python tools for seismic ground-roll (surface wave) simulation
cd ./data_synthesis
python ground_roll_syn.py
# change the parameters inside the script to get customized result
# the synthetic result is saved as .npy format
sample result
ground-roll simulation parameters:
num_traces: number of seismic traces (single side w.r.t source point)
num_time_samples: number of samples in time axis
time_shift: offset to the top
freq_low: the lower frequency of the chirp signal to simulate dispersity
freq_high: the higher frequency of the chirp signal to simulate dispersity
dx: space sample interval (unit: m)
dy: time sample interval (unit: s)
velocity: ground-roll velocity (unit: m/s)
distance_degradation: amplitude degradation ratio w.r.t distance
win_scale: controls the smooth edge of window, should be larger than (or equal to) 2, the larger the shearer
duration_ratio: controls the sampling of chirp of ground-roll in each trace
save_path: synthetic data save path, if parent folder not exist, it will be created
- if this project helps you, please cite the following papers:
@misc{jia2024groundrollseparationlandseismic,
title={Ground-roll Separation From Land Seismic Records Based on Convolutional Neural Network},
author={Zhuang Jia and Wenkai Lu and Meng Zhang and Yongkang Miao},
year={2024},
eprint={2409.03878},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2409.03878},
}@inproceedings{jia2019separating,
title={Separating ground-roll from land seismic record via convolutional neural network},
author={Jia, Zhuang and Lu, Wenkai and Zhang, Meng and Miao, Yongkang},
booktitle={SEG 2018 Workshop: SEG Maximizing Asset Value Through Artificial Intelligence and Machine Learning, Beijing, China, 17-19 September 2018},
pages={60--63},
year={2019},
organization={Society of Exploration Geophysicists and the Chinese Geophysical Society}
}