A method for predicting muon flux intensity of kilometers underground

Abstract

The disclosure provides a kilometer-level muon flow intensity prediction method underground, and relates to the field of geological exploration. The method comprises the following steps: obtaining an initial cosmic ray model; obtaining a contour parameterized model of a target geological body, and obtaining a reference density of the target geological body; determining a target geological body model according to the reference density of the target geological body and the contour parameterized model; simulating according to the initial cosmic ray model and the target geological body model to determine muon events reaching a detection device; correcting the muon events according to the type of the detection device based on a corresponding direction reconstruction algorithm to obtain a muon direction prediction distribution; obtaining muon differential flow intensity prediction values of each direction interval according to the muon direction prediction distribution; obtaining muon differential flow intensity measurement values of each direction interval; and determining the position of a density change area of the target geological body according to the difference between the muon differential flow intensity measurement values and the muon differential flow intensity prediction values of each direction interval.

Description

Technical Field

[0001] This disclosure relates to the field of geological exploration, and in particular to a method for predicting muon flow intensity at depths of up to 1,000 meters underground. Background Technology

[0002] Cosmic ray muons (hereinafter referred to as muons) are produced by the interaction of primordial cosmic rays with atmospheric matter at altitudes of 30 kilometers and above, and their energies can extend to TeV and above. High-energy muons have strong penetrating power in matter, and their tracks can be approximated as straight lines. When they pass through matter, they mainly lose energy through ionization energy loss, which is strongly correlated with different matter densities, thus making them naturally suitable for geological tomography.

[0003] Muon imaging technology has the following advantages: due to the strong penetrating power of high-energy muons, the sensitive detection area can be buried deep, up to 1 kilometer or more; since the measurement results do not depend on the properties of the objects around the detected object, but mainly on the single property of the density of the detected object, the anti-interference ability is strong; in addition, muons are a naturally occurring and free particle source, and there is no need to make special radiation protection for them, which reduces costs.

[0004] As muons pass through the object being probed, the attenuation of the muon flux is related to the length of their track within the object and the density of matter along that track. Therefore, by measuring the muon flux and calculating the track length based on the material profile, the material density can be deduced, thus enabling geological tomography.

[0005] Muon flow intensity prediction is an important part of geological tomography. Among related technologies, there is no kilometer-level geological tomography analysis method applicable to various types of detection devices, and no kilometer-level geological tomography analysis method applicable to spherical full liquid scintillator 4π solid angle detection device. Summary of the Invention

[0006] In view of the above problems, this disclosure provides a method for predicting muon flow intensity at a depth of kilometer underground, so as to overcome the above problems or at least partially solve the above problems.

[0007] This disclosure provides a method for predicting muon current intensity at a depth of kilometer underground, including:

[0008] Obtain an initial cosmic ray model, which includes the distribution of energy and direction followed by the first muon before it enters the geological body;

[0009] Obtain the contour parametric model of the target geological body and the reference density of the target geological body, wherein the burial depth of the target geological body reaches the kilometer level underground;

[0010] The target geological body model is determined based on the reference density of the target geological body and the contour parameterization model;

[0011] Simulations are performed based on the initial cosmic ray model and the target geological body model to determine muon events that reach the detection device. The detection device is a spherical liquid scintillator with a 4π solid angle or other detection device.

[0012] According to the type of the detection device, based on the corresponding orientation reconstruction algorithm, the muon event is responded to and corrected to obtain the muon orientation prediction distribution. This includes: when the detection device is a spherical full liquid scintillator 4π solid angle detection device, the muon event is responded to and corrected according to the time series and / or energy series corresponding to each photomultiplier tube in the spherical full liquid scintillator 4π solid angle detection device to obtain the muon orientation prediction distribution.

[0013] Based on the predicted distribution of muon directions, the predicted values ​​of the muon differential current strength for each direction interval are obtained.

[0014] Optionally, when the detection device is the spherical full liquid scintillation 4π solid angle detection device, it further includes:

[0015] Based on the electrical signals output by each photomultiplier tube of the spherical total liquid scintillation 4π solid angle detection device, the time series and energy series corresponding to each photomultiplier tube are determined. The electrical signals are generated based on the second muon that passes through the target geological body and reaches the spherical total liquid scintillation 4π solid angle detection device.

[0016] Based on the sum of the energy sequences of each of the electrical signals, the background electrical signal is removed from the electrical signals to obtain the electrical signal of the second muon;

[0017] Obtain the time sequence and energy sequence of the electrical signal of the second muon output by each photomultiplier tube;

[0018] The reconstruction direction of the second muon is obtained based on the time series and / or energy series of the electrical signal of the second muon;

[0019] The detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillation 4π solid angle detection device were obtained;

[0020] Based on the reconstruction direction of the second muon, the detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillator 4π solid angle detection device, the measured values ​​of the muon differential current intensity in each directional interval are obtained.

[0021] Optionally, if the detection device is one of the other detection devices, it further includes:

[0022] Acquire the electrical signals output by the other detection devices, wherein the electrical signals are generated based on the third muon that passes through the target geological body and reaches the other detection devices;

[0023] Obtain the orientation reconstruction algorithm corresponding to the other detection devices;

[0024] The reconstructed direction of the third muon is obtained based on the direction reconstruction algorithm corresponding to the other detection devices and the electrical signals output by the other detection devices.

[0025] Obtain the detection efficiency and effective cross-sectional area of ​​the other detection devices;

[0026] Based on the reconstruction direction of the third muon, the detection efficiency and effective cross-sectional area of ​​the other detection devices, the measured values ​​of the muon differential current intensity in each directional interval are obtained.

[0027] Optionally, it also includes:

[0028] The standard deviation of each directional interval is determined based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval.

[0029] Based on the standard deviation of each directional interval, determine whether the measured density of each directional interval deviates from the reference density;

[0030] The location of the density change zone is determined based on whether the measured density in each directional interval deviates from the reference density, wherein the measured density in the directional interval where the density change zone is located deviates from the reference density.

[0031] Optionally, the step of determining muon events reaching the detection device based on the initial cosmic ray model and the target geological body model includes:

[0032] The target geological body model was imported into a Monte Carlo simulation program based on the physical processes of muon-matter interaction;

[0033] By sampling the initial cosmic ray model, the energies and directions of multiple first muons are obtained;

[0034] The initial position of each of the first muons is set as: outside the target geological body, and on a ray passing through the center of the detection device and in the direction of each of the first muons;

[0035] In the Monte Carlo simulation program, the interaction process between the plurality of first muons and the target geological body is simulated to determine muon events that arrive at the detection device.

[0036] Optionally, the step of adjusting the response of the muon event based on the type of the detection device and the corresponding orientation reconstruction algorithm to obtain the predicted distribution of muon orientations includes:

[0037] The structure of the detection device is imported into the simulation response program;

[0038] In the simulation response procedure, the direction of the muon event is used as the initial direction to simulate the response process of the muon event in the detection device, and a simulation output signal is obtained;

[0039] Based on the structure of the detection device, a corresponding direction reconstruction algorithm is used to reconstruct the direction of the analog output signal to obtain the predicted direction. The structure of the detection device includes: a detection device structure whose direction resolution and / or detection efficiency are related to the muon incident direction, and a detection device structure whose direction resolution and detection efficiency are both independent of the muon incident direction.

[0040] The predicted distribution of the muon direction is obtained based on the predicted directions corresponding to multiple muon events.

[0041] Optionally, if the detection device has a structure in which both directional resolution and detection efficiency are independent of the muon incident direction,

[0042] In the simulation response procedure, the direction of the muon event is used as the initial direction to simulate the response process of the muon event in the detection device, resulting in a simulated output signal, including:

[0043] In the simulation response procedure, the directions of a portion of muon events are randomly and uniformly sampled as initial directions, and the response process of the portion of muon events in the detection device is simulated to obtain the simulation output signal;

[0044] The step of reconstructing the direction of the analog output signal based on the structure of the detection device and using a corresponding direction reconstruction algorithm to obtain the predicted direction includes:

[0045] The directions of the aforementioned muon events are reconstructed using a corresponding direction reconstruction algorithm to obtain the predicted directions of the aforementioned muon events, as well as the distribution of the angles between the predicted directions and the initial directions.

[0046] For each of the remaining muon events other than the aforementioned muon events, an angle is obtained from the distribution of the angles, and the predicted direction of each of the remaining muon events is obtained based on the angle and the initial direction of each of the remaining muon events.

[0047] Optionally, obtaining the predicted value of the muon differential current strength for each directional interval based on the muon direction prediction distribution includes:

[0048] Based on the predicted distribution of muon directions, count the number of muon events whose predicted directions fall within each of the predicted direction intervals;

[0049] The strong prediction value of the muon differential current for each directional interval is determined based on the number of muon events falling within each directional interval.

[0050] Optionally, the step of removing the background electrical signal from the electrical signals based on the sum of the energy sequences of each of the electrical signals to obtain the electrical signal of the second muon includes:

[0051] Obtain the energy threshold;

[0052] The electrical signal corresponding to the energy in the energy sequence that is less than the energy threshold is determined as the background electrical signal;

[0053] The background electrical signal is removed from each of the electrical signals to obtain the electrical signal of the second muon.

[0054] Optionally, the reconstruction direction of the second muon is obtained based on the time series of the electrical signal of the second muon, including:

[0055] Remove the time information of the second muon incident on the detection device from the time sequence of the electrical signal of the second muon;

[0056] The Monte Carlo simulation method was used to simulate the response caused by the deposition of energy by charged particles in the target material, and the time when each photomultiplier tube received optical photons was obtained in each simulation process.

[0057] Multiple templates are obtained based on the time it takes for each photomultiplier tube to receive an optical photon during each simulation.

[0058] The distances between the plurality of templates and the second muon are obtained respectively, and a plurality of target templates are determined from the plurality of templates based on the distances, wherein the distance between the target template and the second muon is less than the distance between the non-target template and the second muon;

[0059] The weight of each target template is determined based on the distance between each target template and the second muon;

[0060] The reconstruction direction of the second muon is determined based on the weight of each target template and the incident direction of the muon in each target template.

[0061] Optionally, determining the standard deviation of each directional interval based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval includes:

[0062] Based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval, the dimensionless number of each directional interval is determined. The dimensionless number of a directional interval represents the difference between the material density of the target geological body whose reconstructed direction falls on the second muon track in that directional interval and the reference density.

[0063] The uncertainty of the dimensionless number of each direction interval is determined based on the number of the second muons in each direction interval.

[0064] The standard deviation of each directional interval is determined based on the uncertainty of each directional interval and the dimensionless number of each directional interval.

[0065] The step of determining whether the measured density of each directional interval deviates from the reference density based on the standard deviation of each directional interval includes:

[0066] If the standard deviation of a given directional interval is greater than a preset value and the dimensionless number of the given directional interval is greater than 1, then the measured density of the target geological body within that directional interval is determined to be less than the reference density.

[0067] If the standard deviation of a given directional interval is greater than a preset value and the dimensionless number of the given directional interval is less than 1, it indicates that the measured density of the target geological body within that directional interval is greater than the reference density.

[0068] The embodiments disclosed herein have the following advantages:

[0069] In this embodiment, the target geological body model can be determined using a reference density and contour parameterized model, with the target geological body reaching a depth of kilometers underground. Simulations can then be performed based on the initial cosmic ray model and the target geological body model to determine muon events reaching the detection device. The detection device can be a spherical total liquid scintillation 4π solid angle detector or other detection devices. Depending on the type of detection device, the direction of the muon events can be corrected to obtain a predicted distribution of muon directions, thereby obtaining predicted values ​​of muon differential current intensity for each direction interval. Specifically, when the detection device is a spherical total liquid scintillation 4π solid angle detector, the response correction of the muon events can be performed based on the time series and / or energy series corresponding to each photomultiplier tube in the spherical total liquid scintillation 4π solid angle detector to obtain the predicted distribution of muon directions. Thus, this embodiment provides a method for predicting underground kilometer-level muon current intensity applicable to a spherical total liquid scintillation 4π solid angle detector, and is also applicable to other types of detection devices. Subsequently, the location of the density variation zone of the target geological body can be determined based on the predicted value of the muon differential flow intensity. Attached Figure Description

[0070] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments of this disclosure will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 This is a flowchart illustrating the steps of a method for predicting muon current intensity at a depth of 1,000 meters underground, as described in this disclosure.

[0072] Figure 2 This is a schematic diagram illustrating the orientation of the muon in an embodiment of this disclosure;

[0073] Figure 3 This is a flowchart illustrating the steps for determining the location of the density change region in an embodiment of this disclosure. Detailed Implementation

[0074] To make the above-mentioned objectives, features and advantages of this disclosure more apparent and understandable, the disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0075] Reference Figure 1 The diagram illustrates a flowchart of a method for predicting muon flow intensity at a depth of one kilometer underground, as shown in this embodiment of the present disclosure. Figure 1 As shown, the method for predicting muon flow intensity at a depth of 1,000 meters underground may specifically include steps S11 to S16.

[0076] Step S11: Obtain the initial cosmic ray model, which includes the distribution of energy and direction followed by the first muon before entering the geological body.

[0077] The initial cosmic ray model can be an empirical model, a Monte Carlo simulation model determined based on atmospheric material parameters and the physical mechanisms of muon generation and propagation, or a fitting model based on measurement data. The total flux of the first muon in the initial cosmic ray model can be set as F0. Optionally, the empirical model can be a model determined based on Gaisser's law. The first muon refers to the simulated cosmic ray muon. The initial cosmic ray model includes the energy and direction distribution of multiple first muons before entering a geological body. Sampling the initial cosmic ray model can yield the energy and direction followed by the first muons before entering the geological body.

[0078] For ease of description, the direction of the muon's track is defined as the direction of the muon, denoted by the azimuth angle φ and the zenith angle θ, as defined below. Figure 2As shown in the diagram. The Z-axis is vertically upward, while the X and Y axes are horizontal. Since muons fly from top to bottom, the detection device should be placed below the lowest horizontal plane of the region of interest (ROI) of the target geological body. The ROI can be the entire target geological body or a part of it.

[0079] This disclosure utilizes high-energy muons (energy at several GeV and above), which are extremely relativistic particles. Their interaction with the target matter can be considered independent of kinetic energy; that is, their kinetic energy cannot be measured by the detection device targeted by this disclosure. This disclosure utilizes the integral of muon flux with respect to kinetic energy, referred to as flux intensity. Furthermore, this disclosure utilizes the flux intensity within a certain directional interval, i.e., differential flux intensity.

[0080] Alternatively, the direction interval can be divided as follows: the range of cosθ values ​​[0,1] is divided into n... cosθ Divide the range of φ (0, 2π) into n parts. φ Let the interval be denoted as (i,j), and define the i-th cosθ interval × the j-th φ interval as the (i,j)-th direction interval, where 1≤i≤n. cosθ , 1≤j≤n φ .

[0081] Step S12: Obtain the contour parameterized model of the target geological body and the reference density of the target geological body, wherein the burial depth of the target geological body reaches the kilometer level underground.

[0082] The target geological body can be any geological body to be predicted. In this embodiment, the target geological body is located at a depth of kilometers. For example, if the target geological body is a mountain 1.5 kilometers high, and the detection device is placed at a height of 0.5 kilometers, the detection device can detect the portion of the mountain at a height of 0.5 kilometers to 1.5 kilometers, which represents a depth of 1 kilometer. The depth of the target geological body refers to the vertical distance from the highest point of the target geological body to the detection device. The location of the detection device is below the region of interest of the target geological body.

[0083] The contour parametric model of the target geological body is generated based on its contour information. The sampling points for the target geological body's contour information can be obtained through methods including, but not limited to, remote sensing and satellite surveying. The three-dimensional closed geometry spanned by the set of sampling points constitutes the contour parametric model of the target geological body. Optionally, the Delaunay triangulation method can be used to span the set of sampling points into a three-dimensional closed geometry.

[0084] This disclosure only considers the impact of changes in the internal density of the target geological body on muon flux or flow intensity. Optionally, it can be assumed that the percentage of elemental composition of the internal material of the target geological body is the same as the percentage of elemental composition of the Earth's crust. Before measuring the internal density of the target geological body, a priori assumptions can be made about the internal density of the target geological body based on prior information to obtain a reference density of the target geological body. Optionally, it can be assumed that the internal material density of the geological body is the same, and its density value can be the density value measured by sampling the material of the geological body, thereby obtaining the reference density of the target geological body.

[0085] Step S13: Determine the target geological body model based on the reference density of the target geological body and the contour parameterization model.

[0086] The density of the contour parameterized model of the target geological body is set to the assumed reference density of the target geological body, thus obtaining the target geological body model.

[0087] Step S14: Based on the initial cosmic ray model and the target geological body model, a simulation is performed to determine the muon event that reaches the detection device. The detection device is a spherical liquid scintillator with a 4π solid angle or other detection device.

[0088] The target geological body model is imported into a Monte Carlo simulation program based on the physical processes of muon-matter interaction. Optionally, this simulation program is based on Geant4 (GEometryANd Tracking), an open-source tool software commonly used in high-energy physics and medical physics.

[0089] The initial cosmic ray model is sampled to obtain the energy and direction of the first muon, and the initial position of each first muon is set as: a point on the ray outside the target geological body, passing through the center of the detection device, and with the direction of each first muon.

[0090] In the Monte Carlo simulation program, the interaction process between multiple first muons and the internal material of the target geological body is simulated. It is determined whether each first muon is blocked by the target geological body and unable to reach the detection device. Muon events that can pass through the target geological body and reach the detection device (i.e., not blocked by the target geological body) are retained, and the zenith angle and azimuth angle of the actual direction of the muon event reaching the detection device are recorded. The above simulation is repeated N times. MC To reduce the statistical uncertainty introduced during the simulation, N MCThe number of simulated events reaching the detection device should be very large, far exceeding the number of measured events. The detection device can be a spherical total liquid scintillation 4π solid angle detector or other detection devices; the spherical total liquid scintillation 4π solid angle detector is a type of detector whose directional resolution and detection efficiency are independent of the muon incident direction; other detection devices are those other than the spherical total liquid scintillation 4π solid angle detector. Other detection devices may include: detectors whose directional resolution and / or detection efficiency are related to the muon incident direction, and detectors other than the spherical total liquid scintillation 4π solid angle detector whose directional resolution and detection efficiency are independent of the muon incident direction.

[0091] Step S15: Based on the type of the detection device and the corresponding orientation reconstruction algorithm, the response correction of the muon event is performed to obtain the muon orientation prediction distribution. This includes: when the detection device is a spherical total liquid scintillator 4π solid angle detection device, the response correction of the muon event is performed based on the time series and / or energy series corresponding to each photomultiplier tube in the spherical total liquid scintillator 4π solid angle detection device to obtain the muon orientation prediction distribution.

[0092] Different types of detection devices require different direction reconstruction algorithms for responding to muon events. A suitable direction reconstruction algorithm can be selected based on the type of detection device to correct the response of muon events.

[0093] Optionally, for detection devices whose directional resolution and / or detection efficiency are related to the muon incident direction, the response correction for muon events can be performed according to the following method: Step a: Import the structure of the detection device into the simulation program. Optionally, the simulation program can be Geant4, an open-source tool software based on high-energy physics and medical physics research. Step b: Take the actual direction of the muon event as the initial direction of the muon in this simulation process, and use the simulation program described in step a to simulate the response process of the muon event in the detection device to obtain the output signal. Step c: Use the direction reconstruction algorithm corresponding to the detection device to reconstruct the direction of the output signal in step b. The reconstructed direction is the predicted direction. Repeat steps b and c. The distribution of the predicted directions is the muon direction prediction distribution. The corresponding direction reconstruction algorithm can refer to the direction reconstruction algorithm proposed in related technologies.

[0094] Optionally, for detection devices whose directional resolution and detection efficiency are independent of the muon incident direction (such as a spherical full liquid scintillator with a 4π solid angle), an equivalent direction reconstruction algorithm can be used to correct the response of muon events. Based on the structure of the detection device, the equivalent direction reconstruction algorithm is used to reconstruct the directions of a subset of muon events, obtaining the distribution of the angles between the reconstructed directions and the initial directions. For each other muon event, excluding the subset of muon events, an angle is obtained from the angle distribution, and the predicted direction of each other muon event is obtained based on this angle and the initial direction. Based on the predicted direction corresponding to each muon event, the predicted distribution of muon directions is obtained.

[0095] Optionally, response correction for a detection device whose directional resolution and detection efficiency are independent of the muon incident direction may include the following steps: Step a: Import the structure of the detection device into a simulation program. Optionally, the simulation program can be Geant4, an open-source tool software based on high-energy physics and medical physics research. Step b: Randomly and uniformly sample the directions of muon events as the initial muon directions in this simulation process. Use the simulation program described in step a to simulate the muon response process in the detection device and obtain the output signal. Step c: Use the direction reconstruction algorithm corresponding to the detection device to reconstruct the direction of the output signal in step b. The reconstructed direction is the predicted direction, and calculate the angle between the reconstructed direction and the initial direction. Step d: Repeat steps b and c, and statistically analyze the distribution of the angle in step c. Step e: Sample the angle distribution in step d to obtain an angle. Rotate the actual direction of the simulated muon event obtained in the previous section by this angle to obtain the predicted direction. Repeat step e. The distribution of the predicted directions obtained is the muon direction prediction distribution.

[0096] The orientation reconstruction algorithm corresponding to the spherical all-liquid scintillator 4π solid angle detector can be as follows: based on the time series and / or energy series corresponding to each photomultiplier tube in the spherical all-liquid scintillator 4π solid angle detector, the response correction of muon events is performed to obtain the predicted distribution of muon orientation.

[0097] A spherical all-liquid scintillator (4π solid angle detector) is a cosmic ray muon detector where the target material is a liquid scintillator, the shape is spherical, and the entire internal area, except for the photomultiplier tube (PMT) and supporting structure, is occupied by the liquid scintillator. For the entire 4π solid angle muon direction detection range, this type of device has the advantage of detection efficiency and directional resolution independent of the incident muon direction. In this type of detector, incident muons deposit energy in the target material, emitting optical photons. These optical photons are incident on the photocathode of the PMT in the detector, exciting electrons (called photoelectrons) with a certain probability (approximately 20-30%). The photoelectrons undergo a subsequent multiplication process to form the output electrical signal of the PMT. For the i-th PMT, the time T of its output electrical signal can be calculated. i and amplitude (optionally, represented by the number of photoelectrons) nPE i where 1≤i≤N PMT N PMT This refers to the number of PMTs. T i (1≤i≤N PMT The sequence composed of nPE is called a time series. i (1≤i≤N PMT The sequence composed of time and energy sequences is called the energy sequence. The time and energy sequences are the inputs to the analytical methods of the spherical total liquid scintillator 4π solid angle detector.

[0098] The spherical total liquid scintillation 4π solid angle detector possesses spherical symmetry, ensuring that the angle distribution between the muon measurement direction and the actual muon direction (hereinafter referred to as the angle distribution) is independent of the actual muon direction. The mean of the angle distribution (defined as angular resolution) is also independent of the actual muon direction, meaning the angular resolution is uniform. Simultaneously, the muon detection efficiency is also uniform. These two advantages eliminate the need for corrections to non-uniform angular resolution and detection efficiency, allowing its application in density imaging analysis within geological bodies.

[0099] An incident muon (which could be a first muon or a second muon as described later) corresponds to a track within the target material of the detection device. The time and number of optical photons received on the PMT are related to the relative position of the PMT to the track. Therefore, in the case of a muon event, T on the PMT... i and nPE i (1≤i≤N PMT The trajectory direction, i.e., the muon direction information, is contained within the time series and energy series (or solely from the time series, or solely from the energy series). The direction of the incident muon can be reconstructed from the time series and energy series (or solely from the time series, or solely from the energy series).

[0100] The following describes a method for reconstructing the incident muon direction solely based on the time series: The time information of the second muon's incident on the detection device is removed from the time series of the second muon's electrical signal; the response caused by the deposition of energy by charged particles in the target material is simulated using Monte Carlo simulation to obtain the time when each photomultiplier tube receives an optical photon during each simulation; multiple templates are obtained based on the time when each photomultiplier tube receives an optical photon during each simulation; the distances between the multiple templates and the second muon are obtained, and multiple target templates are determined from the multiple templates based on these distances, wherein the distance between the target templates and the second muon is less than the distance between the non-target templates and the second muon; the weight of each target template is determined based on its distance to the second muon; and the reconstructed direction of the second muon is determined based on the weight of each target template and the incident direction of the muon in each target template.

[0101] T i (1≤i≤N PMT The data records when muons entered the detection device. This information does not contain muon direction information and cannot be used by muon direction reconstruction algorithms. It can be removed using the following methods. Definition:

[0102]

[0103] Among them, t i The time series representing the i-th PMT, after removing information about when the muon was incident into the detector, i = 1, 2, ..., N PMT The meanings of the remaining characters can be found in the preceding text.

[0104] Monte Carlo simulations based on the detector structure can be used to obtain the response caused by the energy deposited by charged particles in the target material. The response index of interest in this disclosure is... That is, the time when an optical photon is received on the i-th PMT in the j-th Monte Carlo simulation of a muon event. Here, 1 ≤ j ≤ M, and M is the number of simulations. To reduce the impact of statistical uncertainty, M needs to be large. Similarly, define:

[0105]

[0106] in, The time series corresponding to the i-th PMT in the j-th Monte Carlo simulation muon event, after removing information about when the muon was incident on the detector; Characterize the time series corresponding to the k-th PMT in the j-th Monte Carlo simulation muon event, k = 1, 2, ..., N PMT The meanings of the remaining characters can be found in the preceding text.

[0107] For the j-th Monte Carlo simulation muon event, its incident direction P j It is artificially set, meaning it is known. P j The distribution is uniform, that is, let the zenith angle θ j and azimuth φ j It is P j When the corresponding zenith angle and azimuth angle are given, cosθ j It follows a uniform distribution in [-1,1], φ j The muons follow a uniform distribution in the range (0, 2π). Furthermore, the incident position of the muons on the outer surface of the spherical container is facing P. j The directions are uniformly distributed on the hemisphere. A simulated event is called a template, and j is defined as the template number.

[0108] Reconstruction direction P of incident muon case in It can be obtained by the following method:

[0109]

[0110] Where l is the l-th template closest to the incident muon instance, j l This is the template number, P. jl W is the incident direction of the muon in this template. jl It is P jl The weights are given by L, which is a constant to be determined.

[0111] Where d j The smaller the value, the closer the j-th template is to the incident muon instance, where:

[0112]

[0113] The meaning of each character can be found in the preceding text.

[0114] Optionally, the weight is defined as: W jl =1 / d jl .

[0115] The angle distribution and angular resolution can be used to evaluate the performance of the orientation reconstruction algorithm. Optionally, one calculation method is as follows: Generate test cases in the same way as the template, reconstruct the orientation of the test cases using the orientation reconstruction algorithm, and calculate the angle between the reconstructed orientation and the actual orientation. Repeat this step, and statistically analyze the distribution of this angle to obtain the desired angle distribution. The mean of this distribution is the desired angular resolution.

[0116] Step S16: Based on the predicted distribution of muon directions, obtain the predicted values ​​of the muon differential current strength for each direction interval.

[0117] Based on the predicted distribution of muon directions, the number of muon events whose predicted directions fall within each direction interval is counted; based on the number of muon events falling within each direction interval, the predicted value of the muon differential current in each direction interval is determined.

[0118] The number of muon events falling in the (i,j)th direction interval is nEvents MC (i,j), then the strong prediction value I of the muon differential current in this direction interval. MC (i,j)=nEvents MC (i,j)F0 / N MC .

[0119] By employing the technical solution of this disclosure, a target geological body model can be determined through a reference density and contour parameterized model of the target geological body. Simulations can then be performed based on the initial cosmic ray model and the target geological body model to determine muon events reaching the detection device. The detection device can be a spherical total liquid scintillator with a 4π solid angle or other detection devices. Furthermore, depending on the type of detection device, the direction of the muon events can be corrected to obtain a predicted distribution of muon directions, thereby obtaining predicted values ​​of muon differential current intensity for each direction interval.

[0120] In the case of a spherical all-liquid scintillator with a solid angle of 4π, the direction of muon events can be corrected based on the time series and / or energy series corresponding to each photomultiplier tube in the spherical all-liquid scintillator with a solid angle of 4π, thus obtaining the predicted distribution of muon directions.

[0121] Thus, this disclosure provides a method for predicting underground kilometer-level muon current intensity applicable to a spherical full liquid scintillation 4π solid angle detection device, and is also applicable to other types of detection devices.

[0122] As an example, the muon differential current intensity measurement values ​​for each directional interval can also be obtained. When the detection device is a spherical full liquid scintillator 4π solid angle detection device, obtaining the muon differential current intensity measurement values ​​for each directional interval may include steps S21 to S26:

[0123] Step S21: Based on the electrical signals output by each photomultiplier tube of the spherical total liquid scintillation 4π solid angle detection device, determine the time series and energy series corresponding to each photomultiplier tube. The electrical signals are generated based on the second muon that passes through the target geological body and reaches the spherical total liquid scintillation 4π solid angle detection device.

[0124] The second muon is a real muon that is incident on the spherical total liquid scintillation 4π solid angle detection device and elicits a response. The detection device is placed below the lowest horizontal plane where the region of interest of the target geological body is located to detect the region of interest of the target geological body and obtain the measured value of the muon differential current intensity.

[0125] The specific methods for determining the time and energy sequences corresponding to each photomultiplier tube can be found in the previous text and will not be repeated here.

[0126] Step S22: Based on the sum of the energy sequences of each of the electrical signals, remove the background electrical signal from the electrical signals to obtain the electrical signal of the second muon.

[0127] Optionally, an energy threshold is obtained; the electrical signal corresponding to the energy in the energy sequence that is less than the energy threshold is determined as the background electrical signal; the background electrical signal is removed from each of the electrical signals to obtain the electrical signal of the second muon.

[0128] Specifically, the different distributions of the total energy nPEtotal are used to distinguish between muon signals and background noise. Among them:

[0129]

[0130] The meaning of each character can be found in the preceding text.

[0131] For a detection device with an effective target volume sphere diameter of approximately 1 meter, the average energy deposited by muons in the target material is around 100 MeV. From an event rate perspective, the background energy caused by the deposition of charged particles from the decay of natural radionuclides in the target material dominates the muon background. Due to the characteristics of natural radioactive decay, this background deposition energy is generally less than 5 MeV. That is, the deposition energy of the muon signal is an order of magnitude greater than the background deposition energy. In the target material, the deposition energy of charged particles is converted into the total energy of all optical photons, which is proportional to the number of optical photons, and thus proportional to the number of photoelectrons, and further proportional to nPEtotal. Here, optical photons are the collective term for scintillation photons and Cherenkov photons generated by the deposition energy of muons in the target material, and photoelectrons are the electrons emitted by optical photons at the photocathode of the photomultiplier tube. Because the light yield of liquid scintillator (the number of optical photons excited per unit deposition energy) is very large, the nPEtotal corresponding to deposition energies of MeV and above is very large, meaning the relative statistical uncertainty of nPEtotal is... The background noise is very small, meaning nPEtotal can be measured very accurately. By setting an nPEtotal threshold and only retaining events above the threshold, the background noise can be reduced to a negligible level while maintaining muon detection efficiency. Muon detection efficiency is defined as the number of muons exceeding the threshold divided by the number of incident muons whose tracks intersect with the target material. For simplicity, we will assume below that all events above the nPEtotal threshold are caused by muons.

[0132] Step S23: Obtain the time sequence and energy sequence of the electrical signal of the second muon output by each photomultiplier tube.

[0133] After distinguishing between the electrical signal of the second muon and the background electrical signal, the time series and energy series of the second muon electrical signal can be obtained from the second muon electrical signal.

[0134] Step S24: Obtain the reconstruction direction of the second muon based on the time series and / or energy series of the electrical signal of the second muon.

[0135] When the detection device is a spherical full liquid scintillator with a 4π solid angle, the reconstructed direction of the second muon can be obtained from the time series and / or energy series of the second muon's electrical signal. The specific method for obtaining the reconstructed direction of the second muon from the time series of its electrical signal can refer to the method for reconstructing the direction of the incident muon described above, and will not be repeated here.

[0136] Step S25: Obtain the detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillation 4π solid angle detection device.

[0137] For detection devices whose detection efficiency is independent of the incident direction (such as a spherical liquid scintillator with a 4π solid angle), the detection efficiency ξ and effective cross-sectional area S are defined and calculated as follows: Let C1 be the cross-section of the target volume of the detection device with the largest area perpendicular to the vertical direction. The target volume refers to the volume occupied by the target material. S1 is the area of ​​C1. A point is randomly and uniformly selected on C1, and the response of a muon moving vertically downwards with its track passing through that point is simulated in the detection device. This simulation is repeated Q0 times, and the number of muons satisfying the selection criteria is recorded as Q1. Then, when Q0 is large, ξ = Q1 / Q0, and S = S1ξ.

[0138] Step S26: Based on the reconstruction direction of the second muon, the detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillator 4π solid angle detection device, the measured values ​​of the muon differential current intensity in each direction interval are obtained.

[0139] Since the zenith angle θ of the actual muon direction satisfies cosθ≥0, this method does not consider muon events where the cosine of the zenith angle of the reconstructed direction is <0. The number of muon events nEvents(i,j) whose measurement direction falls within the (i,j)-th direction interval is counted. Let the data acquisition time be T, then the measured value of the muon differential current intensity within the (i,j)-th direction interval is: I mea (i,j)=nEvents(i,j) / (S(i,j)T).

[0140] When the detection device is not a spherical full liquid scintillation 4π solid angle detection device, but other detection devices, obtaining the muon differential current intensity measurement values ​​in each directional interval may include steps S31 to S35:

[0141] Step S31: Obtain the electrical signal output by the other detection device, the electrical signal being generated based on the third muon that passes through the target geological body and reaches the other detection device.

[0142] The third muon is a real muon that, when incident on other detection devices, elicits a response. After the third muon is incident on other detection devices, those devices can output an electrical signal caused by the third muon.

[0143] Step S32: Obtain the orientation reconstruction algorithm corresponding to the other detection devices.

[0144] Different types of detection devices use different orientation reconstruction algorithms. For other detection devices that are not spherical liquid scintillation 4π solid angle detectors, the orientation reconstruction algorithms corresponding to other detection devices in related technologies can be obtained. This invention does not limit the orientation reconstruction algorithms corresponding to other detection devices.

[0145] Step S33: Based on the direction reconstruction algorithm corresponding to the other detection devices and the electrical signals output by the other detection devices, obtain the reconstructed direction of the third muon.

[0146] By utilizing the orientation reconstruction algorithms corresponding to other detection devices, the electrical signals output by other detection devices can be corrected, thereby determining the reconstruction orientation of the third muon based on the corrected electrical signals.

[0147] Step S34: Obtain the detection efficiency and effective cross-sectional area of ​​the other detection devices.

[0148] For a detection device whose detection efficiency is related to the incident direction, it is necessary to define and calculate the detection efficiency ξ(i,j) and effective cross-sectional area S(i,j) for each (i,j) direction interval. The definition and calculation methods are similar to those for ξ and S.

[0149] For ease of description, the detection efficiency ξ and effective cross-sectional area S of the detection device whose detection efficiency is independent of the incident direction will also be denoted as ξ(i,j) and S(i,j) respectively. Note that for the detection device whose detection efficiency is independent of the incident direction, for any i and j (1≤i≤n) cosθ , 1≤j≤n φ For all ξ(i,j)=ξ, S(i,j)=S.

[0150] Step S35: Based on the reconstruction direction of the third muon, the detection efficiency and effective cross-sectional area of ​​the other detection devices, obtain the measured values ​​of the muon differential current intensity in each direction interval.

[0151] Since the zenith angle θ of the actual muon direction satisfies cosθ≥0, this method does not consider muon events where the cosine of the zenith angle of the reconstructed direction is <0. The number of muon events nEvents(i,j) whose measurement direction falls within the (i,j)-th direction interval is counted. Let the data acquisition time be T, then the measured value of the muon differential current intensity within the (i,j)-th direction interval is: I mea (i,j)=nEvents(i,j) / (S(i,j)T).

[0152] As an example, based on the above technical solution, such as Figure 3 As shown, the location of the density change region can be determined based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval, specifically including steps S41 to S43:

[0153] Step S41: Determine the standard deviation of each direction interval based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each direction interval.

[0154] Based on the predicted value I of the muon differential current intensity in each directional interval. MC (i,j) and the measured value of the muon differential current intensity I mea (i,j), determine the dimensionless number η of each directional interval. i,j =I mea (i,j) / I MC (i,j), the dimensionless number represents: the reconstruction direction falls within each of the direction intervals (i,j). i,j The difference between the material density of the target geological body and the reference density is obtained from the second or third muon track. The uncertainty of the dimensionless number for each directional interval is determined based on the number of second or third muons in each directional interval. Let Δη i,j For η i,j The uncertainty includes statistical uncertainty and systematic uncertainty. When n is much greater than 1, the statistical uncertainty can be considered as...

[0155] The statistical uncertainty equal to nEvents(i,j) The system uncertainty can be obtained through Monte Carlo simulation. Based on the uncertainty and dimensionless number of each directional interval, the standard deviation δ of each directional interval is determined. i,j .

[0156] Step S42: Determine whether the measured density of each directional interval deviates from the reference density based on the standard deviation of each directional interval.

[0157] Based on the standard deviation of each directional interval and the reference density of the target geological body, it can be determined whether the measured density of each directional interval deviates from the reference density, including: if the standard deviation of a directional interval is greater than a preset value and the dimensionless number of the directional interval is greater than 1, it indicates that the measured density of the target geological body in that directional interval is less than the reference density; if the standard deviation of a directional interval is greater than a preset value and the dimensionless number of the directional interval is less than 1, it indicates that the measured density of the target geological body in that directional interval is greater than the reference density.

[0158] If the standard deviation δ i,j The following conditions must be met:

[0159]

[0160] Characterize the ( i,j The density of the target geological body within the directional intervals differs from the reference density by m standard deviations or more, and η i,j -1 > (<) 0 indicates that the internal density of the target geological body is less than (greater than) the reference density. Optionally, m can be 3, 5 or other positive numbers.

[0161] Step S43: Determine the location of the density change zone based on whether the measured density of each directional interval deviates from the reference density, wherein the measured density of the directional interval where the density change zone is located deviates from the reference density.

[0162] If the measured density in a certain directional interval deviates from the reference density, then the target geological body in that directional interval is located in the density variation zone.

[0163] This disclosure presents a technical solution applicable to various types of detection devices, capable of determining the location of density variation zones. It also proposes a background subtraction algorithm and a direction reconstruction algorithm for a spherical total liquid flashover 4π solid angle detection device. Combined with the geological tomography imaging method applicable to various types of detection devices proposed in this disclosure, it makes it possible to apply the spherical total liquid flashover 4π solid angle detection device to the field of geological exploration.

[0164] Those skilled in the art should understand that the embodiments of this disclosure are not limited to the described order of actions, because according to the embodiments of this disclosure, some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of this disclosure.

[0165] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0166] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0167] This disclosure describes embodiments of methods, apparatus, electronic devices, and computer program products according to embodiments of this disclosure with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0168] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0170] While preferred embodiments of the present disclosure have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the present disclosure.

[0171] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0172] The above provides a detailed description of a method for predicting muon current intensity at depths of 1,000 meters underground. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of this disclosure. Therefore, the content of this specification should not be construed as a limitation of this disclosure.

Claims

1. A method for predicting muon flux intensity in a kilometer underground, characterized in that, include: Obtain an initial cosmic ray model, which includes the distribution of energy and direction followed by the first muon before it enters the geological body; Obtain the contour parametric model of the target geological body and the reference density of the target geological body, wherein the burial depth of the target geological body reaches the kilometer level underground; The target geological body model is determined based on the reference density of the target geological body and the contour parameterization model; Simulations are performed based on the initial cosmic ray model and the target geological body model to determine muon events that reach the detection device. The detection device is a spherical liquid scintillator with a 4π solid angle or other detection device. According to the type of the detection device, based on the corresponding orientation reconstruction algorithm, the muon event is responded to and corrected to obtain the muon orientation prediction distribution. This includes: when the detection device is a spherical full liquid scintillator 4π solid angle detection device, the muon event is responded to and corrected according to the time series and / or energy series corresponding to each photomultiplier tube in the spherical full liquid scintillator 4π solid angle detection device to obtain the muon orientation prediction distribution. Based on the predicted distribution of muon directions, the predicted values ​​of the muon differential current strength for each direction interval are obtained.

2. The method according to claim 1, wherein, In the case where the detection device is the spherical full liquid scintillation 4π solid angle detection device, it further includes: Based on the electrical signals output by each photomultiplier tube of the spherical total liquid scintillation 4π solid angle detection device, the time series and energy series corresponding to each photomultiplier tube are determined. The electrical signals are generated based on the second muon that passes through the target geological body and reaches the spherical total liquid scintillation 4π solid angle detection device. Based on the sum of the energy sequences of each of the electrical signals, the background electrical signal is removed from the electrical signals to obtain the electrical signal of the second muon; Obtain the time sequence and energy sequence of the electrical signal of the second muon output by each photomultiplier tube; The reconstruction direction of the second muon is obtained based on the time series and / or energy series of the electrical signal of the second muon; The detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillation 4π solid angle detection device were obtained; Based on the reconstruction direction of the second muon, the detection efficiency and effective cross-sectional area of ​​the spherical full liquid scintillator 4π solid angle detection device, the measured values ​​of the muon differential current intensity in each directional interval are obtained.

3. The method according to claim 1, wherein, If the detection device is one of the other detection devices, it further includes: Acquire the electrical signals output by the other detection devices, wherein the electrical signals are generated based on the third muon that passes through the target geological body and reaches the other detection devices; Obtain the orientation reconstruction algorithm corresponding to the other detection devices; The reconstructed direction of the third muon is obtained based on the direction reconstruction algorithm corresponding to the other detection devices and the electrical signals output by the other detection devices. Obtain the detection efficiency and effective cross-sectional area of ​​the other detection devices; Based on the reconstruction direction of the third muon, the detection efficiency and effective cross-sectional area of ​​the other detection devices, the measured values ​​of the muon differential current intensity in each directional interval are obtained.

4. The method according to claim 2 or 3, characterized in that, Also includes: The standard deviation of each directional interval is determined based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval. Based on the standard deviation of each directional interval, determine whether the measured density of each directional interval deviates from the reference density; The location of the density change zone is determined based on whether the measured density in each directional interval deviates from the reference density, wherein the measured density in the directional interval where the density change zone is located deviates from the reference density.

5. The method according to claim 1, wherein, The process of determining muon events reaching the detection device through simulation based on the initial cosmic ray model and the target geological body model includes: The target geological body model was imported into a Monte Carlo simulation program based on the physical processes of muon-matter interaction; By sampling the initial cosmic ray model, the energies and directions of multiple first muons are obtained; The initial position of each of the first muons is set as: outside the target geological body, and on a ray passing through the center of the detection device and in the direction of each of the first muons; In the Monte Carlo simulation program, the interaction process between the plurality of first muons and the target geological body is simulated to determine muon events that arrive at the detection device.

6. The method according to claim 1, wherein, The step of adjusting the response of the muon event based on the type of the detection device and the corresponding orientation reconstruction algorithm to obtain the predicted distribution of muon orientations includes: The structure of the detection device is imported into the simulation response program; In the simulation response procedure, the direction of the muon event is used as the initial direction to simulate the response process of the muon event in the detection device, and a simulation output signal is obtained; Based on the structure of the detection device, a corresponding direction reconstruction algorithm is used to reconstruct the direction of the analog output signal to obtain the predicted direction. The structure of the detection device includes: a detection device structure whose direction resolution and / or detection efficiency are related to the muon incident direction, and a detection device structure whose direction resolution and detection efficiency are both independent of the muon incident direction. The predicted distribution of the muon direction is obtained based on the predicted directions corresponding to multiple muon events.

7. The method for predicting muon current intensity at a depth of kilometer underground according to claim 6, characterized in that, When the structure of the detection device is such that both its directional resolution and detection efficiency are independent of the muon incident direction. In the simulation response procedure, the direction of the muon event is used as the initial direction to simulate the response process of the muon event in the detection device, resulting in a simulated output signal, including: In the simulation response procedure, the directions of a portion of muon events are randomly and uniformly sampled as initial directions, and the response process of the portion of muon events in the detection device is simulated to obtain the simulation output signal; The step of reconstructing the direction of the analog output signal based on the structure of the detection device and using a corresponding direction reconstruction algorithm to obtain the predicted direction includes: The directions of the aforementioned muon events are reconstructed using a corresponding direction reconstruction algorithm to obtain the predicted directions of the aforementioned muon events, as well as the distribution of the angles between the predicted directions and the initial directions. For each of the remaining muon events other than the aforementioned muon events, an angle is obtained from the distribution of the angles, and the predicted direction of each of the remaining muon events is obtained based on the angle and the initial direction of each of the remaining muon events.

8. The method for predicting muon current intensity at a depth of kilometer underground according to claim 1, characterized in that, The step of obtaining the predicted value of the muon differential current strength for each direction interval based on the muon direction prediction distribution includes: Based on the predicted distribution of muon directions, count the number of muon events whose predicted directions fall within each of the predicted direction intervals; The strong prediction value of the muon differential current for each directional interval is determined based on the number of muon events falling within each directional interval.

9. The method for predicting muon flow intensity at a depth of kilometer underground according to claim 2, characterized in that, The step of removing the background signal from the sum of the energy sequences of each of the electrical signals to obtain the electrical signal of the second muon includes: Obtain the energy threshold; The electrical signal corresponding to the energy in the energy sequence that is less than the energy threshold is determined as the background electrical signal; The background electrical signal is removed from each of the electrical signals to obtain the electrical signal of the second muon.

10. The method for predicting muon flow intensity at a depth of kilometer underground according to claim 2, characterized in that, Based on the time series of the electrical signal of the second muon, the reconstruction direction of the second muon is obtained, including: Remove the time information of the second muon incident on the detection device from the time sequence of the electrical signal of the second muon; The Monte Carlo simulation method was used to simulate the response caused by the deposition of energy by charged particles in the target material, and the time when each photomultiplier tube received optical photons was obtained in each simulation process. Multiple templates are obtained based on the time it takes for each photomultiplier tube to receive an optical photon during each simulation. The distances between the plurality of templates and the second muon are obtained respectively, and a plurality of target templates are determined from the plurality of templates based on the distances, wherein the distance between the target template and the second muon is less than the distance between the non-target template and the second muon; The weight of each target template is determined based on the distance between each target template and the second muon; The reconstruction direction of the second muon is determined based on the weight of each target template and the incident direction of the muon in each target template.

11. The method for predicting muon current intensity at a depth of kilometer underground according to claim 4, characterized in that, The step of determining the standard deviation of each directional interval based on the predicted value and the measured value of the muon differential current intensity in each directional interval includes: Based on the predicted value of the muon differential current intensity and the measured value of the muon differential current intensity in each directional interval, the dimensionless number of each directional interval is determined. The dimensionless number of a directional interval represents the difference between the material density of the target geological body whose reconstructed direction falls on the second muon track in that directional interval and the reference density. The uncertainty of the dimensionless number of each direction interval is determined based on the number of the second muons in each direction interval. The standard deviation of each directional interval is determined based on the uncertainty of each directional interval and the dimensionless number of each directional interval. The step of determining whether the measured density of each directional interval deviates from the reference density based on the standard deviation of each directional interval includes: If the standard deviation of a given directional interval is greater than a preset value and the dimensionless number of the given directional interval is greater than 1, then the measured density of the target geological body within that directional interval is determined to be less than the reference density. If the standard deviation of a given directional interval is greater than a preset value and the dimensionless number of the given directional interval is less than 1, it indicates that the measured density of the target geological body within that directional interval is greater than the reference density.

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