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Kurtosis-based P and S wave picker

Project description

Seismological P- and S- wave picker using the modified Kurtosis method

Python port of the picker described in Baillard et al., 2014

debugging information is saved to the local file run_{datetime}.log


The picker is based around the Kurtosis, but also uses energy levels, polarity, clustering and phase association in a 3-step process:

Step 1: define a global pick window

The Kurtosis is calculated for all stations. The global window surrounds the most densely clustered region of triggers.

Step 2: pick P and S arrivals on each station individually

For each station:
  • calculate the Kurtosis over coarse to fine scales.
  • Identify candidates on the coarse scale and refine their times using the finier scales
  • Choose P- and S- candidates based on the signal-to-noise level of each pick
  • Verify the candidates using the waveform polarity, if possible
    • polarity is only used if one of the picks has a dip of > 30 degrees

Step 3: associate picks

  • Calculate origin times for each trace, based on the P-S delay and a simple velocity model (could I use a single Vp/Vs value?)
  • If at least 3 origin times are clustered, use their average origin time to validate all candidates, possibly dipping into the pool of unused candidates for replacemene P and S picks
  • If less than 3 origin times are clustered, reject bad P- and S- picks based on clustering of P-pick times, S-pick times and P-S delays

Example workflow

Start by autopicking a few events, with all bells and whistles on:

To pick one event from a database in /SEISAN/MAYOBS:

from ps_picker import PSPicker
picker = PSPicker('parameters_C.yaml', '/SEISAN/MAYOBS/WAV/MAYOB',  '/SEISAN/MAYOBS/REA/MAYOB')
picker.run_one('19-0607-59L.S201905', plot_global=True, plot_stations=True, verbose=True)

Look at all of the plots and verify that the picks and association are as you expect. If not, change the paramters and run again.

Next, pick several events with only the global plots on

The bells and whistles text will be saved to a log file named run_{DATETIME}.log

To pick events from May 5th to 25th in the same database:

from ps_picker import PSPicker
picker = PSPicker('parameters_C.yaml', '/SEISAN/MAYOBS/WAV/MAYOB',  '/SEISAN/MAYOBS/REA/MAYOB')
picker.run_many('20190505', '20190525', plot_global=True)

Finally, run the whole database without plots

(run_{DATETIME}.log is always created)

To pick events from May 26th 2019 May 1st 2020:

from ps_picker import PSPicker
picker = PSPicker('parameters_C.yaml', '/SEISAN/MAYOBS/WAV/MAYOB', '/SEISAN/MAYOBS/REA/MAYOB')
picker.run_many('20190526', '20200501')

The three main methods:

def __init__(self, parm_file, wav_base_path, database_path_in,
             database_path_out='Sfile_directory', database_format='NORDIC',
             verbose=True, debug_plots=False):
    :param parm_file: path/name of the parameter file
    :param wav_base_path: absolute basepath to the waveform files (just before
                          the YEAR/MONTH subdirectories)
    :param database_path_in: absolute basepath to the database/catalog file(s)
                             (just before the YEAR/MONTH subdirectories)
    :param database_path_out: path to output database files
    :param database_format: 'NORDIC' is the only choice for now
        'NORDIC': Use SEISAN conventions for waveform  and database files
                  (naming, and location in YEAR/MONTH subdirectories)
    :param verbose: output 'verbose' and 'debug' logs to console (will be
                    flagged DEBUG because logging module has no VERBOSE level)
    :param debug_plots: show debugging plots
def run_one(self, database_filename, plot_global=True, plot_stations=False,
            assoc=None, verbose=False, debug_plots=None):
    Picks P and S arrivals on one waveform, using the Kurtosis

    Information in the database file will be appended with the picks.
    :param database_filename: database file to read
    :param plot_global: show global and overall pick plots
    :param plot_stations: show individual station plots
    :param assoc: Associator object (used by run_many())
    :param verbose: same as in creator
    :param debug_plots: same as in creator
def run_many(self, start_date, end_date, plot_global=False,
    plot_stations=False, verbose=False, ignore_fails=False):
    Loops over events in a date range

    :param start_date: "YYYYMMDD" or "YYYYMMDDHHMM" of first data to process
    :param end_date: "YYYYMMDD" of last data to process
    :param plot_global: show global and overall pick plots
    :param plot_stations: show individual station plots
    :param ignore_fails: keep going if one run fails


Parameter and response files

Are documented here

To Do

  • Add event location-based acceptance of solitary P- and S- candidates
  • In P-, S- and P-S clustering stage, allow unused candidates to be substituted for rejected picks
  • Dedicated To Do file

Also see the profiling file

Project details

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