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279 results on '"WANG, Xuben"'

3. Seismic Data Strong Noise Attenuation Based on Diffusion Model and Principal Component Analysis

Author

Peng, Junheng, Li, Yong, Liao, Zhangquan, Wang, Xuben, and Yang, Xingyu

Subjects
Physics - Geophysics, I.2.6, I.4.3
Abstract

Seismic data noise processing is an important part of seismic exploration data processing, and the effect of noise elimination is directly related to the follow-up processing of data. In response to this problem, many authors have proposed methods based on rank reduction, sparse transformation, domain transformation, and deep learning. However, such methods are often not ideal when faced with strong noise. Therefore, we propose to use diffusion model theory for noise removal. The Bayesian equation is used to reverse the noise addition process, and the noise reduction work is divided into multiple steps to effectively deal with high-noise situations. Furthermore, we propose to evaluate the noise level of blind Gaussian seismic data using principal component analysis to determine the number of steps for noise reduction processing of seismic data. We train the model on synthetic data and validate it on field data through transfer learning. Experiments show that our proposed method can identify most of the noise with less signal leakage. This has positive significance for high-precision seismic exploration and future seismic data signal processing research., Comment: 10 pages, 13 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Published
2023

50. 3-D Inversion of Semi-Airborne Transient Electromagnetic Data Based on Decoupled Mesh

Author

Hui, Zhejian, Wang, Xuben, Yin, Changchun, and Liu, Yunhe

Abstract

Semi-airborne transient electromagnetic (SATEM) method is an effective exploration tool in complex environments due to its utilization of unmanned aerial platforms for data collection. With the escalating demands of detection accuracy, the conventional 1-D inversion is no longer sufficient. Over the last two decades, there has been rapid development in 3-D electromagnetic (EM) inversions. SATEM method usually has a substantial number of receiver stations. To obtain accurate 3-D solutions, one has to refine the grids near the receiver points, which causes a huge number of grids and reduces computational efficiency. Thus, computational complexity is one of the primary factors restricting the practicality of 3-D inversions. In this article, we have developed an approach using decoupled meshes. This method uses a series of meshes to parallelly calculate the forward modeling and Jacobian information, with one mesh containing only a subset of receiver points. This scheme aims to decrease the number of grids and improve the efficiency. After that, we map the results to an overarching inversion mesh using the node cloud technique and renew the model parameters. We check our algorithm via both synthetic and field data. Numerical experiments show that the decoupled mesh inversion method can effectively recover the location and resistivities of the anomalies under the complex topography. When compared with the conventional inversion method, the decoupled mesh inversion method can significantly reduce the calculation time.

Published
2024
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