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Seismoelectric and electroseismic datasets for a shallow or ground surface source

Citation

Zheng, Xuzhen; Ren, Hengxin; Butler, Karl E. (2021), Seismoelectric and electroseismic datasets for a shallow or ground surface source, Dryad, Dataset, https://doi.org/10.5061/dryad.95x69p8kj

Abstract

The datasets are numerical modelling results of seismoelectric and electroseismic wave-fields computed by the updated algorithm which combines the Luco-Apsel-Chen generalized reflection and transmission coefficient method (GRTM) and the peak-trough averaging method (PTAM) for a shallow or ground surface source. In addition, the code of the peak-trough averaging method (PTAM) adopted in seismoelectric or electroseismic modelling is cleaned up into a separate Matlab package (named SE_PTAM) and uploaded, which can be easily transplanted into the seismoelectric or electroseismic modelling algorithms based on reflectivity methods (e.g., Garambois & Dietrich, 2002; Grobbe et al., 2016; Haartsen & Pride, 1997; Ren et al., 2010a).

Methods

The datasets are computed by the updated algorithm which combines the Luco-Apsel-Chen generalized reflection and transmission coefficient method (GRTM) and the peak-trough averaging method (PTAM).

 

Usage Notes

The datasets are divided into 5 parts: DataSets S1 to S5, which include all the data presented in the seismoelectric and electroseismic modelling for a shallow or ground surface source. 

The three GIF files, display the propagation animations of the electroseismic wave-fields computed by considering the peak frequency of the Ricker wavelet to be fp=800 Hz, fp=80 Hz, and fp=400 Hz, respectively. The amplitudes of the animations of the electroseismic wave-fields for fp=80 Hz and fp=400 Hz cases are adjusted by multiplying the third power of the distance between the receiver and the projection point of the electric current source on the first subsurface interface in an effort to improve the visibility of relatively weaker signals. The corresponding snapshots are displayed in Figures 6, 8, and 9 of the manuscript, respectively.

The "readme.txt" file is presented as a guide to the datasets and three GIF files.

The uploaded PTAM code contains three MATLAB files, i.e., the main function "SE_PTAM.m", the subfunctions "SE_exact.m" and "SE_ram.m". 

Funding

National Natural Science Foundation of China, Award: 41974081

National Natural Science Foundation of China, Award: 42022027

National Natural Science Foundation of China, Award: 41874082