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Multichannel Statistical Broadband Wavelet Deconvolution for Improving Resolution of Seismic Signals
IEEE Transactions on Geoscience and Remote Sensing ( IF 7.5 ) Pub Date : 2021-02-01 , DOI: 10.1109/tgrs.2020.2997977
Yijun Yuan , Yingcai Li , Shichang Zhou

Many popular deconvolution methods based on Robinson’s convolutional model have played an important role in improving the temporal resolution of seismic data. However, the outcomes of applying these deconvolution methods to real land seismic data are not always desirable due to the effect of noise in the deconvolution process. Although the noise in the seismogram can be minimized during the recording process, the effect of residual noise on deconvolution operators can result in poor deconvolution output. To address the shortcomings of conventional deconvolution methods, we developed a new deconvolution method based on a multichannel statistical principle. In the proposed method, we have extended the surface-consistent convolutional model to include a noise component, thus including the noise effect on deconvolution operators in the deconvolution process. According to the proposed multichannel statistical strategy, we first calculated the autocorrelation of the seismogram, in which the lateral variation effect on the wavelet is considered because of inhomogeneities in the vicinity of sources and receivers. Then, we adopted a local fitting technique to approximate the autocorrelation of the seismic wavelet. To obtain the seismic data with a broad bandwidth and low-noise level, we used the integral-Ricker wavelet as the desired output wavelet. Tests on synthetic data and real land seismic data demonstrate the effectiveness of the proposed method in increasing the resolution of seismic signals.

中文翻译:

用于提高地震信号分辨率的多通道统计宽带小波解卷积

许多流行的基于 Robinson 卷积模型的反卷积方法在提高地震数据的时间分辨率方面发挥了重要作用。然而,由于解卷积过程中的噪声影响,将这些解卷积方法应用于真实陆地地震数据的结果并不总是理想的。虽然在记录过程中可以最大限度地减少地震图中的噪声,但残余噪声对反卷积算子的影响会导致反卷积输出不佳。为了解决传统反卷积方法的缺点,我们开发了一种基于多通道统计原理的新反卷积方法。在所提出的方法中,我们扩展了表面一致卷积模型以包含噪声分量,因此在反卷积过程中包括对反卷积算子的噪声影响。根据提出的多道统计策略,我们首先计算了地震图的自相关性,其中考虑了由于震源和接收机附近的不均匀性对小波的横向变化影响。然后,我们采用局部拟合技术来近似地震子波的自相关。为了获得宽带宽和低噪声水平的地震数据,我们使用积分Ricker小波作为所需的输出小波。对合成数据和真实陆地地震数据的测试证明了该方法在提高地震信号分辨率方面的有效性。我们首先计算了地震图的自相关,其中考虑了由于震源和接收机附近的不均匀性对小波的横向变化影响。然后,我们采用局部拟合技术来近似地震子波的自相关。为了获得宽带宽和低噪声水平的地震数据,我们使用积分Ricker小波作为所需的输出小波。对合成数据和真实陆地地震数据的测试证明了该方法在提高地震信号分辨率方面的有效性。我们首先计算了地震图的自相关,其中考虑了由于震源和接收机附近的不均匀性对小波的横向变化影响。然后,我们采用局部拟合技术来近似地震子波的自相关。为了获得宽带宽和低噪声水平的地震数据,我们使用积分Ricker小波作为所需的输出小波。对合成数据和真实陆地地震数据的测试证明了该方法在提高地震信号分辨率方面的有效性。为了获得宽带宽和低噪声水平的地震数据,我们使用积分Ricker小波作为所需的输出小波。对合成数据和真实陆地地震数据的测试证明了该方法在提高地震信号分辨率方面的有效性。为了获得宽带宽和低噪声水平的地震数据,我们使用积分Ricker小波作为所需的输出小波。对合成数据和真实陆地地震数据的测试证明了该方法在提高地震信号分辨率方面的有效性。
更新日期:2021-02-01
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