Information processing device, information processing method, and program

Abstract

To improve convenience in various estimations related to a tsunami.SOLUTION: A simulation sound wave waveform information DB 80 preliminarily stores unit fault sound wave waveform information showing sound wave waveforms respectively observed at a plurality of points when tsunamis occur at a prescribed unit fault. An observed sound wave waveform information acquisition part 521 acquires observed sound wave waveform information showing a plurality of observed sound wave waveforms respectively observed by sound wave observation devices 2 when the tsunamis actually occur. A tsunami wave source area estimation part 523 estimates each of one or more unit faults as a wave source area by respectively comparing observed sound wave waveform information with the unit fault sound wave waveform information of each of the plurality of unit faults. Also, the tsunami wave source area estimation part 523 specifies tsunami scales of tsunamis that actually occur on the basis of one or more wave source areas. A notification control part 526 outputs information showing the tsunami scales to execute the control of notification.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Conventionally, there is a technique for estimating the source area of ​​a tsunami wave based on the results of observations using observation devices such as ocean bottom pressure gauges, GPS wave gauges, and marine radar (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-089316 Summary of the Invention [Problem to be solved by the invention]

[0004] However, there is a problem in that the installation and operation of the above-mentioned conventional observation equipment, such as the ocean bottom pressure gauge, GPS wave gauge, and marine radar, is very expensive. It was also desirable to estimate information such as the time of arrival of the tsunami and its height as early as possible before the tsunami arrived. Thus, there was a need for improved convenience in various tsunami-related estimations.

[0005] The present invention has been made in light of these circumstances, and aims to improve the convenience of various tsunami-related estimations. [Means for solving the problem]

[0006] In order to achieve the above object, an information processing device according to one aspect of the present invention comprises: An information processing device that can access a database in which information indicating sound waveforms observed at each of a plurality of points when a tsunami occurs in a predetermined unit fault is stored in advance for each of a plurality of unit faults as unit fault sound waveform information (for example, information in the form of a Green's function), an observed waveform acquisition means for acquiring observed sound waveform information indicating a plurality of observed sound waveforms observed at a plurality of points when a tsunami actually occurs; a wave source region estimation means for estimating each of one or more unit faults as a wave source region by comparing the observed sound wave waveform information with each of the unit fault sound wave waveform information for each of the plurality of unit faults; A tsunami scale determination means for determining the scale of the tsunami that actually occurred based on one or more of the wave source areas; output control means for executing control to output information indicating the tsunami scale; Equipped with. [Effects of the Invention]

[0007] According to the present invention, it is possible to improve the convenience of various estimations related to tsunamis. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram showing an example of an outline of information processing executed by an information processing system including a server according to an embodiment of the information processing device of the present invention; [Figure 2] FIG. 2 is a diagram showing an example of the timing of the information processing in FIG. 1 from the occurrence of a tsunami to its arrival. [Figure 3] 2 is a block diagram showing an example of a hardware configuration of a server in the system that executes the information processing shown in FIG. 1. FIG. [Figure 4] 4 is a functional block diagram showing an example of a functional configuration for executing a simulation process and a tsunami detection process, among the functional configurations of the server in FIG. 3. FIG. [Figure 5] FIG. 6 is a flowchart showing the flow of processing in FIGS. 1, 2 and 5. [Figure 6]5 is a diagram showing an example of an observed sound wave waveform acquired by the server of FIG. 4. FIG. [Figure 7A] FIG. 10 is a diagram showing an example of a process for extracting a waveform of a tsunami component from an observed sound wave waveform. [Figure 7B] FIG. 10 is a diagram showing an example of a process for extracting a waveform of a tsunami component from an observed sound wave waveform. [Figure 8A] FIG. 1 is a diagram showing an example of estimating a tsunami source area. [Figure 8B] FIG. 1 is a diagram showing an example of estimating a tsunami source area. [Figure 9A] FIG. 1 is a diagram showing an example of estimating a tsunami source area. [Figure 9B] FIG. 1 is a diagram showing an example of estimating a tsunami source area. [Figure 10A] FIG. 10 is a diagram showing an example of a comparison between the observation results of the GPS wave meter of the present invention and the simulation results. [Figure 10B] FIG. 10 is a diagram showing an example of a comparison between the observation results of the GPS wave meter of the present invention and the simulation results. [Figure 10C] FIG. 10 is a diagram showing an example of a comparison between the observation results of the GPS wave meter of the present invention and the simulation results. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0010] An information processing system (for example, the information processing system in FIG. 3) including a server (for example, server 1 in FIG. 1) according to an embodiment of the information processing device of the present invention estimates the source area of ​​a tsunami and predicts the size of the tsunami that will arrive using observed sound waves. Below, an overview of the information processing system (hereinafter referred to as "this information processing system") including a server according to an embodiment of the information processing device of the present invention will be described using FIGS. 1 and 2. FIG. 1 is a diagram showing an example of an outline of information processing executed by an information processing system including a server according to an embodiment of the information processing device of the present invention.

[0011] First, as shown on the right side of Figure 1, this information processing system simulates the sound waveform that propagates when a tsunami occurs at a specified unit fault, and thereby generates in advance information (hereinafter referred to as "unit fault sound waveform information") that indicates the sound waveform that will be observed at each of multiple points when the tsunami occurs. Hereinafter, the process of generating information indicating the sound waveforms observed at each of a plurality of points when a tsunami occurs at a specified unit fault through a simulation in advance will be referred to as "simulation process."

[0012] The "sound waveform" referred to here refers to the waveform of the air pressure fluctuations that occur with a tsunami and propagate through the atmosphere. In other words, the sound waveform is not limited to the waveform of sound waves in the narrow sense (audible sound waves) that humans hear as sound. Specifically, the "sound waves" referred to here are also known as micro-pressure waves, infrasound, low-frequency sound, infrasound, etc. As will be explained in more detail later, when a tsunami occurs, the sea level rises and falls. This causes local fluctuations in atmospheric pressure near the sea level. Furthermore, these fluctuations in atmospheric pressure propagate to the surrounding area. These propagating pressure fluctuations are the "sound waves" mentioned above, and the waveform associated with these sound waves is the "sound waveform." When a tsunami actually occurs, by placing a barometer or low-frequency sonic meter at an observation point on the ground, the change in atmospheric pressure at that observation point can be observed as sound waves. In this way, the term "sound wave" has a broad definition and can be understood as a relatively low-frequency pressure change in the atmosphere. In the following, we will continue our explanation using the broad terms "sound wave" and "sound waveform."

[0013] Furthermore, as will be described in more detail later, a "unit fault" refers to a specific unit of stratum or bedrock that can generate a tsunami. In addition, in the simulation process, the above-mentioned simulation is performed for each of the plurality of unit faults, and unit fault sound waveform information for each of the plurality of unit faults is generated. Hereinafter, the group of unit fault sound waveform information for each of the plurality of unit faults generated in advance by the simulation process in this manner will be referred to as "simulation sound waveform information." However, in FIG. 1, for the sake of simplicity, one unit fault TDS and its unit fault sound waveform information are shown as a unit fault in the simulation process.

[0014] As shown on the left side of Figure 1, this information processing system estimates the tsunami source area using an inversion method based on information indicating the sound waveforms observed at multiple locations when a tsunami actually occurs (hereinafter referred to as "observed sound waveform information") and the simulated sound waveform information described above. Furthermore, this information processing system predicts the scale of the tsunami in the tsunami source area and the tsunami that will arrive in coastal areas, etc. Hereinafter, the process of estimating the tsunami source area using the inversion method when a tsunami actually occurs will be referred to as "tsunami detection process."

[0015] Although details will be explained later, the "tsunami source region" refers to the area where the tsunami occurred. In other words, the tsunami source region is the area where the uplift or subsidence of the seabed that causes the tsunami occurs. When a tsunami actually occurs, it occurs simultaneously or in a chain reaction on multiple unit faults. In other words, the tsunami source region refers to the area consisting of multiple unit faults that generated such a tsunami. However, in Figure 1, for the sake of simplicity, the tsunami wave source area in the tsunami detection process is shown as consisting of one unit fault, and one unit fault TD and tsunami TT are shown.

[0016] The above-mentioned simulation processing and tsunami detection processing will be described in more detail below. That is, the server 1 of this information processing system executes the following processing, for example, as the above-mentioned simulation processing. That is, when an earthquake or the like occurs at a certain unit fault TDS, resulting in a tsunami TTS, the server 1 simulates the acoustic waveforms HS1 to HS4 observed at each of multiple (four in the example of Figure 1) points R1 to R4. The server 1 stores information indicating the acoustic waveforms HS1 to HS4 observed at each of the multiple points R1 to R4 in the simulation when a tsunami TTS occurs at this unit fault TDS as unit fault acoustic waveform information in a database, for example, in the form of information in the form of a Green's function.

[0017] In addition, unit fault sound waveform information is generated by simulation for each of multiple unit faults within a specified area, not just for one unit fault TDS shown on the right side of Figure 1, and a group of multiple unit fault sound waveform information within the specified area is stored in advance in a database as simulated sound waveform information. Any predetermined area can be used, such as an area including the Pacific Circum-Pacific orogenic belt or an area where a fault that is believed to have the potential to cause a major earthquake (such as a Nankai Trough earthquake) is present.

[0018] Next, as shown on the left side of Figure 1, when an earthquake or the like actually occurs in the tsunami source region (a unit fault TD in Figure 1) and a tsunami TS occurs as a result, atmospheric vibrations generated by the unit fault TD and the tsunami TT occurring in its vicinity are propagated to the surrounding areas at each of multiple points R1 to R4. As a result, sound waveforms HK1 to HK4 are obtained at multiple points R1 to R4. That is, when a tsunami actually occurs, the server 1 acquires observed sound waveform information indicating a plurality of sound waveforms HK1 to HK4 observed at a plurality of points R1 to R4, respectively.

[0019] Then, in the server 1, the tsunami wave source area is estimated by an inversion method based on the observed sound wave waveform information and the simulated sound wave waveform information. That is, as shown in FIG. 1, when a tsunami TT is actually generated by a unit fault TD, the acoustic waveform of the tsunami TT generated by the unit fault TD is included in the observed acoustic waveform information.

[0020] Therefore, the server 1 estimates the tsunami wave source area by comparing the observed sound waveform information with the simulated sound waveform information. That is, the server 1 estimates a combination of sound waveforms HS1 to HS4 generated in one or more unit fault TDSs that reproduces the actually observed sound waveforms HK1 to HK4. At this time, the server 1 also estimates the scale of the sound waves generated at each of one or more unit faults TDS that reproduce the actually observed sound waveforms HK1 to HK4. By finding the combination, the tsunami wave source area is estimated. In this way, the server 1 can estimate which tsunami source area (unit fault TD in the example of Figure 1) the sound waves generated by the tsunami TS are from. The server 1 can also estimate the size of the tsunami TS generated by each unit fault included in which tsunami source area (i.e., the scale of the tsunami TS in the tsunami source area (size above and below the sea surface and its distribution)).

[0021] As mentioned above, in the tsunami source area, tsunamis occur not only at one unit fault TD, but also at multiple unit faults simultaneously or in a chain reaction. The server 1 can use an inversion method to output which of a plurality of unit faults a tsunami has occurred on, based on the observed sound wave waveform information and the simulated sound wave waveform information. In this way, for example, the comparison result that a tsunami has occurred on M (M is a positive integer not greater than N) unit faults out of N (N is a positive integer not less than 2) unit faults is output by the server 1.

[0022] In this way, in the simulation process, the information processing system generates simulated sound waveform information consisting of multiple unit fault sound waveform information in advance by simulating the propagation of sound waves. Then, in the tsunami detection process, the information processing system can estimate the tsunami wave source area by comparing observed sound waveform information consisting of sound waveforms observed at the time of the earthquake with the simulated sound waveform. Then, as will be described in detail later, the server 1 can identify the scale of the tsunami generated from one or more tsunami source areas estimated in this way.

[0023] Next, the timing at which the information processing of FIG. 1 is executed in response to an actual tsunami occurrence will be described with reference to FIG. Figure 2 is a diagram showing an example of the timing of the information processing from the generation of the tsunami to its arrival in Figure 1. As shown on the time axis at the bottom of Figure 2, the flow of information processing will be explained from left to right in Figure 2.

[0024] First, in step ST11, a tsunami occurs, i.e., the sea level in the tsunami source area rises or falls. Next, in step ST12, sound waves are generated from the tsunami in the tsunami source area. That is, as a result of the sea level in the tsunami source area rising or falling in step ST11, sound waves are generated from the sea level according to the magnitude of the rise or fall of the sea level.

[0025] In this way, the tsunami generated in step ST11 and the sound waves generated almost simultaneously in step ST12 both propagate in all directions. The sound waves propagate faster than the tsunami. Therefore, the sound waves reach the coastline before the tsunami reaches the coastline in step ST18, which will be described later. When the distance between the tsunami source area and the coast and the distance from the coast to a point on land meet certain conditions, the sound waves also reach the observation equipment at the ground level (points R1 to R4 in the example in Figure 1). For example, if the distance between the tsunami source area and the coast is several tens of kilometers and the distance from the coast to a point on land is several kilometers, the sound waves also reach the observation equipment first.

[0026] Next, in step ST13, sound waves are observed at points on the ground inside the coast (points R1 to R4 in the example of FIG. 1). Information on sound waves observed on the ground is appropriately transmitted to the server 1. That is, the server 1 acquires observed sound wave waveform information.

[0027] Next, in step ST14, the tsunami wave source area is estimated. That is, the server 1 estimates the tsunami wave source based on the observed sound wave waveform information and the simulated sound wave waveform information. As a result, as shown in step ST15, the estimated tsunami scale is reported before the tsunami reaches the coastal area in step ST18 described later. That is, the server 1 can estimate the tsunami scale in the tsunami wave source area and report the estimated result to people in coastal areas, etc., as information on the tsunami scale.

[0028] Next, in step ST16, a tsunami arrival prediction is performed using a tsunami propagation simulation. That is, based on the information on the tsunami source area estimated in step ST14, the server 1 predicts how the tsunami will propagate from the tsunami source area and what time and height the tsunami will reach the coastal area. As a result, as shown in step ST17, the estimated result of the incoming tsunami is notified before the tsunami reaches the coastal area in step ST18 described later. That is, the server 1 estimates (predicts) the tsunami that will arrive at the predicted coastal area, and can notify people in the coastal area of ​​the estimated result about the incoming tsunami.

[0029] After that, as shown in step ST18, the tsunami actually reaches the coast. In this way, by using sound waves, this information processing system can process information and provide various information about the tsunami before it actually reaches the coast.

[0030] The information processing system described above with reference to FIGS. 1 and 2 has the following advantages. First, this information processing system can keep installation and operation costs low. Traditionally, tsunami source areas have been estimated based on tsunami observation values ​​obtained from observation equipment such as ocean bottom pressure gauges, GPS wave gauges, and marine radar. These conventional observation devices must be installed on or underwater, which means that installation and operation of the observation equipment is very expensive. In contrast, as mentioned above, this information processing system is equipped with a ground-based observation device that measures sonic waveforms. This type of ground-based observation device requires less installation and maintenance costs than conventional observation devices, so installation and operation costs can be kept low. Although the acoustic wave observation device can be installed partially or entirely on the sea, the following description will be given assuming that the entire device is located on land, as shown in Figure 1, etc.

[0031] There is a conventional method for estimating the arrival time and scale of a tsunami based on the time difference between tsunami waveforms observed at multiple points above and below sea level. However, this conventional method requires a significant amount of cost for the operation of observation equipment. Furthermore, with this conventional method, it is not possible to observe the waveform before the tsunami reaches the observation equipment, so it takes time before the tsunami can be estimated. In contrast, this information processing system uses a method to estimate the arrival time and scale of a tsunami by using sound waveforms (observed sound waveform information) observed at multiple points on land, rather than above or underwater. As a result, this information processing system makes it relatively easy to install and maintain observation equipment, and the cost of operating the observation equipment can be kept relatively low. Furthermore, by combining this information processing system with conventional observations (surface and underwater observations), multiplexing (fusion inversion) can be performed inexpensively. As a result, this information processing system can improve the speed and accuracy of estimating tsunami source areas and tsunami scale.

[0032] Furthermore, because the observation equipment for this information processing system is installed on land, there is little risk of it being damaged or shut down by a tsunami or other disaster. In other words, conventional observation equipment directly observes the tsunami itself from above or below the sea. Therefore, if a tsunami actually occurs, there is a possibility that the observation equipment could be damaged by the tsunami, or that the equipment used to send and receive observation data (such as radio wave transmission and reception units and signal transmission wiring) could be damaged. In contrast, the information processing system uses observation equipment located on land and observations are made before the tsunami arrives, so there is little risk of the system being damaged by a tsunami or other disaster and becoming inoperable. This means that there is a higher chance that various tsunami-related information can be estimated correctly.

[0033] Furthermore, as mentioned above, sound waves travel faster than tsunamis (fluctuations in sea level). Therefore, this information processing system may be able to estimate the source of a tsunami faster than conventional observation equipment (GPS wave gauges, DONET, and marine radar). For example, suppose the distance between the tsunami source area and the coast is several tens of kilometers, the distance from the coast to the ground-based observation equipment of this information processing system is several kilometers, and the distance from the coast to conventional offshore observation equipment is several kilometers. In this case, the time from the occurrence of a tsunami until the sound waves reach the ground-based observation equipment of this information processing system may be shorter than the time it takes for the tsunami to reach conventional offshore observation equipment. In other words, information processing can be started when the time it takes for the tsunami to reach the coast is longer, and information about the tsunami can be reported to coastal areas, etc., more quickly.

[0034] The outline and advantages of this information processing system have been explained above using Figures 1 and 2. Below, the configuration of the server that performs information processing will be explained using Figures 3 and 4.

[0035] FIG. 3 is a block diagram showing an example of a hardware configuration of a server in the system that executes the information processing shown in FIG.

[0036] The server 1 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a memory unit 18, a communication unit 19, and a drive 20.

[0037] The CPU 11 executes various processes according to a program recorded in the ROM 12 or a program loaded from the storage unit 18 into the RAM 13 . The RAM 13 also stores data and the like necessary for the CPU 11 to execute various processes.

[0038] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. An input unit 16, an output unit 17, a memory unit 18, a communication unit 19, and a drive 20 are connected to the input / output interface 15.

[0039] The input unit 16 is configured with, for example, a keyboard and is used to input various information. The output unit 17 is configured with a display such as a liquid crystal display, a speaker, etc., and outputs various information as images and sounds. The storage unit 18 is configured with a DRAM (Dynamic Random Access Memory) or the like, and stores various data. The communication unit 19 communicates with other devices (for example, the acoustic observation device 2 in FIG. 4) via a network including the Internet.

[0040] Removable media 31, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately attached to the drive 20. A program read from the removable media 31 by the drive 20 is installed in the storage unit 18 as necessary. Furthermore, the removable media 31 can also store various data stored in the storage unit 18 in the same manner as the storage unit 18.

[0041] 3, various processes including simulation processing and tsunami detection processing can be executed, and as a result, the above-described service can be provided.

[0042] FIG. 4 is a functional block diagram showing an example of a functional configuration for executing the simulation process and the tsunami detection process, among the functional configurations of the server in FIG.

[0043] As shown in FIG. 4, when the server 1 executes a simulation process, a simulation processing unit 51 functions in the CPU 11. When the server 1 executes the tsunami detection process, the tsunami detection processing unit 52 functions in the CPU 11.

[0044] A simulation sound waveform information DB 80 is provided in one area of ​​the storage unit 18 of the server 1. The simulation sound waveform information DB 80 stores and manages a group of a plurality of unit tomographic sound waveforms.

[0045] The simulation processing unit 51 generates unit tomographic sound waveform information for each of a plurality of unit tomographic sections in a predetermined area by simulation in advance. Then, the simulation processing unit 51 stores a group of the plurality of unit tomographic sound waveform information in the predetermined area as simulation sound waveform information in the simulation sound waveform information DB 80. Specifically, for example, a unit fault acoustic waveform is generated by placing a unit fault of a predetermined size in a hypothetical tsunami fault zone in the ocean (a predetermined area in the explanation of Figure 1), and simulating the acoustic propagation to generate the acoustic waveform observed at each observation point when each unit fault rises by a certain amount.

[0046] The acoustic wave observation devices 2-1 to 2-n acquire infrasound waves generated by the tsunami. The sonic observation devices 2-1 to 2-n are placed at multiple locations over a wide area on the ground, which improves the accuracy of estimating the tsunami source area. Furthermore, tsunamis, that is, sound waves caused by rising and falling sea levels, are infrasonic waves, and so the acoustic wave observation devices 2-1 to 2-n are devices capable of observing infrasonic waves. In the following description, when there is no need to distinguish between the sonic observation devices 2-1 to 2-n, they will be collectively referred to as the "sonic observation device 2."

[0047] Each of the acoustic wave observation devices 2-1 to 2-n includes an acoustic wave measurement unit 201, a time management unit 202, and an observed acoustic wave waveform information transmission control unit 203. Below, the functions of the acoustic wave measurement unit 201, the time management unit 202, and the observed acoustic wave waveform information transmission control unit 203 will be explained.

[0048] The sound wave measuring unit 201 measures sound waves including infrasound waves generated by a tsunami. Here, the infrasound waves are not sound waves in the human audible range such as those detected by a microphone, but can be considered as fluctuations in atmospheric pressure. Therefore, for example, the sound wave measurement unit 201 has a barometer capable of measuring sound waves with predetermined frequency characteristics, and continuously measures the sound waves acquired via the barometer at a predetermined sampling interval. Specifically, for example, it is preferable that the sampling interval be 1 Hz or more. An example of an infrasonic wave observed by the sound wave measuring unit 201 will be described later with reference to FIG.

[0049] The time management unit 202 manages accurate time using GPS satellite signals, etc. This ensures that the waveform times are accurately synchronized, making it possible to compare the time history waveforms of infrasound waves at multiple points.

[0050] The observed sound waveform information transmission control unit 203 controls the appropriate transmission of information including the infrasonic waves acquired by the sound wave measurement unit 201 and the time information managed by the time management unit 202 to the server 1 as observed sound waveform information.

[0051] The tsunami detection processing unit 52 collects observed sound wave waveform information acquired by sound wave observation devices 2 placed at multiple locations, and performs processing such as extracting the waveform of tsunami components and estimating the wave source. The tsunami detection processing unit 52 includes an observed sound wave waveform information acquisition unit 521, a tsunami waveform extraction unit 522, a tsunami wave source region estimation unit 523, a linear superposition unit 524, a tsunami propagation simulation unit 525, and a notification control unit 526. Below, the functions of the observed sound wave waveform information acquisition unit 521, the tsunami waveform extraction unit 522, the tsunami wave source region estimation unit 523, the linear superposition unit 524, the tsunami propagation simulation unit 525, and the notification control unit 526 will be described.

[0052] The observed sound wave waveform information acquisition unit 521 acquires observed sound wave waveform information measured by the sound wave observation devices 2 at multiple locations. That is, for example, the observed sound wave waveform information acquisition unit 521 collects data at least every minute, which makes it possible to quickly predict the tsunami height and arrival time after the tsunami occurs.

[0053] The tsunami waveform extraction unit 522 extracts tsunami component waveforms by removing trend components resulting from atmospheric pressure patterns and noise components acquired from sound sources around the observation point, which are included in the observed sound wave waveform information measured by each of the multiple sound wave observation devices 2. Specifically, for example, a numerical filter is used to remove noise components acquired from sound sources around the observation point. An example of extracting the waveform of a tsunami component will be described later with reference to FIG.

[0054] The tsunami wave source region estimation unit 523 estimates the tsunami wave source region by comparing the tsunami component waveform extracted by the tsunami waveform extraction unit 522 with a unit fault sound wave waveform prepared in advance. Specifically, based on the tsunami component waveform extracted by the tsunami waveform extraction unit 522 and the unit fault sound waveform contained in the simulation sound waveform information, the tsunami at each unit fault is estimated by calculating x (initial water level) that minimizes E (sum of squared residuals) using the following equations (1) to (3). Here, y is the tsunami waveform observed at times 1 to t. Also, x is the initial water level of the unit fault (unit faults 1 to n). Also, A is the tsunami waveform (η) due to the unit fault at the observation point. Also, E is the sum of squares of the residuals.

[0055]

number

[0056]

number

[0057]

number

[0058] The unit fault displacement estimated in this way is used as the tsunami wave height at that unit fault (tsunami source area). The data used in this wave source estimation section is not limited to acoustic waveforms; it can also incorporate other observational data such as water level and water pressure waveforms using a joint inversion method, which improves the accuracy of estimating various tsunami information. An example of estimating the tsunami source area will be described later with reference to Figures 8 and 9.

[0059] Next, the tsunami detection processing unit 52 estimates the tsunami height and arrival time by superimposing a unit-fault tsunami waveform based on the estimated wave source area, or by tsunami propagation simulation using the estimated wave source area as the initial water level.

[0060] Specifically, the linear superposition unit 524 multiplies a unit fault tsunami waveform prepared in advance by the initial water level (x) estimated by the wave source estimation unit, and calculates a superposed waveform. Specifically, the linear overlapping unit 524 performs calculations using the following equation (4). Here, η is the tsunami waveform (times 1 to t) at prediction point k, A is the tsunami waveform (times 1 to t) caused by unit fault i at prediction point k, and x is the initial water level estimated at unit fault i.

[0061]

number

[0062] The tsunami propagation simulation unit 525 uses the initial water level (x) estimated by the tsunami wave source area estimation unit 523 as the initial condition and calculates the tsunami waveform at the predicted point by tsunami propagation simulation using a nonlinear long wave equation.

[0063] The notification control unit 526 executes control to notify the tsunami wave source area estimated by the tsunami detection processing unit 52 described above, as well as the tsunami height and arrival time. Specifically, the notification control unit 526 notifies the distribution of the tsunami wave source area estimated by the tsunami wave source area estimation unit 523, the linear superposition results by the linear superposition unit 524, the tsunami propagation simulation results by the tsunami propagation simulation unit 525, etc. as soon as the results are obtained.

[0064] As mentioned above, this information processing system can be combined with conventional observations (surface and underwater observations) to perform multiplexing (fusion inversion). When combining conventional observations (surface and underwater observations), the tsunami observation information acquisition unit 527 also functions.

[0065] The tsunami observation information acquisition unit 527 acquires, as tsunami observation information, information indicating water level or water pressure observed by observation devices (such as bottom pressure gauges, GPS wave gauges, and marine radar) placed at multiple locations on or underwater. The wave source area estimation unit 523 compares the tsunami component waveform extracted by the tsunami waveform extraction unit 522 with the unit fault sound waveform prepared in advance, and also estimates each of the one or more unit faults as a wave source area based on the tsunami observation information, thereby improving the speed and accuracy of estimating the tsunami wave source area and tsunami scale.

[0066] FIG. 5 is a flow chart showing the flow of various processes in FIGS. As shown in FIG. 5, in step ST21, the simulation processing unit 51 generates a unit tomographic sound wave waveform in advance by performing a sound wave propagation simulation. In addition, in step ST22, the simulation processing unit 51 generates a unit-fault tsunami waveform in advance by a tsunami propagation simulation.

[0067] When a tsunami actually occurs, the sonic wave observation device 2 observes the observed sonic wave waveforms generated by the tsunami at multiple points, as shown in step ST23. Next, as shown in step ST24, the observed sound waveform information acquisition unit 521 of the server 1 collects observed sound waveforms from a plurality of points. Next, as shown in step ST25, the tsunami waveform extraction unit 522 removes trend components and noise components from each observed sound wave waveform, and extracts the waveform of the tsunami component. Next, as shown in step ST26, the tsunami wave source region estimation unit 523 estimates the wave source region by comparing it with a unit fault sound wave waveform (Green's function) prepared in advance. Next, in step ST27, the notification control unit 526 notifies the estimated wave source region. Next, in step ST28, the linear superposition unit 524 estimates the tsunami height and arrival time by superposing unit-fault tsunami waveforms based on the estimated wave source area. Next, in step ST29, the tsunami propagation simulation unit 525 performs a tsunami propagation simulation based on the estimated wave source area, and estimates the tsunami height and arrival time. Next, in step ST30, the notification control unit 526 notifies the estimated results of the tsunami height and arrival time.

[0068] FIG. 6 is a diagram showing an example of an observed sound wave waveform acquired by the server of FIG. Specifically, the observed sound wave waveforms shown in Figure 6 are those observed at the Mizusawa observation point (MIZ) and the Hosokura observation point (HSK) when the Tohoku Pacific Coast Earthquake occurred. "Origin time" indicates the time when the tsunami is believed to have occurred. The graph fluctuates significantly about two minutes after the origin time. This indicates that seismic waves reach the ultrasonic observation device 2, and that vibrations caused by the earthquake itself and sound waves generated as a result of the shaking of the area around the ultrasonic observation device 2 due to the earthquake are being observed. About two minutes after the origin time, between 15 and 20 minutes, the graph shows large fluctuations in the circled area labeled "micro-pressure fluctuations." This is the sound waveform caused by the tsunami. After that, the graphs all show a smooth upward trend, which is thought to be a trend due to weather conditions, etc.

[0069] 7A and 7B are diagrams showing an example of a process for extracting a waveform of a tsunami component from an observed sound wave waveform. As shown in Figure 7A, when the observed sound waveform (infrasound waveform) at the time of tsunami occurrence is superimposed on the smoothing curve (background atmospheric fluctuations), a difference occurs between the smoothing curve and the observed sound waveform around 15:00 on the horizontal axis. This is the waveform of the tsunami component. Figure 7B shows a graph of the difference obtained by subtracting the smoothing curve (background atmospheric fluctuations) from the observed sound waveform (infrasound waveform) at the time of the tsunami occurrence. As described above, low-frequency micro-pressure fluctuations are observed near 15:00 on the horizontal axis of the graph in FIG. 7B. In this way, the sound waveform of the tsunami component is extracted by a method such as subtracting background atmospheric fluctuation components from the observed sound waveform using a smoothing curve. Note that the method of extracting the sound waveform of the tsunami component is not limited to the method of subtracting a smoothing curve, and any method may be adopted. In other words, the method of extracting the sound waveform of the tsunami component is sufficient as long as it can remove background atmospheric fluctuation components. Specifically, for example, a method using a numerical filter may be adopted.

[0070] 8A, 8B, 9A, and 9B are diagrams showing an example of estimating a tsunami source area. That is, Figures 8A, 8B, 9A and 9B show the results of estimating the wave source area by obtaining the infrasound waveform at each predicted point using a sound propagation simulation and comparing this waveform with a unit fault sound waveform (Green's function) prepared in advance. FIG. 8A shows the distribution of negative deformation among the fault distributions used in the estimation. FIG. 8B shows the distribution of positive deformation among the fault distributions used in the estimation. FIG. 9A shows the distribution of negative deformation among the fault distributions of the estimation results. FIG. 9B shows the distribution of positive deformation among the fault distributions of the estimation results. Comparing FIGS. 8A, 8B, 9A and 9B, it can be seen that the estimation results reproduce the deformation distribution in each region.

[0071] 10A to 10C are diagrams showing an example of a comparison between the observation results of a GPS wave meter and the simulation results. This is an example of the results of a sound wave propagation simulation to determine the infrasound waveform at each predicted point for the tsunami from the Tohoku Pacific Ocean Earthquake, and then estimating the wave source area by comparing this waveform with a pre-prepared unit fault sound wave waveform (Green's function).Furthermore, the tsunami waveform at a tsunami observation point was determined using a tsunami propagation simulation. FIG. 10A shows the observation results from the GPS wave gauge off the coast of Kuji and the simulation results superimposed on each other. FIG. 10B shows the observation results from the Miyako offshore GPS wave gauge and the simulation results superimposed on each other. FIG. 10C shows the observation results from a GPS wave gauge off the coast of Kamaishi superimposed on the simulation results. As shown in Figures 10A to 10C, the magnitude of the peak tsunami height and the elapsed time until the peak tsunami height were reached at each GPS wave gauge are in good agreement. In other words, it can be seen that the simulation results reproduce the tsunami height at each wave gauge location. Similar to the tsunami height at each GPS wave gauge, it is possible to simulate the wave height at each coastal area.

[0072] The embodiment of the server to which the present invention is applied has been described above. However, the embodiment to which the present invention is applied may also be, for example, as follows.

[0073] For example, the above-described series of processes can be executed by hardware or software. In other words, the functional configuration of FIG. 4 is merely an example and is not particularly limited. That is, it is sufficient if the information processing system is provided with the functionality to execute the above-described series of processes as a whole, and the functional blocks and databases used to realize these functions are not limited to the example in Figure 4. Furthermore, the locations of the functional blocks and databases are not particularly limited to those in Figure 4 and may be arbitrary. For example, the functional blocks and databases of the server 1 may be transferred to the sonic observation device 2 or the like. Furthermore, one functional block may be configured as a single piece of hardware, a single piece of software, or a combination thereof.

[0074] Furthermore, for example, when a series of processes is executed by software, the programs that make up the software are installed into a computer or the like from a network or a recording medium. The computer may be a computer built on dedicated hardware. The computer may also be a computer capable of executing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0075] Furthermore, for example, the recording medium containing such a program may be configured not only as a removable medium (not shown) that is distributed separately from the device main body in order to provide the program to the user, but also as a recording medium that is provided to the user in a state that is pre-installed in the device main body.

[0076] In this specification, the steps of describing a program to be recorded on a recording medium include not only processes that are performed chronologically in accordance with the order, but also processes that are not necessarily performed chronologically but are performed in parallel or individually. In addition, in this specification, the term "system" refers to an overall device that is made up of a plurality of devices, a plurality of means, etc.

[0077] In other words, the information processing device to which the present invention is applied can take various forms having the following configurations.

[0078] That is, an information processing device to which the present invention is applied (for example, the server 1 in FIG. 4) An information processing device that can access a database (for example, the simulation sound waveform information DB80 of FIG. 4) in which information indicating sound waveforms observed at each of a plurality of points when a tsunami occurs in a predetermined unit fault is stored in advance for each of a plurality of unit faults as unit fault sound waveform information (for example, information in the form of a Green's function), an observed waveform acquisition means (for example, the observed sound waveform information acquisition unit 521 in FIG. 4) that acquires observed sound waveform information indicating a plurality of observed sound waveforms observed at each of a plurality of points (for example, points R1 to R4 in FIG. 1 where the sound wave observation device 2 in FIG. 4 is located) when a tsunami actually occurs; a wave source area estimation means (for example, the tsunami wave source area estimation unit 523 of the tsunami detection processing unit 52 in FIG. 4) that estimates each of one or more unit faults as a wave source area by comparing the observed sound wave waveform information with each of the unit fault sound wave waveform information for each of the plurality of unit faults; A tsunami scale determination unit (for example, the tsunami wave source area estimation unit 523 of the tsunami detection processing unit 52 in FIG. 4) that determines the tsunami scale of the tsunami that actually occurred based on one or more of the wave source areas; An output control means (for example, the notification control unit 526 in FIG. 4) that controls the output of the information indicating the tsunami scale; It is enough to have this. This will improve the convenience of various tsunami-related estimations.

[0079] Furthermore, the observed waveform acquisition means (for example, the tsunami waveform extraction unit 522 of the tsunami detection processing unit 52 in FIG. 4) collecting actual observed acoustic waveforms at each of the plurality of ground locations; performing noise removal on the plurality of sound waveforms; Acquire, as the observed sound waveform information, information indicating a plurality of sound waveforms for a predetermined time period (for example, time-series waveforms for several tens to several hundreds of seconds after the occurrence of an earthquake) from among the plurality of sound waveforms from which noise has been removed. It is possible.

[0080] The unit fault sound wave waveform information is information obtained by setting the plurality of unit faults in an area expected to be a tsunami wave source region, and simulating sound wave propagation when each of the plurality of unit faults is set as a processing object and the processing object rises by a certain amount, The wave source region estimation means employs an inversion method in the comparison to estimate the one or more wave source regions. It is possible.

[0081] Further, the tsunami scale identification means identifies the tsunami scale using a tsunami wave source area distribution based on the one or more wave source areas. It is possible.

[0082] a tsunami observation information acquisition means (for example, the tsunami observation information acquisition unit 527 in FIG. 4) that acquires, as tsunami observation information, information indicating the water level or water pressure observed at each of a plurality of points when a tsunami actually occurs; Furthermore, The wave source area estimation means can compare the observed sound waveform information with the unit fault sound waveform information for each of the plurality of unit faults, and can also estimate each of one or more unit faults as a wave source area based on the tsunami observation information. [Explanation of symbols]

[0083] 1 Server, 2 Acoustic Observation Device, 11 CPU, 18 Memory Unit, 20 Drive, 31 Removable Media, 51 Simulation Processing Unit, 52 Tsunami Detection Processing Unit, 80 Simulation Acoustic Waveform Information DB, 201 Acoustic Measurement Unit, 202 Time Management Unit, 203 Observed Acoustic Waveform Information Transmission Control Unit, 521 Observed Acoustic Waveform Information Acquisition Unit, 522 Tsunami Waveform Extraction Unit, 523 Tsunami Wave Source Estimation Unit, 524 Tsunami Propagation Superposition Unit, 525 Tsunami Propagation Simulation Unit, 526 Notification Control Unit, 527 Tsunami Observation Information Acquisition Unit

Claims

1. An information processing device that can access a database in which information indicating sound waveforms observed at each of a plurality of points when a tsunami occurs at a specific unit fault is stored in advance for each of a plurality of unit faults as unit fault sound waveform information, the information being generated using a simulation of the propagation of sound waveforms when a tsunami occurs at a unit fault, the simulation results of which have been confirmed to be able to reproduce actual observation results for tsunamis that have actually occurred in the past, an observed waveform acquisition means for acquiring, as observed sound waveform information, information indicating a plurality of observed sound waveforms observed at a plurality of points when a tsunami actually occurs; a wave source region estimation means for estimating each of one or more unit faults as a wave source region by comparing the observed sound wave waveform information with each of the unit fault sound wave waveform information for each of the plurality of unit faults; a tsunami scale determination means for determining the scale of the tsunami that actually occurred based on the observed sound wave waveform information and one or more of the wave source areas; output control means for executing control to output information indicating the tsunami scale; Equipped with The observed waveform acquisition means Collecting the plurality of observed sound wave waveforms actually observed at each of the plurality of points; For the plurality of observed sound waveforms, at least a trend component derived from the atmospheric pressure distribution and a noise component acquired from the sound source around the observed point are set as targets, and noise removal is performed using the targets as noise; acquiring, as the observed sound waveform information, information indicating a plurality of observed sound waveforms in a predetermined time period from among the plurality of observed sound waveforms from which noise has been removed; Information processing device.

2. The unit fault sound wave waveform information is information obtained by setting the plurality of unit faults in an area expected to be a tsunami source region, setting each of the plurality of unit faults as a processing object, and simulating sound wave propagation when the processing object rises by a certain amount, The wave source region estimation means employs an inversion method in the comparison to estimate the one or more wave source regions. The information processing device according to claim 1 .

3. The tsunami scale identification means identifies the tsunami scale using a tsunami wave source area distribution based on the one or more wave source areas.

3. The information processing device according to claim 1 or 2.

4. a tsunami observation information acquisition means for acquiring, as tsunami observation information, information indicating water levels or water pressures observed at each of a plurality of points when a tsunami actually occurs; Furthermore, The wave source area estimation means compares the observed sound wave waveform information with the unit fault sound wave waveform information for each of the plurality of unit faults, and also estimates each of one or more unit faults as the wave source area based on the tsunami observation information.

4. The information processing device according to claim 1.

5. An information processing method is executed by an information processing device that can access a database that stores in advance unit fault sound waveform information for each of a plurality of unit faults, the information indicating sound waveforms observed at each of a plurality of points when a tsunami occurs at a specific unit fault, the information being generated using a simulation of the propagation of sound waveforms when a tsunami occurs at a unit fault, the simulation results of which have been confirmed to be able to reproduce actual observation results for tsunamis that have actually occurred in the past, an observed waveform acquisition step of acquiring, as observed sound waveform information, information indicating a plurality of observed sound waveforms observed at a plurality of points when a tsunami actually occurs; a wave source region estimation step of estimating each of one or more unit faults as a wave source region by comparing the observed sound wave waveform information with each of the unit fault sound wave waveform information for each of the plurality of unit faults; a tsunami scale determination step of determining the scale of the tsunami that actually occurred based on the observed sound wave waveform information and one or more of the wave source areas; an output control step of executing control to output information indicating the tsunami scale; Including, The observed waveform acquisition step includes: Collecting the plurality of observed sound wave waveforms actually observed at each of the plurality of points; For the plurality of observed sound waveforms, at least a trend component derived from the atmospheric pressure distribution and a noise component acquired from the sound source around the observed point are set as targets, and noise removal is performed using the targets as noise; acquiring, as the observed sound waveform information, information indicating a plurality of observed sound waveforms in a predetermined time period from among the plurality of observed sound waveforms from which noise has been removed; Including steps, Information processing methods.

6. A computer that can access a database in advance stored with each of a plurality of unit faults as unit fault sound waveform information, which is information indicating sound waveforms observed at each of a plurality of points when a tsunami occurs at a specific unit fault, generated using a simulation of the propagation of sound waveforms when a tsunami occurs at a unit fault, and which has been confirmed to be able to reproduce actual observation results for tsunamis that have actually occurred in the past. an observed waveform acquisition step of acquiring, as observed sound waveform information, information indicating a plurality of observed sound waveforms observed at a plurality of points when a tsunami actually occurs; a wave source region estimation step of estimating each of one or more unit faults as a wave source region by comparing the observed sound wave waveform information with each of the unit fault sound wave waveform information for each of the plurality of unit faults; a tsunami scale determination step of determining the scale of the tsunami that actually occurred based on the observed sound wave waveform information and one or more of the wave source areas; an output control step of executing control to output information indicating the tsunami scale; Execute a control process including The observed waveform acquisition step includes: Collecting the plurality of observed sound wave waveforms actually observed at each of the plurality of points; For the plurality of observed sound waveforms, at least a trend component derived from the atmospheric pressure distribution and a noise component acquired from the sound source around the observed point are set as targets, and noise removal is performed using the targets as noise; acquiring, as the observed sound waveform information, information indicating a plurality of observed sound waveforms in a predetermined time period from among the plurality of observed sound waveforms from which noise has been removed; Execute a control process including the steps: program.

Images