Earthquake Prediction (continued)
There is no visible precursor observed at TXAR. Therefore, it is unlikely that the event that preceeded the earthquake at Melbourne, FL was a precursor. Now the task is to determine if the TXAR array, interpreted as a unit, can detect precursors.
It has been known since the mid-1960s that seismic arrays have two distinct advantages over a network of single stations. First, an array increases the signal-to-noise ratio by the square root of the number of elements in the array. Second, seismic array data can be used to determine the signal-to-noise ratio (SNR), azimuth, horizontal phase velocity, and arrival time of a plane wave (a beam) travelling across the array.
Science Horizons' SeismicRadar product uses the beam grid shown to:
- Assume an azimuth and a horizontal phase velocity of a beam travelling across the array,
- calculate the time difference between the seismic sites and a reference site as the beam travels across the array,
- graphically display the beam amplitude obtained by adding the data from all of the sites, and
- display the data on the specific beam vector in the slowness grid.
There are two types of seismic array data that SeismicRadar is asked to process and identify. The first type contains a visually identified signal. In this case, SeismicRadar is simply asked to determine the Arrival Time, SNR, Azimuth, and Horizontal Phase Velocity data for a well-defined time interval. The P-wave and the S-wave shown on the previous page are examples of that type of data.
The second type of data that SeismicRadar is asked to identify involves a search for data whose Arrival Time, SNR, Azimuth, and Horizontal Phase Velocity are assumed known. Then SeismicRadar is asked to identify the location of seismic data with those defined characteristics. Earthquake precursors are an example of this type of data. Therefore, in order for SeismicRadar to idenfity a precursor, it must know the characteristics of the precursor
We have assumed that an earthquake precursor will have the same fundamental characteristics of the earthquake's P-wave and that the Signal-to-Noise Ratio (SNR) must be a maximum in order for the precursor's characteristics to be compared with the P-wave.
The results of the SeismicRadar processing are summarized below. The actual data produced by SeismicRadar is shown in the following figures. SeismicRadar has identified two precursors prior to the 10 September 2007 Gulf of Mexico earthquake. This is notable considering that these two precursors were identified using seismic data recorded 1063 miles from the epicenter.
| Event | Arrival | SNR | Azimuth | Horizontal Phase Velocity |
|---|---|---|---|---|
| P-wave | 14:59:42 | 998 | 103.88° | 8.38 km/sec |
| S-wave | 15:02:41 | 644 | 110.03° | 3.76 km/sec |
| "Precursor 1" | 14:33:11 | 38 | 101.77° | 7.83 km/sec |
| "Precursor 2" | 14:58:42 | 43 | 102.26° | 8.16 km/sec |
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SeismicRadar display of P-wave data captured by Lajitas (TXAR) array
and associated raw waveform data. |
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SeismicRadar display of S-wave data captured by Lajitas (TXAR) array
and associated raw waveform data. |
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SeismicRadar display of "Precursor 1" data captured by Lajitas
(TXAR) array and associated raw waveform data. |
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SeismicRadar display of "Precursor 2" data captured by Lajitas
(TXAR) array and associated raw waveform data. |
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