 2018(20):85.
[2] 段建华. 微地震事件不同初至拾取方法的对比分析[J].煤田地质与勘探,2013,41(3):82-86. Duan Jianhua. Comparative Analysis of Different Picking Methods of Microseismic Events from the Beginning to the End[J]. Coal Geology & Exploration, 2013,41(3):82-86.
[3] Zhang Z Y, Weller A, Kruschwitz S. Pore Radius Distribution and Fractal Dimension Derived from Spectral Induced Polarization[J]. Near Surface Geophysics, 2017, 15(6):625-632.
[4] 程浩,袁月,王恩德,等.基于小波变换的自适应阈值微震信号去噪研究[J].东北大学学报(自然科学版),2018,39(9):1332-1336. Cheng Hao, Yuan Yue, Wang Ende, et al. Study on Adaptive Threshold Microseismic Signal Denoising Based on Wavelet Transform[J]. Journal of Northeastern University (Natural Science Edtion), 2018, 39(9):1332-1336.
[5] 张雪冰,刘财,刘洋,等.基于局部均值分解的地震信号时频分解方法[J].吉林大学学报(地球科学版), 2017, 47(5):1562-1571. Zhang Xuebing, Liu Cai, Liu Yang, et al. Time-Frequency Decomposition Method of Seismic Signals Based on Local Mean Value Decomposition[J]. Journal of Jilin University (Earth Science Edition),2017,47(5):1562-1571.
[6] Li Y, Ni Z, Tian Y. Arrival-Time Picking Method Based on Approximate Negentropy for Microseismic Data[J]. Journal of Applied Geophysics, 2018,152:100-109.
[7] 杨千里. 广义S变换功率谱在地震监测中的应用研究[C]//国家安全地球物理丛书:十四:资源环境与地球物理.北京:中国地球物理学会,2018:301-306. Yang Qianli. Application of Generalized S Transform Power Spectrum in Seismic Monitoring[C]//National Security Geophysics Series:ⅩⅣ:Resources, Environment and Geophysics. Beijing:Chinese Geophysical Society, 2018:301-306.
[8] 马力,何健,李超胜,等.基于广义S变换的地震资料处理[J].科学技术与工程,2017,17(25):171-175. Ma Li, He Jian,Li Chaosheng, et al. Seismic Data Processing Based on Generalized S Transform[J]. Science, Technology and Engineering, 2017, 17(25):171-175.
[9] 陈学华,贺振华,文晓涛,等.基于广义S变换的裂缝分频边缘检测方法[J].吉林大学学报(地球科学版),2011,41(5):1605-1609. Chen Xuehua, He Zhenhua, Wen Xiaotao,et al. Frequency Division Edge Detection Method Based on Generalized S Transform[J]. Journal of Jilin University (Earth Science Edition), 2011, 41(5):1605-1609.
[10] 邓攻,梁锋,李晓婷,等.S变换谱分解技术在深反射地震弱信号提取中的应用[J].地球物理学报,2015,58(12):4594-4604. Deng Gong, Liang Feng, Li Xiaoting, et al. Application of S Transform Spectrum Decomposition Technique in Weak Signal Extraction from Deep Reflection Seismic[J]. Chinese Journal of Geophysics,2015,58(12):4594-4604.
[11] 陈莹莹,简磊.基于最大熵谱估计和时频特性的语音端点检测[J].计算机应用与软件,2017,34(11):91-96. Chen Yingying, Jian Lei. Speech Endpoint Detection Based on Maximum Entropy Spectrum Estimation and Time-Frequency Characteristics[J]. Computer Applications and Software,2017,34(11):91-96.
[12] Saulig N, Milanovic Ž, Ioana C. A Local Entropy-Based Algorithm for Information Content Extraction from Time-Frequency Distributions of Noisy Signals[J]. Digital Signal Processing, 2017(70):155-165.
[13] 倪卓. 基于近似负熵算法实现微地震数据初至拾取研究[D]. 长春:吉林大学, 2018. Ni Zhuo. Research on Initial Arrival Pickup of Microseismic Data Based on Approximate Negative Entropy Algorithm[D]. Changchun:Jilin University, 2018.
[14] 徐耀华, 郭英, 王刚.基于负熵的语音端点检测算法[J].信号处理, 2009, 25(2):307-312. Xu Yaohua, Guo Ying, Wang Gang. Speech Endpoint Detection Algorithm Based on Negative Entropy[J]. Signal Processing, 2009, 25(2):307-312.
[1] Li Qicheng, Guo Lei, He Shugeng, Min Ye. An Improved t0 Method for Determining Normal Depth of Refractive Surface [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(3): 905-910.
[2] Wang Tiexing, Wang Deli, Sun Jing, Hu bin, Liu Sixiu. Separation and Primary Estimation of Blended Data by 3D Sparse Inversion [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(3): 895-904.
[3] Shao Guangzhou, Zhao Kaipeng, Wu Hua. Finite Difference Forward Modeling of Surface Waves Based on MPI [J]. Journal of Jilin University(Earth Science Edition), 2020, 50(1): 294-303.
[4] Luo Teng, Feng Xuan, Guo Zhiqi, Liu Cai, Liu Xiwu. Seismic Inversion of Anisotropy Parameters of Fractured Reservoirs by Simulated Annealing and Particle Swarm Optimization [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(5): 1466-1476.
[5] Lei Dongning, Qiao Yueqiang, Hu Qing, Wang Qiuliang, Lin Song, Li Xue. Quaternary Activity and Its Seismo-Geological Implication of Eastern Segment of Danjiang Fault [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(5): 1362-1375.
[6] Dai Liyan, Dong Hongli, Li Xuegui. Review of Microseismic Data Denoising Methods [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(4): 1145-1159.
[7] Xiao Han, Wang Deli. Travel-Time Computation in VTI Media Based on Fast Marching Method [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(4): 1160-1168.
[8] Sun Zhangqing, Wang Dengke, Han Fuxing. Ray Tracing and Kinematic Characteristics of Different Types of Seismic Waves in Complex Seabed [J]. Journal of Jilin University(Earth Science Edition), 2019, 49(4): 1169-1181.
[9] Xue Linfu, Zhu Ming, Li Wenqing, Liu Wenyu, Liu Zhenghong, Liu Zeyu. Earthquake Triggered by “Magma Bubble” Bursting: 2013 Songyuan Earthquake Cluaters in Jilin as an Example [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(6): 1865-1875.
[10] Lin Song, Li Yuan, Cheng Miao, Deng Xiaohu, Wang Wei. Westward Extension and Quaternary Activity Characteristics of Jiayu Fault [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(5): 1501-1511.
[11] Liu Cai, Pei Sijia, Guo Zhiqi, Fu Wei, Zhang Yusheng, Liu Xiwu. Seismic AVO Simultation and Analysis in Heterogeneous Media [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(5): 1512-1521.
[12] Liu Yi, Liu Cai, Liu Yang, Gou Fuyan, Li Bingxiu. Adaptive Streaming Prediction Interpolation for Complex Seismic Wavefield [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1260-1267.
[13] Deng Xinhui, Liu Cai, Guo Zhiqi, Liu Xiwu, Liu Yuwei. Full Wave Field Seismic Response Simulation and Analysis of Anisotropic Shale Reservoir in Luojia Area of Jiyang Depression [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1231-1243.
[14] Zhang Bing, Guo Zhiqi, Xu Cong, Liu Cai, Liu Xiwu, Liu Yuwei. Fracture Properties and Anisotropic Parameters Inversion of Shales Based on Rock Physics Model [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1244-1252.
[15] Ye Yunfei, Sun Jianguo, Zhang Yiming, Xiong Kai. Construction of Low-Frequency Model with Three-Dimensional Tomographic Velocity Inversion and Application in Deep-Water Bock W of South China Sea [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(4): 1253-1259.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!