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

georesource 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

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 the "Time correlated earthquakes (Seasonal Trends)" application.

The

User shall click on 'SELECT FILES' button in order to use

seismic

catalog data among the ones that are already uploaded in his/her personal workspace.

The User is then requested to fill in the fields shown below:

• Chosen Magnitude Column -

• The user may

• chose among different magnitude scales (e.g

• ML, MW), in the Episodes where these scales are available.

• Output file name prefix –

• File name for the output plot.

• Site name – Name of the site for which the episode is uploaded.

• Latitude range – Range of

• the latitudes of events to be used for

• reshuffling analysis.

• Longitude range

•  –Range of the longitude of events to be used for

• reshuffling analysis.

• Depth range – Range

• of the depth of events to be used for reshuffled analysis.
• Elevation range - Range of the elevation of events to be used for reshuffled analysis.
• Time range - Range of the time of events to be used for reshuffled analysis. The user can here select a time range to be analysed by clicking boxes.

• Magnitude range – Range of

• the magnitude of events to be used for

• reshuffled analysis.

• 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

• as an integer.
• Size of bins – Bin sizes for a given time period. The user can choose "yearly", "monthly", "weekly", "daily", "hourly" and "minutely".

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 the Lacq hydrocarbon field.

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

Figure 3 describes the outputs of Lacq the 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 The 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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