Search Results - "Guo, Xuebao"

Surface-Related and Internal Multiple Elimination Using Deep Learning by Bao, Peinan, Shi, Ying, Wang, Weihong, Xu, Jialiang, Guo, Xuebao

“…Multiple elimination has always been a key, challenge, and hotspot in the field of hydrocarbon exploration. However, each multiple elimination method comes…”
Get full text

A robust source-independent misfit function for time domain waveform inversion based on normalized convolved wavefield by Guo, Xuebao, Shi, Ying, Wang, Weihong, Liu, Hong

“…It is usually necessary to provide a source wavelet before the waveform inversion, and accuracy of the wavelet determines whether the synthetic data matches…”
Get full text

Modeling of frequency-domain elastic-wave equation with a general optimal scheme by Li, Aman, Liu, Hong, Yuan, Yuxin, Hu, Ting, Guo, Xuebao

“…Frequency-domain numerical modeling is an important foundation of frequency-domain full waveform inversion.However, the conventional 9-point scheme for…”
Get full text

Improving waveform inversion using modified interferometric imaging condition by Guo, Xuebao, Liu, Hong, Shi, Ying, Wang, Weihong, Zhang, Zhen

“…Similar to the reverse-time migration, full waveform inversion in the time domain is a memory-intensive processing method. The computational storage size for…”
Get full text

Locating volcanic tremor using azimuth coherence of cross-correlation by Guo, Xuebao, Sun, Muchen, Yu, Youqiang, Shi, Ying, Jia, Xin

Get full text

High-order azimuth coherent imaging for microseismic location by Shi, Ying, Guo, Xuebao, Yu, Youqiang

“…Abstract The cross-correlation-based methods, widely used for microseismic monitoring, utilize cross-correlation to extract time differences of signals within…”
Get full text

Self-Supervised Multitask 3-D Partial Convolutional Neural Network for Random Noise Attenuation and Reconstruction in 3-D Seismic Data by Cao, Wei, Shi, Ying, Wang, Weihong, Guo, Xuebao, Tian, Feng, Zhao, Yang

“…Most existing traditional and deep learning (DL)-based methods used for random noise attenuation or reconstruction of seismic data typically only process 2-D…”
Get full text

BiInNet: Bilateral Inversion Network for Real-Time Velocity Analysis by Cao, Wei, Shi, Ying, Guo, Xuebao, Tian, Feng, Ke, Xuan, Li, Chunsheng

“…Most previous studies focus on using complex deep neural networks to learn diverse features of massive synthetic data. In more realistic situations with a…”
Get full text

MLPCC-MLMAE-Based Early Stopping Strategy for Unsupervised 3-D Seismic Data Reconstruction by Cao, Wei, Tian, Feng, Liu, Zongbao, Liu, Fang, Zhao, Yang, Shi, Ying, Wang, Weihong, Guo, Xuebao

“…Unsupervised methods for single 3-D seismic data reconstruction, such as deep image prior (DIP) and Bernoulli sampling (BS) frameworks, have achieved promising…”
Get full text

Extracting Low-Frequency Information from Time Attenuation in Elastic Waveform Inversion by Guo, Xuebao, Liu, Hong, Shi, Ying, Wang, Weihong

“…Low-frequency information is crucial for recovering background velocity, but the lack of low-frequency information in field data makes inversion impractical…”
Get full text

Dynamic Convolution-based Misfit Function for Time Domain Full Waveform Inversion by Guo, Xuebao, Liu, Hong, Shi, Ying, Wang, Weihong, Zhang, Zhen, Jing, Hongliang

“…Under the same propagation operator, the precision of the seismic wavelet determines whether synthetic data can match field data accurately. By constructing…”
Get full text

Seismic velocity inversion based on CNN-LSTM fusion deep neural network by Wei, Cao, Xue-Bao, Guo, Feng, Tian, Ying, Shi, Wei-Hong, Wang, Hong-Ri, Sun, Xuan, Ke

“…Based on the CNN-LSTM fusion deep neural network, this paper proposes a seismic velocity model building method that can simultaneously estimate the root mean…”
Get full text