Method of imminent earthquake prediction by observation of electromagnetic field and system for carrying out the same

• US 5,694,129 A
• Filed: 08/29/1995
• Issued: 12/02/1997
• Est. Priority Date: 08/29/1995
• Status: Expired due to Fees

• Current Assignee: National Institute Of Information, Science And Technology Agency National Research Institute For Earth Science And Disaster Prevention
• Original Assignee: Ministry of Transportation and Communications ROC (Government of The Republic of China), Science And Technology Agency National Research Institute For Earth Science And Disaster Prevention
• Inventors: Takahashi, Kozo, Fujinawa, Yukio
• Primary Examiner(s): Lobo, Ian J.
• Application Number:
  US08/520,671
• Time in Patent Office: 826 Days
• Field of Search: 342/22, 367/13, 367/14, 324/323, 324/348, 340/690
• US Class Current: 342/22
• CPC Class Codes: G01V 1/01 Measuring or predicting earthquakes

Abstract

A seismic electromagnetic field signal is detected at each of observation stations installed at at least two places, and civil noise and atmospheric discharge noise are eliminated from the signal to obtain a low-frequency seismic electromagnetic field signal O_s. A local characteristic signal C_e and a refined local characteristic signal C_f are obtained by processing the signal O_s. The signals O_s, C_e and C_f are transmitted to a central station. At the central station, a delay time T and a half-width H are obtained from the cross-correlation function between the observation stations, and further a regional characteristic signal C_r is obtained from the seismic electromagnetic field signal O_s. An earthquake source region distribution, an earthquake magnitude, and earthquake occurrence time are estimated on the basis of the signals obtained at the central station and the local characteristic signal C_e and refined local characteristic signal C_f obtained at each observation station.

Claims

1. An earthquake prediction method in which seismic electromagnetic field signals detected and processed at a plurality of observation stations are transmitted to and processed by a central station to estimate earthquake occurrence time, an earthquake occurrence place, and an earthquake magnitude, thereby making earthquake prediction, said method comprising the steps of:

outputting a seismic electromagnetic field signal O_a obtained by eliminating civil noise and atmospheric discharge noise from a seismic electromagnetic field signal detected with an electromagnetic field sensor of each of observation stations installed in a plurality of places, and arrival bearing data (direction d and extension Δ

d) concerning a lightning electromagnetic field signal detected by lightning position detecting means;

comparing said seismic electromagnetic field signal O_a with waveforms of known seismic electromagnetic field signals and eliminating signals other than a signal having the same waveform as that of said seismic electromagnetic field signal O_a, thereby extracting a noiseless seismic electromagnetic field signal O_s ;

outputting a local characteristic signal C_e including a number of pulses present in a predetermined time interval for each amplitude level of said seismic electromagnetic field signal O_s, and a maximum value and a minimum value of said signal O_s, and local direction distribution data (main direction d_0i and dispersion Δ

d_0i) obtained from arithmetic mean of said arrival bearing data (d and Δ

d) captured in a predetermined period of time;

outputting a refined local characteristic signal C_f including a number of pulses for each amplitude level of said seismic electromagnetic field signal O_s which are present in a spatial window defined by a central direction d_s connecting an observation point of said observation station and a seismic electromagnetic field source region central position X₀ indicated by data sent from said central station, and a dispersion Δ

d_s corresponding to an extension Δ

X₀ of said seismic electromagnetic field source region central position X₀, said refined local characteristic signal C_f further including a maximum value and a minimum value of said seismic electromagnetic field signal O_s but not including a noise component present outside said spatial window;

transmitting said seismic electromagnetic field signal O_s having a frequency below a predetermined level, said local characteristic signal C_e, said refined local characteristic signal C_f, said arrival bearing data (d and Δ

d), and said local direction distribution data (d_0i and Δ

d₀₁), which are obtained at each of said observation stations, to said central station;

obtaining, at said central station, a cross-correlation function R_ij (δ

t)=∫

O_si (t+δ

t)O_sj (t)dt between said signals O_s inputted from said observation stations with a delay time, smoothing said cross-correlation function R_ij (δ

t) by a moving average to obtain a smoothed cross-correlation function R_sij (t)=∫

ω

(t-τ

)R_sij (t)dτ

, obtaining a point of time at which said smoothed cross-correlation function reaches a maximum as delay time T_ij, and further obtaining a half-width H of said smoothed cross-correlation function;

calculating, as an earthquake occurrence spatial point, an intersection of a plurality of hyperboloids of two sheets drawn as loci of points at which a propagation distance difference corresponding to said delay time T_ij is constant, with any pair of observation points defined as foci, and calculating a central position X_t of a spacial distribution of a set of said earthquake occurrence spatial point, together with an extension Δ

X_t ;

temporally matching time-series data of said seismic electromagnetic field signals O_s inputted with a delay time so that said delay time is eliminated, extracting from said signals O_s signals which are mutually present in an allowable arrival time interval Δ

T₁₂ determined on the basis of said half-width H of said cross-correlation function, and outputting a noiseless seismic electromagnetic field signal O_r ;

outputting a regional characteristic signal C_r including a pulse number of said signal O_r for each amplitude level and a maximum value and a minimum value of said signal O_r, and a seismic electromagnetic field source region average central position X_r, extension Δ

X_r and average intensity distribution I_r, which are obtained from an intersection region of said local direction distribution data (d_0i and Δ

d_0i), as average distribution data, and further outputting an epicentral distance L from said observation point to said average central position X_r ;

calculating a weighted mean of said spatial distribution central position X_t and Δ

X_t, said average central position X_r, Δ

X_r and I_r, and a seismic electromagnetic field source region X_i, Δ

X_i and I_i calculated on the basis of said arrival bearing data (d and Δ

d) from each of said observation stations, thereby estimating a seismic electromagnetic field source region central position X₀, extension Δ

X₀ and intensity distribution I₀, and transmitting said central position data X₀ and extension Δ

X₀ to each of said observations stations;

estimating an earthquake magnitude M₀ on the basis of said regional characteristic signal C_r, local characteristic signal C_e, refined local characteristic signal C_f and epicentral distance L, together with a quantity indicating an extension of seismic eleetromagnetic field source regions, which is obtained on the basis of a set of said data central position X₀ and extension Δ

X₀ ;

obtaining abnormality occurrence time T₀ based on a function of time and pulse numbers of said regional characteristic signal C_r ; and

adding empirically set time Δ

T to said abnormality occurrence time T₀ obtained on the basis of said function of said time and pulse numbers of said regional characteristic signal C_r, local characteristic signal C_e and refined local characteristic signal C_f, thereby estimating earthquake occurrence time T_E.

2. An imminent earthquake prediction method according to claim 1, wherein said estimated earthquake occurrence time T_E, said central position data X₀, extension Δ

X₀ and intensity distribution I₀, and said earthquake magnitude M₀ are compared with meteorological data to check whether or not there is lightning, and also compared with crustal activity monitoring data to evaluate reliability of said earthquake occurrence time T_E, said central position X₀, extension Δ

X₀ and intensity distribution I₀, and said earthquake magnitude M₀.

3. An imminent earthquake prediction method according to claim 1, wherein a value A of area is calculated on the basis of the set of said central position X₀ and extension Δ

X₀ as a quantity indicating an extension of said seismic electromagnetic field source regions, and a first estimate M₁ of said earthquake magnitude is obtained on the basis of said value A, and wherein a second estimate M₂ of said earthquake magnitude is obtained on the basis of said regional characteristic signal C_r, local characteristic signal C_e and refined local characteristic signal C_f, together with said epicentral distance L, and said earthquake magnitude M₀ is finally obtained by calculating a weighted mean of said estimates M₁ and M₂.

4. An earthquake prediction method according to claim 3, wherein said first estimate M₁ of said earthquake magnitude is obtained by inserting said value A of area into the following formula:

M=aLogA+b (where a and b are constants) and said second estimate M₂ is obtained by inserting said regional characteristic signal C_r, local characteristic signal C_e, refined local characteristic signal C_f and epicentral distance L into the following empirical relation for earthquake magnitude;

space="preserve" listing-type="equation">M=f(C.sub.r, C.sub.e, C.sub.f, L).

5. An earthquake prediction method according to claim 1, wherein said earthquake occurrence time T_E is obtained by calculating a weighted mean characteristic value of a number of pulses of said characteristic signals C_e, C_f and C_r inputted per predetermined time interval to determine a weighted mean characteristic function C_m ;

obtaining an abnormality judgment criterion C₀ empirically set from a graph showing a relationship between said characteristic function C_m and time;

obtaining said time T₀ at which said weighted mean characteristic function C_m exceeds said abnormality judgement criterion C₀ as time to judge that an abnormality has occurred; and

adding said time Δ

T, which is empirically known to go before occurrence of an earthquake, to said time T₀.

6. An earthquake prediction system in which seismic electromagnetic field signals detected at observation stations installed at a plurality of places are processed and transmitted to a central station, and said signals are further processed at said central station to estimate earthquake occurrence time, an earthquake occurrence place, and an earthquake magnitude, thereby making earthquake prediction,

wherein each of observation stations installed in a plurality of places comprises:

local seismic electromagnetic field discriminating means for comparing a seismic electromagnetic field signal O_a, which is obtained by eliminating civil noise and atmospheric discharge noise from a seismic electromagnetic field signal detected with an electromagnetic field sensor of said observation station, with waveforms of known seismic electromagnetic field signals which have previously been stored in memory, and for extracting a known seismic electromagnetic field signal having the same waveform as that of said seismic electromagnetic field signal O_a, and outputting a noiseless local seismic electromagnetic field signal O_s, said means further outputting arrival bearing data (d and Δ

d) concerning a lightning electromagnetic field signal detected by lightning position detecting means;

local characteristic estimating means for outputting a local characteristic signal C_e including a number of pulses present in a predetermined time interval for each amplitude level of said seismic electromagnetic field signal O_s, and a maximum value and a minimum value of said signal O_s, and local direction distribution data (d_0i and Δ

d_0i) obtained from arithmetic mean of said arrival bearing data (d and Δ

d) captured in a predetermined period of time;

refined local characteristic estimating means for outputting a refined local characteristic signal C_f including a number of pulses for each amplitude level of said seismic electromagnetic field signal O_s which are present in a spatial window defined by a central direction d_s connecting an observation point of said observation station and a seismic electromagnetic field source region central position X₀ indicated by data sent from said central station, and a dispersion Δ

d_s corresponding to an extension Δ

X₀ of said seismic electromagnetic field source region central position X₀, and said refined local characteristic signal C_f further including a maximum value and a minimum value of said seismic electromagnetic field signal O_s but not including a noise component present outside said spatial window; and

means for transmitting a signal O_s having a frequency below a predetermined level among signals O_s outputted from said local seismic electromagnetic field discriminating means, said local characteristic signal C_e, said refined local characteristic signal C_f, said arrival bearing data (d and Δ

d), and said local direction distribution data (d_0i and Δ

d_0i) to said central station;

and wherein said central station comprises;

correlation processing means for obtaining a cross-correlation function R_ij (δ

t)=∫

O_si (t+δ

t)O_sj (t)dt between said signals O_s inputted from said observation stations with a delay time, smoothing said cross-correlation function R_ij (δ

t) by a moving average to obtain a smoothed cross-correlation function R_ij (t)=∫

ω

(t-τ

)R_sij (t)dτ

, obtaining a point of time at which said smoothed cross-correlation function reaches a maximum as delay time T_ij, and further obtaining a half-width H of said smoothed cross-correlation function;

tomography means for calculating, as an earthquake occurrence spatial point, an intersection of a plurality of hyperboloids of two sheets drawn as loci of points at which a propagation distance difference corresponding to said delay time T_ij is constant, with any pair of observation points defined as loci, and calculating a central position X_t of a spatial distribution of seismic electromagnetic field source regions, together with an extension Δ

X_t ;

regional seismic electromagnetic wave discriminating means for temporally matching time-series data of said seismic electromagnetic field signals O_s inputted with a delay time so that said delay time is eliminated, extracting from said signals O_s signals which are mutually present in an allowable arrival time interval Δ

T₁₂ determined on the basis of said half-width H inputted thereto from said correlation processing means, and for outputting a noiseless regional seismic electromagnetic field signal O_r ;

regional characteristic estimating means for outputting a regional characteristic signal C_r including a pulse number of said signal O_r for each amplitude level and a maximum value and a minimum value of said signal O_r, a seismic electromagnetic field source region average central position X_r, extension Δ

X_r and intensity distribution I_r, which are calculated from an intersection region of said local direction distribution data (d_0i and Δ

d_0i, and for calculating and outputting an epicentral distance L from said observation station to a position indicated by said average central position X_r ;

source region distribution estimating means for calculating a weighted mean of said average central position X_r, Δ

X_r and I_r from said regional characteristic estimating means, said spatial distribution central position X_t and Δ

X_t from said tomography means, and a seismic electromagnetic field source region data X_i, Δ

X_i and I_i calculated on the basis of said arrival beating data (d and Δ

d) from each of said observation stations, thereby estimating a seismic electromagnetic field source central position X₀, extension Δ

X₀ and intensity distribution I₀, and for transmitting said central position data X₀ and extension Δ

X₀ to said refined local characteristic estimating means of each of said observation stations;

means for estimating an earthquake magnitude M₀ on the basis of a quantity indicating an extension of seismic electromagnetic field source regions, which is obtained on the basis of a set of said central position data X₀ and extension Δ

X₀, said regional characteristic signal C_r, local characteristic signal C_e, refined local characteristic signal C_f and epicentral distance L;

means for obtaining abnormality occurrence time T₀ based on a function of time and pulse numbers of said regional characteristic signal C_r ; and

means for estimating earthquake occurrence time T_E by adding empirically known time Δ

T to said abnormality occurrence time T₀ obtained on the basis of said function of said time and input pulse numbers of said characteristic signals C_e, C_f and C_r.

7. An earthquake prediction system according to claim 6, further comprising synthetic decision means whereby said estimated earthquake occurrence time T_E from said occurrence time estimating means, said central position X₀, extension Δ

X₀ and intensity distribution I₀ from said source region distribution estimating means, and said earthquake magnitude M₀ from said magnitude estimating means are compared with meteorological data to check whether or not there is lightning, and further compared with crustal activity monitoring data to decide reliability of the estimation of said earthquake occurrence time T_E, said central position X₀, extension Δ

X₀ and intensity distribution I₀, and said earthquake magnitude M₀.

8. An earthquake prediction system according to claim 6, wherein said means for estimating an earthquake magnitude calculates a value A of area on the basis of the set of said central position data X₀ and extension Δ

X₀ as a quantity indicating an extension of said seismic electromagnetic field source regions, and obtains a first estimate M₁ of earthquake magnitude on the basis of said value A, and wherein said means for estimating an earthquake magnitude further obtains a second estimate M₂ of said earthquake magnitude on the basis of said regional characteristic signal C_r, local characteristic signal C_e and refined local characteristic signal C_f, together with said epicentral distance L, and finally obtains said earthquake magnitude M₀ by calculating a weighted mean of said estimates M₁ and M₂.

9. An earthquake prediction system according to claim 8, wherein said means for estimating an earthquake magnitude obtains said first estimate M₁ of said earthquake magnitude by inserting said value A of area into the following formula:

M=aLogA+b (where a and b are constants) and obtains said second estimate M₂ by inserting said regional characteristic signal C_r, local characteristic signal C_e, refined local characteristic signal C_f and epicentral distance L into the following empirical relation for earthquake magnitude;

space="preserve" listing-type="equation">M=f(C.sub.r, C.sub.e, C.sub.f, L).

10.

10. An earthquake prediction system according to claim 6, wherein said means for estimating earthquake occurrence time obtains said earthquake occurrence time T_E by calculating a weighted mean characteristic value of a number of pulses of said characteristic signals C_e, C_f and C_r inputted per predetermined time interval to determine a weighted mean characteristic function C_m ;

obtaining an abnormality judgement criterion C₀ empirically set from said characteristic function C_m ;

obtaining said time T₀ at which said characteristic function C_m exceeds said abnormality judgment criterion C₀ as time to judge that an abnormality has occurred; and

adding said time Δ

T, which is empirically known to go before occurrence of an earthquake, to said time T₀.