RU2463631C1 - Method to detect earthquake sources by network of seismic stations - Google Patents

Abstract

FIELD: mining.

SUBSTANCE: in an earthquake-prone area a network of seismic stations is arranged with seismographs from three-component conductometric pressure sensors. Pressure sensors are placed on a base perpendicular to a route of measurements, size of which is multiple to wavelength of a measured signal. Arrays of discrete counts of a signal of longitudinal and transverse wave speed ratio are generated from seismic stations under various azimuths of measurement route directions. Arrays of measurements are visualised in the form of Poincare diagrams, and the nature of the surveyed process is identified on their basis. The moment when a regular component appears in the diagram is identified as the start of the seismic process. The detected abnormality is located by several seismic stations by generation of their directivity patterns with two seismographs. A hypocentre of an earthquake source is detected as a point where radius-vectors of speeds of seismic waves from several seismic stations cross. Arrays of signal measurements are represented in the form of a phenomenological difference equation of a tracked process. Coefficients of the phenomenological equation are calculated, as well as dynamics of signal energy variation by coefficients from a sample to a sample. A time constant of the dynamic process is identified, as well as the stabilised signal value. The resulting signal attenuation on the route and relative attenuation are calculated. Time and magnitude of the expected shock is forecasted.

EFFECT: expanded interval of forecasting time, higher forecasting validity.

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Description

The invention relates to the field of seismology and may find application in national systems for observing and processing data from geophysical measurements for predicting earthquakes.

A reliable forecast of earthquakes is possible when establishing their root cause. One of the root causes of earthquakes is the pumping of the earth's crust by the additional energy of an upward flow of gases (H ₂ , He, CH ₄ ). The fact of emanation of gases from the earth's crust on the eve of a seismic shock [see, for example, patents RU No. 2204852, 2003, No. 2275659, 2006, No. 2302020, 2007]. Pumping the earth's crust with additional energy leads to a buildup of the earthquake source, accompanied by the propagation of ultra-low lithospheric waves from the hypocenter [see Scientific discovery No. 365, “The phenomenon of buildup of the earthquake source before a seismic shock”, Russian Academy of Natural Sciences, 2008].

There is a known method for predicting earthquakes, patent RU No. 2170446, 2001, by measuring the ultra-low lithospheric waves of the buildup of the earthquake source by space means of the Navstar system (GPS) - analogue.

, рассчитывают время удара, отсчитываемое от момента появления периодических отклонений координат:

и магнитуду

, где Т - период отклонения координат, ч, dek r - натуральный логарифм отношения амплитуд отклонения координат двух смежных периодов; d, l - коэффициенты регрессии.In the analogous method, receiving stations of the space navigation system are placed in a seismic region, spaced on an extended measuring base, they perform continuous high-precision measurement of the coordinates of the receiving points of the receiving stations, register the moment of occurrence of periodic deviations Δx _i , Δy _i , Δz _{i of the} coordinates of the points and track changes in these deviations in time, the hypothetical center of the focus is calculated as the point of intersection of the radius vectors in space, the length and the guides of the cosines, which are determined from the relations :

, calculate the impact time, counted from the moment of occurrence of periodic deviations of coordinates:

and magnitude

where T is the coordinate deviation period, h, dek r is the natural logarithm of the ratio of the coordinate deviation amplitudes of two adjacent periods; d, l - regression coefficients.

The disadvantages of the analogue method are:

- the presence of a hidden section of insensitivity (dead zone), limited by the mean square error of the GPS means, reducing the forecast interval;

- the inaccuracy of the regressive dependencies of calculating the time of impact and magnitude due to the dependence of the period (T) of the coordinate deviation from time.

The closest analogue to the claimed method is a method for the operational forecast of earthquakes, patent RU No. 2353957, G01V, 9/00, 2009

где B_x1(0), B_y1(0), B_x2(0), B_y2(0) - значения автокорреляционных функций сигналов в нуле в плоскостях x, y геофонов соответственно первого и второго пунктов.The closest analogue method includes recording seismic waves in the form of discrete samples of amplitudes (x _k , y _k ) of signals in mutually orthogonal planes at two points spaced on the measuring base, and the axis of the sensitive point sensors along the x coordinate orient the processing of the recorded data in the x direction by decomposing functional series, calculation of the autocorrelation functions of signals, in addition, registration of the Earth's natural acoustic noise in the form of acoustograms by means of geophones, having immersed in deep wells, visualization of a point set of samples of the data sequence in the form of Poincare diagrams in the planes (x _k, x _{k + 1} ) (y _k , y _{k + 1} ), tracking the dynamics of changes in the shape of the Poincare diagrams, determining the time constant of the transition process (T ), the forecast of the time of the expected impact t _y ≈4.7T, magnitude (M) from the relation lgt _y [days] = 0.54M-3.37, and the coordinates of the focus hypocenter are identified with the intersection point of the guiding cosines counted from the base axis:

where B _x1 (0), B _y1 (0), B _x2 (0), B _y2 (0) are the values of the autocorrelation functions of signals at zero in the x, y planes of the geophones of the first and second points, respectively.

The disadvantages of the closest analogue are:

- limited azimuths of detection of foci of prepared earthquakes (due to the uniqueness of the direction of the base) in various zones of the controlled region;

- the most stable sign-precursor of seismic shock is not determined as the dimensions of the zone of the prepared earthquake.

The problem solved by the claimed method is to increase the time interval of the prognosis for prediction by detecting early signs of anomalies on the measured path in the form of changes in the velocities of longitudinal and transverse waves, visualizing the dynamics of the transient process and increasing the reliability of the forecast by determining the size of the zone of the prepared earthquake.

и установившегося значения сигнала W_ycтi≈W_{0 i}·l^-4,7, расчет результирующего затухания сигнала на трассе ΔW_i≈W_{0 i}-W_{ycт i} и относительного затухания K_i=ΔW_i/W_{ycт I}, прогнозирования времени ожидаемого удара t_y≈4,7T_Σ и магнитуды M=r·ln[K_Σ], гдеThe problem is solved in that the method of detecting earthquake sources by a network of seismic stations includes the formation of arrays of discrete samples of the signal of the ratio of the velocities of the longitudinal (V _P ) and transverse (V _S ) waves of the seismic stations at different azimuths of the directions of the measurement routes, visualization of the measurement arrays in the form of Poincare diagrams and determination using the nature of the measured process, identification of the moment of occurrence of the regular component in the diagram with the beginning of the seismic process, direction finding of the detected anomaly seismic stations by forming their radiation patterns by two seismic receivers from three-component conductometric pressure sensors located on the base, with dimensions of a multiple wavelength of the measured signal perpendicular to the measurement path, determining the hypocenter of the earthquake source as the point of intersection of the radius vectors of the velocity of the seismic wavelengths of several seismic waveforms in the form of a phenomenological difference equation of the monitored process, the calculation of the coefficients f phenomenologically dynamics equations and signal power changes by the coefficients W _i (t) = a ² + b ² + c + d from sample to sample, the determination of the time constant T _i of the dynamic process

and the steady-state value of the signal W _ycti ≈W _{0 i} · l ^-4.7 , calculation of the resulting signal attenuation along the path ΔW _i ≈W _{0 i} -W _{yst i} and the relative attenuation K _i = ΔW _i / W _{yst I} , predicting the time of the expected impact t _y ≈4.7T _Σ and magnitudes M = r · ln [K _Σ ], where

Δt is the time interval between samples of measurements;

- среднегеометрическая постоянная времени измеряемого процесса по всем трассам;

- geometric mean time constant of the measured process over all paths;

- среднегеометрическое значение относительного затухания сигнала по всем трассам;

- geometric mean relative signal attenuation over all paths;

W _0i is the energy of the chaotic process on the measured path;

n is the number of stations in the network;

r is the regression coefficient;

a, b, c, d are the calculated coefficients of the phenomenological equation.

The invention is illustrated by drawings, where

figure 1 is a diagram of direction finding of earthquake sources by a network of seismic stations of the Kamchatka geophysical test site;

figure 2 - view of the function of the recorded signal (V _p / V _s ) in the observation interval;

figure 3 - visualization of Poincare diagrams of the functions of the signals: a) a random signal, b), c), d) with a regular component;

4 is a graphical interpretation of the field of solutions of the phenomenological equation: a) steady state, b), c), d) pumping (discharge) of energy in the medium on the measured paths;

figure 5 - the dynamics of the functions of the energy of the signals on the measured paths;

Fig.6 - dynamics of the attenuation of the signal from the size of the zone of the prepared earthquake;

7 is a functional diagram of a device that implements the method.

поперечных

где Е - модуль упругости Юнга, G - модуль сдвига, ρ - плотность среды [см. Курс физики. Г.А.Зисман, О.М.Тодес. Т.1, стр.301-302. М., Изд. Наука, 1964 г.]. В качестве сигнала предвестника изменения вязкоупругих характеристик среды выбрано отношение V_p/V_s, изменяющееся во времени и в пространстве от азимута трассы измерений. Одна из реализаций сигнала предвестника иллюстрируется графиком фиг.2. Известно [см., например, Р. Дуда, П.Харт. «Распознавание образов и анализ сцен». стр.319-331, перев. с англ., М., Мир, 1976 г.], что максимум информации о происходящих процессах содержится в образе объекта.The technical essence of the invention is as follows. One of the root causes of earthquakes is the degassing of the earth's crust and its pumping with additional energy of an upward flow of high pressure gases. Saturation of the earth's crust with a gas component changes its viscoelastic characteristics. The dispersion of rock density leads to a dispersion of the propagation velocities of lithospheric waves, i.e. a change in the relationship between the propagation velocities of longitudinal V _p and transverse V _s waves. The propagation velocity of longitudinal waves in the medium

transverse

where E is the Young's modulus of elasticity, G is the shear modulus, ρ is the density of the medium [see Physics course. G.A. Zisman, O.M. Todes. T.1, p. 301-302. M., ed. Science, 1964]. As a precursor signal for changes in the viscoelastic characteristics of the medium, the ratio V _p / V _{s is} selected, which varies in time and in space from the azimuth of the measurement path. One of the implementations of the precursor signal is illustrated in the graph of figure 2. It is known [see, for example, R. Duda, P. Hart. "Pattern recognition and scene analysis." p. 319-331, transl. from English., M., Mir, 1976], that the maximum information about the ongoing processes is contained in the image of the object.

Hidden information about the dynamics of the process at its early stage can be extracted from the electrical signal of the seismic background if the mathematical processing procedures visualize and track the change in the waveform (image of the object). To do this, programmatically, the data sequence is displayed in the form of Poincare diagrams [see, for example, A. Poincare. Selected Works in 3 volumes. Per. from French, ed. NN Bogolyubova, Science, 1974]. The Poincaré diagram is a graphical graphical representation of the N-values of a sequence, for example, X _k for k = 1, 2, 3 ... N in a two-dimensional field in which the ordinate of the point is the value of X _{k + 1} , and the abscissa is the previous value of X _k . Drawing alternately the points for k = 1, 2, 3 ... N on the graph, we get the point set X _{k + 1} , (X _k ), forming a figure by which we can judge the type of sequence (image of the object).

Poincare Chart Visualization Text

Figure 3 illustrates the Poincare diagram for various classes of signals:

a - White Gaussian noise, lack of information;

b - unstable state, chaotic oscillation;

c - steady state of the medium, a converging sequence of measurements;

g - catastrophic state of the medium, diverging sequence (energy discharge).

The very fact that a regular component appears in the Poincaré diagram (from the point set of the sample of measurements) indicates the beginning of the transition process to the release of energy by the energy-saturated focal zone.

где V_x, V_y - скорости продольных волн для данной сейсмостанции по координатам x, y. Для каждой сейсмостанции определяют направление

. Координаты аномалии находят как точку пересечения радиус-векторов скоростей от нескольких сейсмостанции. После обнаружения аномалии и ее пеленгации на измеряемых трассах осуществляют прогноз параметров ожидаемого сейсмического удара. Возникновение на измеряемой трассе газонасыщенного объема земной коры изменяет параметры регистрируемого сигнала. Динамика изменения параметров сигнала содержит всю информацию о предстоящем сейсмическом ударе. Для извлечения скрытой информации из последовательности выборок измерений используют их приближение феноменологическим уравнением в виде:The moment of occurrence in the seismic background of the regular component is identified with the occurrence of an anomalous zone of the prepared earthquake on the measured path. After detecting anomalies on the measurement path, it is direction-finding. It is known [see. G. Korn, T. Korn. "A Handbook of Mathematics for Scientists and Engineers" Sec. “Analytical Geometry”, pp. 73-74, translated from English, M, Nauka, 1971], that the position of the radius vector in space is completely determined by its cosine guides. It is known from analytic geometry that the cosine guide of a vector is equal to the ratio of its projection onto a given axis to the length of the vector. The length of the total velocity vector (length V) is found as the square root of the sum of the squares of its projections:

where V _x , V _y are the longitudinal wave velocities for a given seismic station along the x, y coordinates. For each seismic station determine the direction

. The anomaly coordinates are found as the point of intersection of the velocity radius vectors from several seismic stations. After detecting the anomaly and its direction finding on the measured paths, the parameters of the expected seismic impact are forecasted. The occurrence of a gas-saturated volume of the earth's crust on the measured path changes the parameters of the recorded signal. The dynamics of the signal parameters contains all the information about the upcoming seismic impact. To extract hidden information from a sequence of measurement samples, use their approximation by a phenomenological equation in the form:

x _k = f (x _k-1 , x _k-2 , ..., x _k-η , a) + ξ _k ; f∈F.

Here f (.) Is the desired function belonging to some chosen class of functions F; α is the state parameter, x _k = x (t _k ) is the observed parameter of the system, t _k , k = 1, 2 ... N is the discrete time, N is the sample size.

The method is developed in the class of power recurrent algebraic polynomials [see, for example, O.N. Novoselov. "Identification and analysis of dynamic systems." Ed. MGUL, M, 2006, pp. 34-44]

The general solution of the phenomenological equation was found in the form:

который определяется путем приравнивания нулю частных производных:The coefficients a, b, c, d were found from the minimum condition of the mean square deviation function

which is determined by equating to zero partial derivatives:

This system is a system of linear algebraic equations for the desired parameters a, b, c, d, where the coefficients for unknowns have the form:

Here N is the number of elements in the sequence x _k ; α, β = 0..4; p, q = 0..2; m [.] is the mathematical expectation operator. The system of linear equations was solved by a specialized program based on the Gauss method.

Algorithm Implementation Program Text

The occurrence on the measured path of a gas-saturated volume of the earth's crust of a prepared earthquake changes the parameters of the recorded signal. In the initial (stable) state, the ratio of speeds V _p / V _s is (Fig. 2) of the order of 1.4. Saturation of the earth's crust with a gas component changes the viscoelastic characteristics of the medium, while the ratio V _p / V _s tends to unity, and the signal itself disappears, its dispersion tends to zero.

Implementations of solutions for various azimuths of the measuring paths of seismic stations are illustrated by graphs of figure 4, where: a) the field of stable solutions inside the triangle a, b; b), c), d) - unstable states of pumping the medium with additional energy (excitation mode) or energy release by the medium.

The coefficients a, b at the first degrees of signal amplitudes (x _k , x _{k + 1} ...) have the physical meaning of a constant component.

Coefficients c, d at quadratic values characterize the energy of the variable component of the signal (dispersion).

The total energy of the signal is equal to the square of the constant component plus the variance, i.e. W _i (t) = [a ² + b ² + c + d].

One of the implementations of the signal energy function for the MKZ station in the observation interval (unstable state) is illustrated in the graph of FIG. 5

С вероятностью 0,99 экспонента достигает предельного значения при соотношении t/T_i=4,7. Признаком-предвестником землетрясения является увеличение размеров зоны подготавливаемого землетрясения (аномальной зоны фиг.1). Известна примерная зависимость ожидаемой магнитуды сейсмического удара (М) от размеров зоны подготавливаемого землетрясения [см., «Краткосрочный прогноз катастрофических землетрясений с помощью радиофизических наземно-космических методов». Доклады конференции ОИФЗ им. О.Ю.Шмидта. М.: РАН, 1998 г., стр.9].It is known that the physical quantity itself and its rate of change are connected by a differential equation of the first degree, the general solution of which is an exponential dependence [see, N. S. Piskunov. "Differential and integral calculus for technical schools." M .: Nauka, 1976, p. 458]. The exponential dependence has the property that from its discrete samples it is possible to restore the entire function. The exponential dependence of the attenuation of the signal on the measured path is illustrated by the graph of figure 5. The signal energy decreases from W _{0i of a} chaotic (Gaussian) process to a steady minimum W _yst.i , the value of which

With a probability of 0.99, the exponent reaches its limit value with the ratio t / T _i = 4.7. A sign of the earthquake precursor is an increase in the size of the zone of the prepared earthquake (anomalous zone of Fig. 1). The approximate dependence of the expected magnitude of seismic shock (M) on the dimensions of the zone of the prepared earthquake is known [see, “Short-term forecast of catastrophic earthquakes using radiophysical ground-space methods”. Conference reports O.Yu. Schmidt. M .: RAS, 1998, p. 9].

M≈ln [R, km].

Due to absorption in a gas-saturated volume (to a first approximation), we can assume that the signal energy W _i on the propagation path decreases in proportion to the size R _{i of the} anomalous zone. The absolute value of the signal attenuation on the path is calculated as ΔW _i = W _0i -W _yst.i = ΔW (R _i ).

Since the absolute value of absorption depends on the characteristics of the measurement equipment, it is necessary to operate with a relative characteristic

K _i = ΔW _i / W _yst.i.

и

где n - число сейсмостанций, задействуемых при измерениях.The zone of the prepared earthquake, confined to faults in the earth's crust, does not have symmetry, the dimensions of the anomalous zone R _i on the measured paths also depend on azimuths, therefore, when forecasting earthquakes, it is necessary to operate with geometric mean values of the calculated values, i.e.

and

where n is the number of seismic stations involved in the measurements.

Quantitative values of the calculated parameters are given below in the example implementation.

An example implementation of the method

The implementation of the method was carried out at the Kamchatka Geophysical Test Site RAS. The layout of the landfill is illustrated in figure 1. The range includes 6 seismic stations: Russkaya (RUS), Petropavlovsk (PET), Shipunsky (SPN), Cape Kozlova (MKZ), Krutoberegovo (KVT), Avacha (AVH).

Seismic monitoring stations record the arrival of longitudinal and transverse waves from each earthquake that occurred in the focal zone located 150 km from the coast of the Kamchatka Peninsula.

The focal zone of Kamchatka is a junction of continental and oceanic plates, the last of which carries out movement under the continental plate. To the north, in the monitoring zone of the KVT stations, there is a junction of these plates with a more northern one, i.e. triple articulation occurs, the seismic activity of which is very high. The focal zone of earthquakes is from the north of Kamchatka to the south, right up to Indonesia. In monitoring the environment, the stations RUS, PET, KVT, MKZ, SPN, AVH used data obtained only from local earthquakes.

и сигнал пеленга аномалии (V_px/дл.V_p). Результирующие сигналы от канального коммутатора 13 оцифровывают в АЦП 14, 15, записывают в буферное ЗУ 16 для последующего ввода данных в компьютер 17 в стандартном наборе элементов: процессор 18, оперативное ЗУ 19, винчестер 20, дисплей 21, принтер 22, клавиатура 23. Компьютеры 17 объединены в локальную вычислительную сеть, и обеспечена синхронизация их работы во времени.Functional diagram of a measurement system that implements the method is illustrated in Fig.7. The measurement system (Fig. 7) contains six seismic stations 1 ... 6 located in the Kamchatka region. Each of the seismic stations, for the azimuths of the measurement paths in the focal zone, contains a group of two three-component seismic receivers, 7, 8, whose sensitivity axes of the same name components are mutually parallel. The seismic receivers are located on the measuring base 9, which is a multiple of the average wavelength of the measured spectrum. The bases are perpendicular to the measured paths. The seismic receivers are installed buried coaxially with each other. Through the built-in amplifiers 10, 11, 12, the signals from the output of the geophones are fed to the corresponding inputs of the channel switch 13. The channel switch implements the function of the relations of the sums of signals

and a bearing signal of the anomaly (V _{px /} dl. V _p ). The resulting signals from the channel switch 13 are digitized in the ADC 14, 15, recorded in the buffer memory 16 for subsequent data input into the computer 17 in a standard set of elements: processor 18, operational memory 19, hard drive 20, display 21, printer 22, keyboard 23. Computers 17 are integrated into a local area network, and their work is synchronized over time.

All elements of the device are existing technical developments. The device used elements of vibration measuring equipment from Bruel & Kjairi ENDEVCO, Denmark, the following models: built-in amplifiers 10, 11, 12 models 2626, 2628; channel switch, ADC, buffer memory (elements 13, 14, 15, 16) - multifunction block 3560-L.

- скорость колебательного движения, u - смещение частиц от положения равновесия в процессе колебательного движения. Поскольку давление во фронте сейсмической волны пропорционально скорости, для ее измерения на сейсмостанциях используют датчики давления. Известен класс устройств мембранного типа, позволяющих измерять инфразвуковые колебания земной коры (см., например, «Кондуктометрический датчик колебаний». Патент RU №2055352, G01N, 27/02, 1996 г.). Датчик имеет высокую чувствительность и линейность выходной характеристики в области инфрачастот 0,1…100 Гц, быстродействие 100ms. Промышленная разработка кондуктометрического датчика представляет собой трехкомпонентный сейсмоприемник (см., например, «Способ определения гипоцентра нефтегазового месторождения». Патент RU №2150719, G01V, 1/100, 2000 г.). Он может использоваться в любой пространственной ориентации, т.е. осуществлять измерения во взаимно ортогональных плоскостях.A seismic wave is characterized by an excess pressure P [n / m ² ] = pc | υ |, where p is the density of the medium, c is the speed of the acoustic waves,

is the speed of oscillatory motion, u is the displacement of particles from the equilibrium position in the process of oscillatory motion. Since the pressure at the front of the seismic wave is proportional to the speed, pressure sensors are used to measure it at seismic stations. A known class of membrane-type devices that can measure infrasonic vibrations of the earth's crust (see, for example, "Conductometric vibration sensor". Patent RU No. 2055352, G01N, 27/02, 1996). The sensor has high sensitivity and linearity of the output characteristic in the field of infra-frequencies 0.1 ... 100 Hz, speed 100ms. The industrial development of the conductivity sensor is a three-component seismic receiver (see, for example, “Method for determining the hypocenter of an oil and gas field.” Patent RU No. 2150719, G01V, 1/100, 2000). It can be used in any spatial orientation, i.e. take measurements in mutually orthogonal planes.

Analysis of seismic data was carried out for the period from 01.01.2001 to 31.12.2004. The time intervals during which the changes in the state of the environment were considered were ~ 16, 8, 4, 2 days before the earthquake and, respectively, 2, 4, 8, 16 days after. Signal processing at each station was carried out using registered seismic waves, taking into account the direction of their arrival, i.e. different azimuths were selected (azimuth can have a value from 0 to 360).

A complete cycle of software processing of the signals of seismic stations (MKZ, RUS) was carried out according to the claimed operations of the method. The result of calculating the coefficients of the phenomenological equation of samples of measurements of MKZ seismic stations is presented in the table.

The function of changing the signal energy on the MKZ station path over the entire interval of measurement samples is illustrated in the graph of FIG. 5.

The calculated energy of Gaussian noise is W _0i = 0.42 mW.

Seismic process time constant

The _steady-state value of the signal energy is W _yst = W _0i · e ^-4.7 = 0.0038.

The absolute absorption of signal energy by the anomalous zone is ΔW = W _0i -W _yst = 0.416.

.Relative Signal Attenuation

.

The expected magnitude of the seismic impact: M ₁ = r · ln | K ₁ | = 1.2 ln | 112 | = 5.7.

The expected seismic impact time t _y = 4.7T ₁ ≈3.9 days.

Similar calculations for the same time intervals of RUS station yielded results: K ₂ = 89, M ₂ = 5.4, t _y = 3.4 days.

.The geometric mean value of the time constant of the seismic process for 2 seismic stations

.

, M_Σ=5,55 баллов.The average signal attenuation in the anomalous zone

, M _Σ = 5.55 points.

Since the dimensions of the anomalous zone are not directly measured, and the dependence of the signal attenuation on the zone sizes is used, the correction regression coefficient r is determined when calculating M. In the interval of observation times [2001-2003] from the a posteriori data of the earthquakes in the range M∈ [5.0 ... 7.3] points, the regression value r = 1.2 was obtained.

The effectiveness of the method is characterized by statistical stability of the measurement results and, as a result, high reliability, scale of the territory covered by monitoring and a large interval of time of proactive forecast of the upcoming seismic shock.

Claims (1)

A method for detecting earthquake sources by a network of seismic stations, including the formation of arrays of discrete samples of the signal of the ratio of the velocities of longitudinal (V _P ) and transverse (V _S ) waves from seismic stations at various azimuths of the directions of the measurement paths, visualizing the measurement arrays in the form of Poincare diagrams and determining the nature of the measured process from them , identification of the moment of appearance of the regular component in the diagram with the beginning of the seismic process, direction finding of the detected anomaly by several seismic stations by means of of their radiation patterns by two seismic receivers from three-component conductometric pressure sensors placed on the basis of a multiple of the wavelength of the measured signal, perpendicular to the measurement path, determining the hypocenter of the earthquake focus as the point of intersection of the radius vectors of the velocity of the seismic waves from several seismic stations, and representing the signal measurement arrays as a phenomenon the difference equation of the process being monitored, the calculation of the coefficients of the phenomenological equation and d the dynamics of the signal energy by the coefficients W _i (t) = a ² + b ² + c + d from sample to sample, determination of the time constant T _{i of the} dynamic process

and the steady-state value of the signal W _{mouth i} ≈W _0i e ^-4.7 , calculation of the resulting signal attenuation along the path ΔW _i ≈W _0i -W _{mouth i} and the relative attenuation K _i = ΔW _i / W _{mouth i} , predicting the time of the expected impact t _y ≈ “4.7T _Σ and magnitudes M = r · ln [K _Σ ],
where Δt is the time interval between samples of measurements;

- geometric mean time constant of the measured process over all paths;

- geometric mean relative signal attenuation over all paths;
W _0i is the energy of the chaotic process on the measured cable;
n is the number of stations in the network;
r is the regression coefficient;
a, b, c, d are the calculated coefficients of the phenomenological equation.

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