Simulation program, simulation method and information processing device

Abstract

To improve the accuracy of electromagnetic surveying by a TEM method.SOLUTION: A simulation device acquires first magnetic field information detected by a sensor obtained by generating a magnetic field in a space from a transmission source to be installed outside the space, and acquires second magnetic field information acquired by the sensor by generating a magnetic field from the transmission source to a space of a retrieval object with the existence of an object for generating electromagnetic induction by simulation with a physical amount by a magnetic field from the object. The simulation device executes optimization of the physical amount on the basis of the first magnetic field information and the second magnetic field information, and generates a specific resistance distribution by using the optimized physical amount.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] To explore geothermal reservoirs, it is effective to estimate the resistivity distribution around the reservoir. Known methods for estimating resistivity include the frequency-domain MT (Magneto-Telluric) method and the time-domain TEM (Transient Electro-Magnetic) method.

[0003] The MT method is a technique for estimating resistivity by measuring electric and magnetic fields using natural magnetic fields. Normally, only the resistivity at the measurement point can be obtained, but by dividing the space into meshes using an appropriate physical model, the resistivity at all meshes in the space can be estimated. The TEM method uses artificial magnetic fields, and compared to the MT method, it can estimate resistivity with higher accuracy, higher resolution, and at lower cost. It is generally said that the horizontal resolution of the superconducting TEM method is six times that of the MT method. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 9-281249 [Patent Document 2] Japanese Patent Application Laid-Open No. 2009-74953 [Patent Document 3] Japanese Patent Application Laid-Open No. 2007-285729 Summary of the Invention [Problem to be solved by the invention]

[0005] However, when electromagnetic exploration is performed using the TEM method, the exploration accuracy can be poor. For example, when estimating the location of a reservoir using electromagnetic exploration using the TEM method in an area where an existing power plant is in operation, the steel pipes of the power plant can cause electromagnetic induction, which can lead to errors in the sensor's measurement results and degrade the exploration accuracy.

[0006] In one aspect, an object of the present invention is to provide a simulation program, a simulation method, and an information processing device that can improve the accuracy of electromagnetic exploration using the TEM method. [Means for solving the problem]

[0007] In the first proposal, the simulation program causes a computer to execute a process of generating a magnetic field from a transmission source in space and acquiring first magnetic field information detected by a sensor installed outside the space, and generating a magnetic field from the transmission source in a space to be searched in which an object that generates electromagnetic induction is present and acquiring second magnetic field information by the sensor through a simulation using the physical quantity due to the magnetic field from the object as a parameter, optimizing the physical quantity based on the first magnetic field information and the second magnetic field information, and generating a resistivity distribution in the space using the optimized physical quantity. [Effects of the Invention]

[0008] According to one embodiment, the accuracy of electromagnetic exploration using the TEM method can be improved. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the overall configuration of a geothermal reservoir exploration system according to a first embodiment. [Figure 2] Figure 2 is a diagram illustrating a typical geothermal reservoir exploration. [Figure 3] FIG. 3 is a diagram illustrating the geothermal reservoir exploration process according to the first embodiment. [Figure 4]FIG. 4 is a functional block diagram of the simulation apparatus according to the first embodiment. [Figure 5] FIG. 5 is a diagram illustrating the formulation. [Figure 6] FIG. 6 is a diagram for explaining the estimation of the vertical magnetic field by simulation. [Figure 7] FIG. 7 is a diagram for explaining the measurement of magnetic field information as an actual measurement location. [Figure 8] FIG. 8 is a diagram illustrating optimization. [Figure 9] FIG. 9 is a flowchart illustrating the flow of the geothermal reservoir exploration process according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0010] The following describes in detail the embodiments of the simulation program, simulation method, and information processing device disclosed herein with reference to the accompanying drawings. Note that the present invention is not limited to these embodiments. Furthermore, the embodiments can be combined as appropriate within a consistent range. [Example]

[0011] (Explanation of geothermal reservoir exploration) In recent years, new geothermal reservoirs have often been explored in areas where existing geothermal power plants are in operation, and in such cases, electromagnetic exploration using the TEM method is performed. FIG. 1 is a diagram illustrating an example of the overall configuration of a geothermal reservoir exploration system according to Example 1. As shown in FIG. 1, the electromagnetic exploration system according to Example 1 includes a power plant 1, a steel pipe 2, a reservoir 3, a transmission source 4, a sensor 5, and a simulation device 10. In Example 1, an example of exploring a new reservoir A using these will be described.

[0012] Power plant 1 is an existing geothermal power plant that generates electricity by capturing the power of heated, high-temperature water and steam through steel pipes 2 installed in an existing storage tank 3. Steel pipes 2 are steel pipes installed to capture steam and the like, and are an example of an object that generates electromagnetic induction. Storage tank 3 is a geothermal storage tank that is already in use.

[0013] The transmission source 4 is a device used for electromagnetic exploration and is an example of a device that generates a magnetic field underground, which is an example of space. The sensor 5 is a sensor installed on the ground and is an example of a sensor that measures magnetic field information (e.g., secondary magnetic field) that is propagated underground from the magnetic field generated by the transmission source 4. The simulation device 10 is an example of an information processing device or computer that performs electromagnetic exploration using the TEM method and estimates the position of a new storage tank A from underground.

[0014] (General electromagnetic survey) We will now explain electromagnetic exploration typically performed in the above-mentioned environment. Figure 2 is a diagram illustrating typical geothermal reservoir exploration. The configuration of the electromagnetic exploration system shown in Figure 2 is the same as that shown in Figure 1. In this configuration, typical electromagnetic exploration involves using a sensor 5 to detect a magnetic field generated underground from a transmission source 4 and estimate the resistivity distribution. Then, using experts or analysis software, the location of a new reservoir is estimated from the estimated resistivity distribution.

[0015] Here, the magnetic field information 50 detected (measured) by the sensor 5 would normally decrease smoothly over time. However, underground where the steel pipe 2 is present, the magnetic field from the steel pipe 2 is superimposed on the magnetic field from the transmission source 4, so the magnetic field information 51 detected (measured) by the sensor 5 contains noise. As a result, an error occurs between the normal magnetic field information 50 and the magnetic field information 60 affected by the steel pipe 2, and the new location of the reservoir is estimated to be B. In other words, the influence of the steel pipe 2 reduces the accuracy of the reservoir location estimation. If the accuracy of the location estimation deteriorates in this way, an increasing number of wells (reservoirs) will be abandoned without finding the reservoir even after drilling. This results in increased costs and longer processing times, significantly reducing the efficiency of electromagnetic exploration.

[0016] (Electromagnetic exploration according to Example 1) Therefore, the simulation device 10 according to the first embodiment generates a magnetic field from a transmission source 4 underground and acquires first magnetic field information detected by a sensor 5 installed on the ground. The simulation device 10 also generates a magnetic field from the transmission source 4 in a search target space where a steel pipe 2 that generates electromagnetic induction is present and acquires second magnetic field information acquired by the sensor 5 through a simulation using, as a parameter, the magnetic moment, which is an example of a physical quantity due to the magnetic field from the steel pipe 2. The simulation device 10 then optimizes the magnetic moment based on the first magnetic field information and the second magnetic field information, and generates a resistivity distribution in the ground using the optimized magnetic moment.

[0017] That is, in order to remove noise by simulating a system including the electromagnetic induction of the steel pipe 2, the simulation device 10 creates a model including the underground steel pipe 2 and performs a simulation using its magnetic moment as an unknown parameter. The simulation device 10 then estimates the exact location of the geothermal reservoir from the resistivity at each point underground estimated as a result of the simulation.

[0018] FIG. 3 is a diagram illustrating the geothermal reservoir exploration process according to Example 1. As shown in FIG. 3, the simulation device 10 acquires the "original magnetic field," which is an actual measurement value in the environment shown in FIG. 1 or underground without the steel pipe 2, and the "simulated magnetic field" by forward simulation in which the steel pipe 2 is modeled as a vertical dipole. The simulation device 10 then calculates the magnetic moment that minimizes the squared error between the "original magnetic field" and the "simulated magnetic field." The simulation device 10 then optimizes the "simulated magnetic field" using the calculated magnetic moment and generates a resistivity distribution underground using the optimized magnetic field.

[0019] In this way, the simulation device 10 according to the first embodiment can improve the accuracy of the electromagnetic exploration by the TEM method by executing a simulation in which the influence of the steel pipe 2 is taken into consideration.

[0020] (Functional configuration) 4 is a functional block diagram illustrating a functional configuration of the simulation device 10 according to the first embodiment. As shown in FIG.

[0021] The communication unit 11 is a processing unit that controls communication with other devices, and is realized by, for example, a communication interface, etc. For example, the communication unit 11 acquires magnetic field information detected by the sensor 5 from the sensor 5, and outputs the results of the simulation device 10 to a specified output destination or transmission destination.

[0022] The storage unit 12 is an example of a processing unit that stores various information and programs executed by the control unit 20, and is realized by, for example, a memory or a hard disk. The storage unit 12 stores magnetic field information 13 acquired or calculated by the control unit 20, which will be described later. The magnetic field information 13 stored here is, for example, time-series data with the horizontal axis representing time (t) and the vertical axis representing the vertical magnetic field (Hz).

[0023] The control unit 20 is a processing unit that controls the simulation device 10, and is realized by, for example, a processor. The control unit 20 has a simulation execution unit 21, an actual measurement value acquisition unit 22, an optimization unit 23, and a generation unit 24. The simulation execution unit 21, the actual measurement value acquisition unit 22, the optimization unit 23, and the generation unit 24 are realized by electronic circuits included in the processor, processes executed by the processor, etc.

[0024] Before describing the processing by the control unit 20, the formulation of the model executed by the simulation device 10 will be described. FIG. 5 is a diagram for explaining the formulation. As shown in FIG. 5, an arbitrary point underground is defined as a variable "X" as an observation target. Note that the points used as the variable "X" can be points in each mesh when the underground is divided into a mesh, or points in each layer obtained by dividing the underground along lines parallel to the ground line.

[0025] Metal data is expressed as (ε', μ'), and geological data is expressed as "ε(x), μ(x), ρ(x)" using the variable x. Note that ρ is resistivity, ε is permittivity, and μ is magnetic permeability, with ε and μ being known values. Here, since all values ​​except ρ(x) are fixed, ε(x) is "ε0" for materials other than metals and "ε'" for materials other than metals, and μ(x) is "μ0" for materials other than metals and "μ'" for materials other than metals. An arbitrary initial value is given to ρ(x), but since ρ(x) is resistivity, it is a value that varies depending on the magnitude of the magnetic moment.

[0026] Next, based on the above modeling, we will explain each functional unit of the control unit 20. The simulation execution unit 21 is a processing unit that generates a magnetic field from a transmission source 4 into the underground of a search target where a steel pipe 2 that generates electromagnetic induction is located, and acquires magnetic field information acquired by a sensor 5 through a simulation using the magnetic moment due to the magnetic field from the steel pipe 2 as a parameter.

[0027] Specifically, the simulation execution unit 21 executes a forward simulation using a known geophysical exploration simulation tool or the like, and estimates the vertical magnetic field measured by the sensor 5.

[0028] Fig. 6 is a diagram for explaining the estimation of a vertical magnetic field by simulation. As shown in Fig. 6, the simulation execution unit 21 models the steel pipe 2 as a vertical magnetic dipole under the assumption of a uniform earth. The simulation execution unit 21 then assumes that electromagnetic induction (e.g., Federer's law) occurs due to the magnetic field generated from the transmission source 4, and that the resulting current (eddy current) causes the steel pipe 2 to function as a vertical magnetic dipole (e.g., Ampere's law).

[0029] That is, the simulation execution unit 21 replaces the transmission source 4 with an antenna and the steel pipe 2 with an equivalent circuit whose magnetic moment (M(t)) is unknown, and models the effect of the steel pipe 2 on the sensor 5. Then, through forward simulation using this model, the simulation execution unit 21 estimates the vertical magnetic field (measurement result) in which the eddy current from the antenna is affected by the magnetic moment (M(t)) and the sensor 5 measures the secondary magnetic field generated by the affected eddy current.

[0030] The actual measurement value acquisition unit 22 is a processing unit that generates a magnetic field from a transmission source 4 underground and acquires magnetic field information detected by a sensor 5 installed on the ground. Specifically, the actual measurement value acquisition unit 22 acquires the vertical magnetic field actually measured by the sensor 5 using the TEM method in the exploration environment shown in Figure 1 where no steel pipe 2 is present.

[0031] Here, it may be difficult to perform actual measurements in an exploration environment where the steel pipe 2 is not present. In such cases, the measured value acquisition unit 22 acquires the results of a known electromagnetic analysis simulator as actual measurements. Figure 7 is a diagram illustrating the measurement of magnetic field information at an actual measurement site. As shown in Figure 7, the measured value acquisition unit 22 performs a simulation under the assumption of uniform earth, assuming the steel pipe 2 to be a vertical metal rod, and including the influence of a low resistivity body present underground. As a result, the measured value acquisition unit 22 estimates the vertical magnetic field in which the sensor 5 measures the secondary magnetic field generated by eddy currents from the antenna.

[0032] The optimization unit 23 is a processing unit that performs optimization of the magnetic moment based on the magnetic field information (vertical magnetic field) acquired by the actual measurement value acquisition unit 22 and the magnetic field information (vertical magnetic field) acquired by the simulation execution unit 21. Specifically, the optimization unit 23 calculates the magnetic moment that minimizes the error between the two pieces of magnetic field information.

[0033] FIG. 8 is a diagram illustrating the optimization. In the example of FIG. 8, Φ is the magnetic flux around the steel pipe 2, V i is the induced electromotive force in steel pipe 2, H´ z (x) is the magnetic field observed by sensor 5, H z (x) is the estimated value of the magnetic field calculated by calculation (simulation). n indicates the observation point, which is expressed as a locations x b time snapshots.

[0034] As shown in FIG. 8, the optimization unit 23 performs forward calculation using the variable X "ε(x), μ(x), ρ(x)" to obtain "H z Specifically, the optimization unit 23 calculates (updates) the voltage V using the current I and "ε(x), μ(x), ρ(x)". i Calculate the voltage V i and ρ(x) i ,ρ(x)" to "H z Calculate "(x)".

[0035] Next, the optimization unit 23 calculates the actual measurement value "H' z (x)" and "H z The optimization unit 23 then calculates the mean square error "Err" between the estimated magnetic field waveform and the actual measured magnetic field waveform. The optimization unit 23 then calculates the magnetic moment M(t) that minimizes the magnetic moment M(t) using the magnetic moment M(t) as an explanatory variable and the mean error "Err" as a cost function. Specifically, the optimization unit 23 evaluates the square error using a gradient method, a simulated annealing method, a genetic algorithm, or the like. In other words, as shown in graph G in Figure 8, the optimization unit 23 adjusts the time axis of the magnetic field waveform, which is an estimated value, and performs optimization so as to reduce the error with the magnetic field waveform, which is an actually measured value.

[0036] Next, the optimization unit 23 updates "ρ(x)", which changes depending on the magnetic moment (M(t)), by forward calculation using the optimized "Err", ε(x), μ(x), and current I. That is, the optimization unit 23 corrects "ρ(x)" by feeding back the squared error evaluated by the gradient method or the like to the unknown parameters, in other words, updates the value of "ρ(x)" with a nearby value. Note that the forward calculation here can be applied to the differential equations of Maxwell's equations.

[0037] Thereafter, the optimization unit 23 repeatedly updates "ρ(x)" by the above-described process and identifies "ρ(x)" when "Err" has converged.

[0038] The generation unit 24 is a processing unit that generates resistivity data, which is the resistivity distribution in the ground, using the magnetic moment optimized by the optimization unit 23. Specifically, the generation unit 24 uses the optimized "ρ(x)" of each point in the ground to run a simulation excluding the steel pipe 2, and generates the resistivity distribution. For example, the generation unit 24 runs a simulation in which the optimized "ρ(x)" of each point is set in the simulation run by the simulation running unit 21, and estimates the resistivity distribution taking into account the electromagnetic induction of the steel pipe 2.

[0039] In this way, the generation unit 24 generates a resistivity cross section with higher horizontal resolution than the MT method, using the resistivity distribution obtained using the optimized "ρ(x)" of each underground point. The generation unit 24 can then use a general analysis tool or the like to accurately estimate the location of the reservoir from the resistivity cross section.

[0040] (Processing flow) Fig. 9 is a flowchart showing the flow of the geothermal reservoir exploration process according to Example 1. As shown in Fig. 9, the simulation device 10 receives, as input, resistivity data of the magnetic field including the steel pipe 2 and the position of the steel pipe 2 (S1).

[0041] Next, the simulation device 10 generates a function that outputs a magnetic field waveform from the unknown parameters of resistivity, permittivity, and magnetic permeability as a model including the steel pipe 2 (S2).

[0042] Then, the simulation device 10 provides initial values ​​for the unknown parameters (S3), estimates the waveform of the magnetic field based on the current unknown parameters (S4), and calculates the square error between the estimated value and the measured value (S5).

[0043] If the squared error is not within the allowable range (S6: No), the simulation device 10 updates the unknown parameter with a nearby value (S7) and repeats S4 and subsequent steps.

[0044] On the other hand, if the squared error is within the allowable range (S6: Yes), the simulation device 10 executes a simulation excluding the steel pipe 2 based on the obtained unknown parameters (S8) and outputs resistivity data without the steel pipe (S9).

[0045] (effect) As described above, the simulation device 10 can accurately estimate the location of the geothermal reservoir by modeling using two methods that are fundamentally consistent and executing a simulation that takes into account the influence of the steel pipe 2. As a result, it is possible to prevent an increase in costs due to abandoning excavation.

[0046] Furthermore, even in environments where it is difficult to measure actual measured values ​​after considering the positions of the sensor 5 and transmission source 4 due to land ownership or other reasons, the simulation device 10 calculates values ​​equivalent to the actual measured values ​​using an electromagnetic analysis simulator, so that the position of the geothermal reservoir can be accurately estimated regardless of the environment.

[0047] In addition, the simulation device 10 evaluates squared errors using gradient methods, simulated annealing, genetic algorithms, etc., thereby simplifying, speeding up, and improving the accuracy of repetitive processing, and enabling the accurate location estimation of geothermal reservoirs to be performed more quickly. [Example]

[0048] Although the embodiments of the present invention have been described above, the present invention may be embodied in various different forms other than the above-described embodiments.

[0049] (Numbers, etc.) The numerical values, number of underground points, graphs, etc. used in the above embodiments are merely examples and can be changed as desired. The process flow described in each flowchart can also be changed as appropriate within a consistent range. The object to be explored is not limited to the steel pipe 2, but can be any other object that causes electromagnetic induction, and the object to be explored is not limited to a storage tank, but can be any object explored by electromagnetic exploration. The underground is also an example of a space in which electromagnetic exploration is performed.

[0050] (system) The information including the processing procedures, control procedures, specific names, various data and parameters shown in the above documents and drawings may be changed arbitrarily unless otherwise specified.

[0051] Furthermore, the specific form of distribution or integration of the components of each device is not limited to that shown in the figure. For example, the optimization unit 23 and the generation unit 24 may be integrated. That is, all or some of the components may be functionally or physically distributed or integrated in any unit depending on various loads, usage conditions, etc. Furthermore, all or any part of the processing functions of each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[0052] Furthermore, all or any part of the processing functions performed by each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware using wired logic.

[0053] (Hardware) Fig. 10 is a diagram illustrating an example of a hardware configuration. Here, a simulation device 10 will be described as an example. As shown in Fig. 10, the simulation device 10 includes a communication device 10a, a hard disk drive (HDD) 10b, a memory 10c, and a processor 10d. The components illustrated in Fig. 10 are interconnected by a bus or the like.

[0054] The communication device 10a is a network interface card or the like, and communicates with other devices. The HDD 10b stores programs and DBs that operate the functions shown in FIG.

[0055] The processor 10d reads out from the HDD 10b or the like a program that executes the same processes as the respective processing units shown in Fig. 4 and loads it into the memory 10c, thereby operating a process that executes each function described in Fig. 4 or the like. For example, this process executes the same functions as the respective processing units of the simulation device 10. Specifically, the processor 10d reads out from the HDD 10b or the like a program that has the same functions as the simulation execution unit 21, the actual measurement value acquisition unit 22, the optimization unit 23, the generation unit 24, etc. Then, the processor 10d executes a process that executes the same processes as the simulation execution unit 21, the actual measurement value acquisition unit 22, the optimization unit 23, the generation unit 24, etc.

[0056] In this way, the simulation device 10 operates as an information processing device that executes a simulation method by reading and executing a program. The simulation device 10 can also realize functions similar to those of the above-described embodiment by reading the program from a recording medium using a medium reading device and executing the read program. Note that the program in these other embodiments is not limited to being executed by the simulation device 10. For example, the above-described embodiment may also be applied in the same way to cases where another computer or server executes the program, or where these execute the program in cooperation with each other.

[0057] This program may be distributed via a network such as the Internet. Alternatively, this program may be recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), or a digital versatile disk (DVD), and may be read out from the recording medium and executed by a computer. [Explanation of symbols]

[0058] 10 Simulation equipment 11 Communications Department 12 Storage section 13 Magnetic field information 20 Control Unit 21 Simulation execution unit 22 Actual measurement value acquisition section 23 Optimization Section 24 Generation part

Claims

1. On the computer, A magnetic field is generated from a transmission source in a space, and first magnetic field information is acquired by a sensor installed outside the space, and a magnetic field is generated from the transmission source in a search target space where an object that generates electromagnetic induction is present, and second magnetic field information is acquired by the sensor through a simulation using a physical quantity due to the magnetic field from the object as a parameter; Optimizing the physical quantity based on the first magnetic field information and the second magnetic field information; generating a resistivity distribution in the space using the optimized physical quantity; A simulation program that executes a process.

2. The acquiring process includes: Acquire the first magnetic field information, which is time-series information of the vertical magnetic field detected by the sensor, and the second magnetic field information, which is time-series information of the vertical magnetic field detected by the sensor and is estimated by the simulation; The process of performing the optimization includes: calculating the physical quantity that minimizes an error between the first magnetic field information and the second magnetic field information; The simulation program according to claim 1 .

3. the physical quantity is a magnetic moment, The optimization process includes: determining the magnetic moment that minimizes a squared error between the first magnetic field information and the second magnetic field information; generating a spatial resistivity distribution using the resistivity determined based on the determined magnetic moment; The simulation program according to claim 1 or 2.

4. the physical quantity is a magnetic moment, The acquiring process includes: acquiring the first magnetic field information measured by the sensor for each of a plurality of regions in the space and the second magnetic field information estimated by the simulation using resistivity, permittivity, and magnetic permeability for each of the plurality of regions; The optimization process includes: determining the resistivity based on the magnetic moment that minimizes a square error between the first magnetic field information and the second magnetic field information; generating a resistivity distribution in the space using the determined resistivity of each of the plurality of regions; The simulation program according to claim 1 or 2.

5. The computer A magnetic field is generated from a transmission source in a space, and first magnetic field information is acquired by a sensor installed outside the space, and a magnetic field is generated from the transmission source in a search target space where an object that generates electromagnetic induction is present, and second magnetic field information is acquired by the sensor through a simulation using a physical quantity due to the magnetic field from the object as a parameter; Optimizing the physical quantity based on the first magnetic field information and the second magnetic field information; generating a resistivity distribution in the space using the optimized physical quantity; A simulation method comprising: executing a process.

6. A magnetic field is generated from a transmission source in a space, and first magnetic field information is acquired by a sensor installed outside the space, and a magnetic field is generated from the transmission source in a search target space where an object that generates electromagnetic induction is present, and second magnetic field information is acquired by the sensor through a simulation using a physical quantity due to the magnetic field from the object as a parameter; Optimizing the physical quantity based on the first magnetic field information and the second magnetic field information; generating a resistivity distribution in the space using the optimized physical quantity; An information processing device comprising a control unit.

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