findres 0.0.2

Repeating earthquake discovery using cross-correlation and differential arrival times

FINDRES

Python code for repeating earthquakes

Abstract

The software package FINDRES is an open source seismological software. It consists of some utilities for data preparation (utils directory) and the main program (xxxx.py). FINDRES is designed to discriminate repeating earthquakes starting from a family of candidate repeating earthquakes, based on the cross-correlation values and S-P time difference between pairs of earthquakes (estimated using cross spectrum).

Motivation and significance

The code FINDRES is inspired to previously published methods that combine both seismic waveform similarity, using cross-correlation function, and differential S-P travel time measured at each seismic station (Chen et al., 2008 and Shakibay Senobari and Funning, 2019). The code is versatile and works with and without P and S-wave phase pickings. At the moment the reading of phases in archive Hypoellipse and Hypoinverse formats are implemented. The code has been tested using synthetic and real data, providing accurate results. It contributes to the implementations of open-source Python packages in seismology aiming to support the activities of researchers and the reproducibility of scientific results.

Requirements

Python installed to run the program (version 3.0 or more) is required [http://python.org]. Dependancies include Obspy, Numpy, Scipy, Scikit-learn, mtspec (©2009-2016, Lion Krischer, Moritz Beyreuther) and Matplotlib libraries. to do

How to use it

The package has few dependencies; the recommended way of installing them is via the Conda package manager. You can create a test environment using

conda create -n findres-test python=3.8 numpy=1.21 scipy scikit-learn pandas tqdm pyyaml obspy mtspec -c conda-forge

Remember to activate the environment with

conda activate findres-test

The package is registered on PyPi, you can install it using pip

pip install findres

After that, you'll have the findres script in your path.

# findres --help

usage: ./bin/findres [-h] [--phase_file PHASE_FILE] [--phase_type {hypoinv,nll,quakeml,hypoel}] [--taup_model TAUP_MODEL] [--rebuild_model]
                     [--graphics_dir GRAPHICS_DIR] [--graphics_format GRAPHICS_FORMAT] [--hypodd] [--stop] [--log LOG] [--progress]
                     catalogue inventory parameters output

positional arguments:
  catalogue             Modified ZMAP catalogue containing repeater candidates, their MSEED location, and names
  inventory             Inventory of the stations data
  parameters            Numerical parameters file
  output                Output YAML file

optional arguments:
  -h, --help            show this help message and exit
  --phase_file PHASE_FILE
                        Catalogue containing the phase picking and other information if available (default: None)
  --phase_type {hypoinv,nll,quakeml,hypoel}
                        Type of PHASE_FILE (default: None)
  --taup_model TAUP_MODEL
                        Velocity model file without extension (assumed to be .tvel) if available (default: None)
  --rebuild_model       Force the rebuild of the velocity model (regenerate ObsPy local cache) (default: False)
  --graphics_dir GRAPHICS_DIR
                        Where to put the graphics relative to OUTPUT_DIR, if not specified the graphics is not generated (default: None)
  --graphics_format GRAPHICS_FORMAT
                        Graphics format, must be one of the extensions recognized by matplotlib (default: pdf)
  --hypodd              Whether to output hypodd input files (default: False)
  --stop                Stop if exceptions are raised during the analysis, otherwise skip to the next event station (default: False)
  --log LOG             Log level (default: info)
  --progress            Show progress bar (default: False)

You can run a test using the data provided in this repository. For example the command to analyse the data and produce graphics while showing a progress bar is

findres cre.zmap inventory.xml parameters.json outputs --phase_file=phases_hypoinv.txt --phase_type=hypoinv --taup_model=ncmodel --progress

The numerical parameters are set using the parameters.yaml file. The name of the fields are self-explicative and more extensive information can be found in the provided example.

References

Sugan, M., Campanella, S., Vuan, A., Shakibay Senobari, N., (2022). A Python Code for Detecting Repeating Earthquakes from Self-similar Waveforms (FINDRES). Submitted to BSSA ?

Shakibay Senobari, N., Funning G. J., (2019), Widespread Fault Creep in the Northern San Francisco Bay Area Revealed by Multistation Cluster Detection of Repeating Earthquakes, Geophysical Research Letters, 46(12), 6425-6434, https://doi.org/10.1029/2019GL082766.

Chen, K. H., Nadeau, R. M. and Rau, R.-J. (2008). Characteristic repeating microearthquakes on an arc-continent collision boundary – the Chihshang fault of eastern Taiwan, Earth Planet. Sci. Lett., 276, 262–272, https://doi.org/10.1016/j.epsl.2008.09.021.