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| The application of translation invariant wavelet de-noising method with a modified threshold to denoising in magnetotelluric sounding |
| Xiao-Ling CAO1,2,3, Liang-Jun YAN1,2, Qing-Li CHEN1,2 |
1. Key Laboratory of Exploration Technologies for Oil and Gas Resources in Ministry of Education,Yangtze university,Wuhan 430100,China
2. Hubei Cooperation Innovation Center of Unconventional Oil and Gas,Wuhan 430100,China
3. School of Information and Mathematics,Yangtze university,Jingzhou 434023,China |
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Abstract In the process of measuring electric field and magnetic field components,due to interference from geological factors,power frequency,human activities,and other external factors as well as the observation system,there often exist many kinds of noises in actual data,which affect the computing of apparent resistivity and phase and the subsequent forward and inversion work.In order to improve the processing effect,the authors applied the TI wavelet denoising method based on improved threshold to the denoising of magnetotelluric signals on the basis of the existing fast algorithm.By using the denoising method,not only the noise can be removed effectively,but also the original shape of signal can be preserved at a large extent.After dealing with the measured magnetotelluric signal data by this method,the authors detected that the denoising method can make the mutation phenomenon under effective control and decrease,and furthermore it improves significantly the quality of time series,apparent resistivity curve and phase curve,thus it has a good denoising effect for magnetotelluric signal.
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Received: 03 May 2017
Published: 04 June 2018
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| 信噪比 | 1 dB | 2 dB | 5 dB | 10 dB | 20 dB | | 软阈值去噪 | 9.69 | 10.69 | 14.13 | 18.78 | 28.48 | | 硬阈值去噪 | 5.72 | 6.66 | 11.29 | 16.41 | 26.25 | | 原始的TI去噪 | 10.25 | 11.00 | 14.56 | 19.87 | 29.00 | | 改进的TI去噪 | 10.88 | 11.42 | 14.98 | 20.31 | 29.91 |
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| 信噪比 | 1 dB | 2 dB | 5 dB | 10 dB | 20 dB | | 软阈值去噪 | 136.87 | 123.45 | 82.13 | 48.08 | 15.73 | | 硬阈值去噪 | 216.34 | 194.14 | 113.87 | 63.18 | 20.36 | | 原始的TI去噪 | 128.40 | 117.70 | 78.18 | 42.40 | 14.78 | | 改进的TI去噪 | 127.10 | 116.91 | 77.82 | 41.89 | 14.12 |
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| 信噪比 | 1 dB | 2 dB | 5 dB | 10 dB | 20 dB | | 原始的TI去噪时间/s | 0.07 | 0.03 | 0.03 | 0.03 | 0.03 | | 改进的TI去噪时间/s | 0.03 | 0.02 | 0.02 | 0.02 | 0.02 |
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| 参数 | 最小值 | 最大值 | 均值 | 方差 | 能量 | | 去噪前 | -7.187×104 | 1.255×105 | 2.613 | 4.603×106 | 8.396×1011 | | 去噪后(haar) | -6.569×104 | 1.197×105 | 2.613 | 2.164×106 | 3.947×1011 | | 去噪后(sym8) | -6.655×104 | 1.191×105 | 2.613 | 2.265×106 | 4.131×1011 | | 去噪后(db6) | -6.630×104 | 1.178×105 | 2.613 | 2.223×106 | 4.054×1011 |
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| 参数 | 最小值 | 最大值 | 均值 | 方差 | 能量 | | 去噪前 | -1.046×104 | 1.308×104 | -3.715 | 1.753×106 | 7.992×1010 | | 去噪后(haar) | -8.369×103 | 9.487×103 | -3.715 | 4.513×105 | 2.058×1010 | | 去噪后(sym8) | -8.452×103 | 1.034×104 | -3.715 | 7.113×105 | 3.244×1010 | | 去噪后(db6) | -8.481×103 | 9.931×103 | -3.715 | 6.992×105 | 3.189×1010 |
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| 参数 | 最小值 | 最大值 | 均值 | 方差 | 能量 | | 去噪前 | -1.054×104 | 1.296×104 | -2.875 | 1.724×106 | 8.479×1010 | | 去噪后(haar) | -8.188×103 | 9.777×103 | -2.875 | 7.118×105 | 3.502×1010 | | 去噪后(sym8) | -8.221×103 | 1.059×104 | -2.875 | 1.087×106 | 5.347×1010 | | 去噪后(db6) | -8.251×103 | 1.018×104 | -2.875 | 1.065×106 | 5.240×1010 |
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| 参数 | 最小值 | 最大值 | 均值 | 方差 | 能量 | | 去噪前 | -7.185×104 | 1.253×105 | 1.878 | 4.203×106 | 8.271×1011 | | 去噪后(haar) | -6.605×104 | 1.198×105 | 1.878 | 2.223×106 | 4.375×1011 | | 去噪后(sym8) | -6.702×104 | 1.196×105 | 1.878 | 2.349×106 | 4.624×1011 | | 去噪后(db6) | -6.671×104 | 1.184×105 | 1.878 | 2.304×106 | 4.534×1011 |
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| 相关系数 | Ex | Ey | Hx | Hy | Hz | | 软阈值去噪法 | 0.786 | 0.798 | 0.813 | 0.802 | 0.610 | | 硬阈值去噪法 | 0.614 | 0.601 | 0.671 | 0.625 | 0.596 | | 本文方法 | 0.835 | 0.844 | 0.878 | 0.859 | 0.662 |
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