Earthquake interactions: Time correlated earthquakes (Seasonal trends) user guide

About the Service
The service use superposed epoch analysis to extract seasonal patterns in seismicity time series and it tests the result robustness against reshuffled series. One key time patterns of anthropogenic activity relatively to tectonic events is temporal driven by production history. When seasonal patterns for geo-energy production are known, we test in the application how these patterns impact the time series of anthropogenic seismicity.  The users choose to test the time pattern of seismicity on a window that corresponds to the rhythm of geo-resource production (e.g. the hourly or daily basis for mining or fluid injection fracking); or monthly patterns for reservoir water level (e.g. Mekkawi et al. 2004), oil and gas production). The service further tests if the time patterns that are observed are significant as tested against reshuffled series. The reshuffled series are imposed to have the same number of events, in the same range of value (e.g. Lemarchand and Grasso, 2007, Tahir et al. 2012). It allows to accept or to reject the observed seasonal trend at a given (e.g. 95%) confidence level. It corresponds to Monte Carlo techniques (e.g. Lemarchand and Grasso, 2007, Tahir et al. 2012, Grasso et al. 2018), involving 1000 random sets of key events. This is assessed by random sampling1000 sets of "synthetic event catalogues" (including bootstrap procedure). The 1000 sets of synthetic catalogues are then analysed in the same manner as the real seismicity catalogue to assess confidence levels for the observed episode distribution.
Reference: 
- Grasso, J.‐R., A. Karimov, D. Amorese, C. Sue, C. Voisin, (2018) Patterns of Reservoir‐Triggered Seismicity in a Low‐Seismicity Region of France. Bulletin of the Seismological Society of America doi: https://doi.org/10.1785/0120180172
- Lemarchand, N., and J.-R. Grasso (2007), Interactions between earthquakes and volcano activity, Geophys. Res. Lett., 34, L24303, doi:10.1029/2007GL031438.
- Mekkawi, M. J-R Grasso, and P Schnegg, 2004. A long lasting seismic relaxation at Lake Aswan, Egypt, 1982_2001, Bull. Seis. Soc. Am. 94, 2, 479-492.
- Tahir, M., J.-R. Grasso, and D. Amorèse,(2012) The largest aftershock: How strong, how far away, how delayed? Geophys. Res. Lett., 39, L04301, doi:10.1029/2011GL050604

Step by step

After the User adds the application to his/her personal workspace, the following window appears on the screen (Figure 1):

Figure 1. Input window of time correlated earthquakes (Seasonal Trends) application.

The user is now requested to fill in the fields shown below:

1) Use Seismic catalogue: The user may click on "select files" button in order to use a seismic catalogue input among the ones that are already uploaded in his/her personal workspace.

2) Select Magnitude Column: The user may choose among different magnitude scales (e.g. M_L, M_W) in the Episodes where these scales are available.

3) Output file name prefix – The file name for the output plot

4) Site name – Name of the site for which the episode is uploaded

5) Latitude range – Range of event latitudes used for seasonal analysis

6) Longitude range – Range of event longitudes used for seasonal analysis

7) Depth range – Range of event depths used for seasonal analysis

8) Time range: Range of event times used for seasonal analysis. Here, the user can select a time range by clicking boxes.

9) Magnitude range – Range of event magnitudes used for seasonal analysis

10) Number of samples – Number of reshuffled catalogues to be stacked as superposed epoch reference; number of synthetic datasets. The user inserts the number of synthetic datasets in the empty box. Minimum value is 100, default value is 1000.

11) Size of bins – Size of time bins for a given seasonal pattern. 3 choices are possible:1) year (monthly bins), 2) week (daily bins), 3) day (hourly bins). The user can choose “monthly”, ”daily” and “hourly”.

Figure 2 shows default values used for Lacq hydrocarbon field.

Figure 2. Default values for Lacq hydrocarbon field.

After defining the aforementioned parameters, the user shall click on the "Run" button and the calculations are performed. The Status changes from 'CREATED' to 'RUNNING' and finally to 'FINISHED'. The output is created and plotted in the main window just below the “RUN” button. The result appears in the left corner of the platform.

Figure 3 describes the outputs of Lacq field seasonal trend. Original data and monthly earthquake stack are displayed as green bars, while the average value of green bars are shown as a red line. A synthetic dataset is used to see how sufficient (strong) original monthly earthquakes are.

Boxplot is used for synthetic dataset results. Thick and thin vertical blue bars are one and two sigma fluctuations estimated from the variability of the N synthetic series. It allows to estimate the 66% and 95% confidence level, respectively, when real series overpass these thresholds.

Boxplot definition:

The first quartile (Q1) is defined as the middle number between the smallest number and the median of the data set.

The second quartile (Q2) is the median of the data.

The third quartile (Q3) is the middle value between the median and the highest value of the data set.

The "thick blue line" is (QR), as (QR= Q3- Q1).

The "white dot" inside the thick blue line (in compact view) is the median.

Thin blue lines are the whiskers, defined as Q3+1.5(IQR) and Q1-1.5(IQR).

Figure 3. Lacq field seasonal trends: In this example, the January rate value is accepted at a 95% confidence level. January, February and June rates are accepted values above the uniform distribution at a 66% confidence level.

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