Uranium content detection method and device, storage medium and electronic equipment

Abstract

This invention provides a uranium content detection method, device, storage medium, and electronic device, belonging to the field of mineral exploration technology. The uranium content detection method includes: acquiring well logging data, which includes hyperthermal neutron counts, thermal neutron counts, and macroscopic scattering cross-section information, obtained by logging after emitting pulsed neutrons into the well to be logged; calculating the formation uranium content based on the hyperthermal neutron counts, thermal neutron counts, and macroscopic scattering cross-section information using a pre-set formation uranium content calculation model, which is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method. This method can eliminate the errors caused by formation porosity and mineralization in the uranium content calculation process, improving the accuracy of formation uranium content evaluation and the efficiency of uranium ore detection.

Description

Technical Field

[0001] This invention relates to the field of mineral exploration technology, specifically to a uranium content detection method, a uranium content detection device, a machine-readable storage medium, and an electronic device. Background Technology

[0002] Heavier atomic nuclei, such as uranium-235, can undergo a chain reaction of nuclear fission, releasing a large amount of energy when neutrons are released. This is the foundation of nuclear power generation and nuclear weapons manufacturing. Nuclear power plants utilize the heat generated by nuclear fission reactions to generate electricity, and are currently one of the most important sources of electricity, boasting advantages such as low carbon emissions and high energy efficiency. A continuous and stable supply of enriched uranium is fundamental to maintaining the stable operation of nuclear power plants; therefore, efficient and accurate uranium ore detection technology is indispensable. Based on the different genesis of the uranium deposit's host block framework, domestic uranium deposits can be classified into sandstone-type uranium deposits, hard-rock-type uranium deposits, carbonaceous shale-type uranium deposits, and metamorphic uranium deposits. Among these, sandstone-type uranium deposits already account for more than 40%, and this proportion is expected to continue to increase in the future.

[0003] Currently, the evaluation of sandstone-type uranium deposits can be divided into two categories: direct detection and indirect detection. As an indirect detection method, natural gamma-ray spectroscopy logging determines the formation uranium content based on the uranium-radium balance by measuring the gamma rays emitted by radium. However, the uranium-radium balance coefficient requires the acquisition of downhole core data to determine the relative uranium content, which is time-consuming and increases exploration costs. Direct detection methods measure the instantaneous and delayed neutrons produced after neutrons interact with uranium, using the neutron-neutron ratio to evaluate the formation uranium content. This method features high evaluation accuracy and exploration efficiency, but it is significantly affected by formation water salinity, porosity, and clay content.

[0004] Therefore, existing methods for detecting uranium content are affected by the mineralization and porosity of the strata, resulting in low accuracy in uranium content calculation. Summary of the Invention

[0005] The purpose of this invention is to provide a uranium content detection method, a uranium content detection device, a machine-readable storage medium, and an electronic device. This uranium content detection method can eliminate the errors caused by formation porosity and mineralization in the uranium content calculation process, thereby improving the accuracy of formation uranium content evaluation and the efficiency of uranium ore detection.

[0006] To achieve the above objectives, the first aspect of this application provides a method for detecting uranium content, comprising: Acquire well logging data, which includes ultrathermal neutron counts, thermal neutron counts, and macroscopic capture cross-section information. The well logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information, the uranium content of the formation is calculated using a pre-set formation uranium content calculation model. This pre-set formation uranium content calculation model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method.

[0007] In this embodiment of the application, the preset uranium content calculation model for the formation is as follows: , in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

[0008] In this embodiment of the application, acquiring well logging data includes: The time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. Based on the time spectrum information, well logging data is obtained.

[0009] In this embodiment of the application, the time spectrum information includes the ultrathermal neutron time spectrum and the thermal neutron time spectrum; The well logging data obtained based on the time spectrum information includes: The superthermal neutron count was determined based on the aforementioned superthermal neutron time spectrum. Based on the thermal neutron time spectrum, the thermal neutron count is determined; Single-exponential fitting is performed on the data within a preset time window in the thermal neutron time spectrum to obtain macroscopic capture cross-section information; Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic capture section information, well logging data is obtained.

[0010] In this embodiment of the application, obtaining the time spectrum information includes: Obtain the initial time spectrum of multiple cycles, wherein the initial time spectrum is a multi-channel time spectrum of one cycle; The initial time spectra of each cycle are accumulated according to the corresponding channel address to obtain the time spectrum information.

[0011] In this embodiment of the application, the time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after the logging tool emits pulsed neutrons into the well to be logged. The logging tool includes: a shell, and inside the shell, from bottom to top, a neutron source, a first composite material shield, an ultrathermal neutron detector, a second composite material shield, and a thermal neutron detector are arranged sequentially.

[0012] In this embodiment of the application, obtaining the time spectrum information includes: The neutron source is controlled to operate in the first time period of each cycle, so as to emit pulsed neutrons into the well to be measured in each cycle. The multichannel ultrathermal neutron time spectrum detected by the ultrathermal neutron detector is obtained, and a first time spectrum is obtained based on the multichannel ultrathermal neutron time spectrum; The multichannel thermal neutron time spectrum detected by the thermal neutron detector is obtained, and a second time spectrum is obtained based on the multichannel thermal neutron time spectrum; Time spectrum information is obtained based on the first time spectrum and the second time spectrum.

[0013] A second aspect of this application provides a uranium content detection device, comprising: The acquisition module is used to acquire logging data, which includes ultrathermal neutron count, thermal neutron count, and macroscopic capture section information. The logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. The calculation module is used to calculate the uranium content of the formation based on the ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information using a pre-set formation uranium content calculation model. The pre-set formation uranium content calculation model is obtained by establishing a numerical simulation model of uranium content, mineralization, and porosity conditions using the Monte Carlo method.

[0014] In this embodiment of the application, the preset uranium content calculation model for the formation is as follows: , in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

[0015] In this embodiment of the application, the acquisition module includes: The time spectrum unit is used to acquire time spectrum information, which is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. The extraction unit is used to obtain well logging data based on the time spectrum information.

[0016] A third aspect of this application provides an electronic device, the electronic device comprising: At least one processor; A memory connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor implements the uranium content detection method described above by executing the instructions stored in the memory.

[0017] A fourth aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned uranium content detection method.

[0018] The above technical solution involves acquiring well logging data, including hyperthermal neutron counts, thermal neutron counts, and macroscopic trapping cross-section information. This data is obtained by logging after emitting pulsed neutrons into the well to be logged. Based on the hyperthermal neutron counts, thermal neutron counts, and macroscopic scattering cross-section information, a pre-set formation uranium content calculation model is used to calculate the formation uranium content. This model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method. By acquiring hyperthermal neutron counts, thermal neutron counts, and macroscopic trapping cross-section information, a direct characterization relationship between the information and the formation uranium content is established using the pre-set formation uranium content calculation model. This model utilizes the Monte Carlo method to establish numerical simulation models under different uranium content, mineralization, and porosity conditions. Extensive random simulation experiments are conducted using the Monte Carlo method to simulate the transport process of radioactive particles in different models. Through in-depth analysis of the simulation data, the quantitative relationship between uranium content and the detection signal is accurately obtained, thereby achieving accurate detection of uranium content. Furthermore, by comparing the detection results under different mineralization and porosity models, the interference characteristics of these environmental factors on the detection signal are clearly identified, thereby effectively eliminating the environmental influences such as mineralization and porosity. This enables the detection of uranium content while eliminating the environmental influences of mineralization and porosity. Utilizing the neutron field characteristics after the interaction between neutrons and formation elements, and between neutrons and uranium-235, a uranium content evaluation method combining hyperthermal neutron count information, thermal neutron count information, and macroscopic capture cross-sections is established. This method can eliminate the errors caused by formation porosity and mineralization in the uranium content calculation process, improving the accuracy of formation uranium content evaluation and the efficiency of uranium ore detection.

[0019] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 The schematic diagram illustrates a flow chart of a uranium content detection method according to an embodiment of this application; Figure 2 This illustration schematically shows a structural diagram of a controllable neutron source thermal neutron-hyperthermal neutron uranium ore logging instrument according to an embodiment of this application; Figure 3 The illustration schematically shows hyperthermal neutron time spectra under different uranium ore grades according to embodiments of this application; Figure 4 The illustration schematically shows thermal neutron time spectra under different uranium ore grades and porosities according to embodiments of this application; Figure 5 The diagram illustrates the response of the superthermal neutron-thermal neutron count ratio under different uranium ore grades and mineralization conditions according to embodiments of this application. Figure 6 This illustration shows a comparison between the results of calculating uranium content using conventional counting ratios and the novel method according to embodiments of this application, and the actual uranium content. Figure 7 The schematic diagram illustrates a structural schematic of a uranium content detection device according to an embodiment of this application; Figure 8 The diagram illustrates the internal structure of a computer device according to an embodiment of this application.

[0021] Explanation of reference numerals in the attached figures 1-DT controllable neutron source; 2-First composite material shield; 3-Ultrathermal neutron He-3 detector; 4-Second composite material shield; 5-Thermal neutron He-3 detector; 6-Formation; 7-Wellbore; 8-Instrument housing; 410-Acquisition module; 420-Computation module; A01-Processor; A02-Network interface; A03-Internal memory; A04-Display screen; A05-Input device; A06-Non-volatile storage medium; B01-Operating system; B02-Computer program. Detailed Implementation

[0022] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0023] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0024] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0025] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0026] Please refer to Figure 1 , Figure 1 The schematic diagram illustrates a flow chart of a uranium content detection method according to an embodiment of this application. This embodiment provides a uranium content detection method, including the following steps: Step 210: Acquire logging data, which includes ultrathermal neutron count, thermal neutron count, and macroscopic capture cross-section information. The logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. In this embodiment, a pulsed neutron source device can be placed inside a logging instrument and slowly lowered into the well to be logged. Once activated, the pulsed neutron source emits pulsed neutrons into the surrounding formation according to a specific frequency and intensity pattern. After entering the formation, the neutrons undergo fission reactions with uranium-235. Detectors in the well can monitor various signals generated by the interaction between the neutrons and the formation, including the energy, quantity, and flight time of the scattered neutrons, as well as the energy and intensity of the gamma rays produced by the capture reaction. This monitoring data is rapidly transmitted to the surface via cable or other data transmission methods to obtain logging data. Specifically, a pulsed neutron source thermal neutron-hyperthermal neutron uranium ore logging instrument can be used to emit pulsed neutrons into the well. Then, the thermal neutron time spectrum and hyperthermal neutron time spectrum are recorded, and the hyperthermal neutron count, thermal neutron count, and macroscopic scattering cross-section information are extracted to obtain logging data.

[0027] In some embodiments, acquiring well logging data includes the following steps: First, time spectrum information is obtained, which is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested; In this embodiment, after a neutron interacts with matter, the detector records a series of time-related signals, the distribution of which constitutes a time spectrum. The time spectrum information mainly includes the time intervals between signals generated after neutron scattering or capture, the time of signal peak occurrence, and the duration of the signal. This information reflects the trajectory of high-energy neutrons in matter, the type of interaction, and the temporal characteristics of their reactions with different atomic nuclei.

[0028] Then, based on the time spectrum information, well logging data is obtained.

[0029] In this embodiment, the aforementioned time spectrum information includes the ultrathermal neutron time spectrum and the thermal neutron time spectrum. Ultrathermal neutrons refer to neutrons with energies greater than those of thermal neutrons. Thermal neutrons are neutrons in thermal equilibrium with the surrounding medium, and their energy distribution approximately conforms to the Maxwell-Boltzmann distribution. Their most probable energy (the energy value with the highest probability of occurrence) is approximately 0.025 eV at room temperature. Ultrathermal neutrons, on the other hand, typically have energies between 0.1 and 1000 eV, falling within the energy range between thermal neutrons and fast neutrons.

[0030] In some embodiments, the time spectrum information includes an ultrathermal neutron time spectrum and a thermal neutron time spectrum; correspondingly, obtaining well logging data based on the time spectrum information includes the following steps: The first step is to determine the superthermal neutron count based on the superthermal neutron time spectrum; In this embodiment, the superthermal neutron time spectrum records the distribution of various signals generated by the interaction between superthermal neutrons and surrounding matter along the time axis. Then, based on a counting window set according to the characteristic time range of the interaction between superthermal neutrons and specific matter, all detected signals are statistically analyzed within this counting window to obtain the superthermal neutron count.

[0031] The second step is to determine the thermal neutron count based on the thermal neutron time spectrum. In this embodiment, similar to the ultrathermal neutron counting process, the characteristic time interval of the interaction between thermal neutrons and matter can be determined first as the counting window, and then the number of detection signals can be counted within this window.

[0032] The third step is to perform single-exponential fitting on the data within a preset time window in the thermal neutron time spectrum to obtain macroscopic capture cross-section information. In this embodiment, after obtaining the thermal neutron time spectrum, a suitable preset time window is selected based on the capture characteristics of thermal neutrons in the formation or the analyte. Within this time window, the decay of the number of thermal neutron capture events over time approximately conforms to a single exponential function. The least squares method or other fitting algorithms can be used to perform a single exponential fit on the thermal neutron count data within the time window. During the fitting process, the values ​​of parameters such as the macroscopic capture cross-section are continuously adjusted to minimize the sum of squared errors between the fitted function and the actual measured data. When performing the fitting, statistical errors and potential systematic errors, such as the influence of detector energy resolution and time resolution on the data, can be fully considered. Through precise fitting calculations, the value of the macroscopic capture cross-section is finally determined. This value reflects the material's ability to capture thermal neutrons and is an important parameter characterizing material properties (such as formation lithology and pore fluid properties).

[0033] The fourth step involves obtaining well logging data based on the ultrathermal neutron count, thermal neutron count, and macroscopic capture section information.

[0034] In this embodiment, the ultrathermal neutron count, thermal neutron count, and macroscopic capture section information are interconnected and together reflect various characteristics of the formation or the material to be tested, thus constituting an important part of the well logging data.

[0035] For example, the total ultrathermal neutron count can be composed of counts recorded by the ultrathermal neutron detector within the 100-1000 μs range, i.e., the total count within this range is obtained from the ultrathermal neutron time spectrum; the total thermal neutron count can be composed of counts recorded by the remote detector within the 100-1000 μs range, i.e., the total count within this range is obtained from the thermal neutron time spectrum; the macroscopic trapping cross section is obtained by using single-exponential fitting within a 300-700 μs time window in the thermal neutron time spectrum. After obtaining the ultrathermal neutron count, thermal neutron count, and macroscopic trapping cross section information, well logging data can be obtained.

[0036] By determining the ultrathermal neutron count based on the ultrathermal neutron time spectrum and the thermal neutron count based on the thermal neutron time spectrum, and by performing single-exponential fitting on the data within a preset time window in the thermal neutron time spectrum, macroscopic capture section information can be obtained. This allows for the rapid and accurate acquisition of well logging data to characterize formation uranium content information.

[0037] In some embodiments, obtaining the time spectrum information includes the following steps: First, the initial time spectrum of multiple cycles is obtained, wherein the initial time spectrum is a multi-channel time spectrum of one cycle; In this embodiment, when acquiring a multichannel time spectrum for one cycle, a multichannel analyzer can be used to divide the time axis into multiple tiny time interval channels. Each channel acts as a time "container" to count the number of neutron detection events occurring within that specific time interval. When the electrical pulse signal generated by the detector is input into the multichannel analyzer, it is assigned to the corresponding time channel for counting based on the pulse's arrival time. As the measurement time progresses, the counts in each time channel accumulate, gradually forming a complete multichannel time spectrum for one cycle, visually demonstrating the distribution of neutron detection events on the time axis. The above measurement process needs to be repeated to obtain the initial time spectrum for multiple cycles.

[0038] Then, the initial time spectra of each cycle are accumulated according to the corresponding channel address to obtain the time spectrum information.

[0039] In this embodiment, the initial time spectrum of each cycle has a unified address division standard. This standard is pre-set by the multichannel analyzer, which divides the entire time range into numerous consecutive small time intervals, each time interval corresponding to an address. During the accumulation operation, for each address, the counts corresponding to that address in the initial time spectrum of different cycles are added sequentially. That is, if the detection event count corresponding to address 50 in the initial time spectrum of the first cycle is 100 times, the count corresponding to that address in the second cycle is 120 times, the count corresponding to that address in the third cycle is 90 times, and so on, then after accumulation, the total count corresponding to that address is the sum of all the counts at that address in each cycle. For example, in the above example, after accumulation, the total count corresponding to address 50 is 100 + 120 + 90 + … (the counts of that address in all subsequent cycles).

[0040] The time spectrum information obtained by accumulating the initial time spectra of each cycle according to the tunnel location effectively reduces data errors caused by various random interference factors in a single measurement, compared to the initial time spectrum of a single cycle. This makes the neutron-matter interaction law reflected by the time spectrum clearer and more accurate. The accumulated time spectrum information can provide a more reliable basis for judging the formation characteristics and can more intuitively reflect the changing trend of neutron absorption and scattering by the formation over time.

[0041] In some embodiments, the time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after the logging tool emits pulsed neutrons into the well to be logged. The logging tool includes: a housing, and inside the housing, from bottom to top, are arranged a neutron source, a first composite material shield 2, an ultrathermal neutron detector, a second composite material shield 4, and a thermal neutron detector.

[0042] In this embodiment, the logging tool can be a controlled neutron source thermal neutron-hyperthermal neutron uranium ore logging tool. The neutron source can be a DT controlled neutron source 1, the hyperthermal neutron detector can be a hyperthermal neutron He-3 detector 3, and the thermal neutron detector can be a thermal neutron He-3 detector 5. The yield of the DT controlled neutron source 1 is not less than 1×10⁸ / s; the diameter of the instrument housing 8 is set to 91 mm; the diameter of the hyperthermal neutron detector is set to 25.4 mm, the length to 112 mm, and the distance between it and the DT controlled neutron source 1 is set to 30 cm; the diameter of the thermal neutron detector is set to 39 mm, the length to 237 mm, and the distance between it and the DT controlled neutron source 1 is set to 60 cm. The gas pressure of the hyperthermal neutron detector is 4 atmospheres, and the gas pressure of the thermal neutron detector is 6 atmospheres. The length of the first composite material shield 2 of the controllable neutron source thermal neutron-superthermal neutron uranium ore logging instrument can be set to 2~6cm, the length of the second composite material shield 4 can be set to 2~6cm, the diameter of the first composite material shield 2 and the second composite material shield 4 can both be set to 80mm, and the first composite material shield 2 and the second composite material shield 4 are made of polytetrafluoroethylene containing 5% boron.

[0043] A logging instrument is constructed by sequentially arranging a neutron source, a first composite material shield 2, an ultrathermal neutron detector, a second composite material shield 4, and a thermal neutron detector inside the casing from bottom to top. After the logging instrument emits pulsed neutrons into the well to be logged, the time spectrum after the neutrons in the well interact is recorded, thereby quickly obtaining time spectrum information.

[0044] In some embodiments, obtaining the time spectrum information includes the following steps: First, the neutron source is controlled to operate in the first time period of each cycle, so as to emit pulsed neutrons into the well to be measured in each cycle. In this embodiment, the first time can be preset, for example, if the cycle duration is 1000μs, the first time is: the first 40μs of each cycle.

[0045] Then, the multichannel ultrathermal neutron time spectrum detected by the ultrathermal neutron detector is obtained, and a first time spectrum is obtained based on the multichannel ultrathermal neutron time spectrum; In this embodiment, the first time spectrum is the ultrathermal neutron time spectrum, which is obtained by accumulating the time spectra of multiple ultrathermal neutron channels according to their respective channel addresses.

[0046] Then, the multichannel thermal neutron time spectrum detected by the thermal neutron detector is obtained, and a second time spectrum is obtained based on the multichannel thermal neutron time spectrum; In this embodiment, the second time spectrum is the thermal neutron time spectrum, which is obtained by accumulating the multiple thermal neutron time spectra according to their respective channel addresses.

[0047] Finally, based on the first time spectrum and the second time spectrum, time spectrum information is obtained.

[0048] In this embodiment, the time spectrum information includes a first time spectrum and a second time spectrum. For example, the measurement timing cycle of the logging tool is 1000 μs. During the first 40 μs of each cycle, the pulse neutron generator operates and produces neutrons. During the time interval from 40 μs to 1000 μs, the pulse neutron generator does not operate. The hyperthermal neutron detector and the thermal neutron detector record 100 channels of hyperthermal and thermal neutron time spectra totaling 1000 μs. The time spectra of multiple cycles are accumulated according to the corresponding channel addresses to obtain the hyperthermal neutron time spectrum and thermal neutron time spectrum of a depth point, thus obtaining the time spectrum information.

[0049] Step 220: Based on the ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information, the formation uranium content is calculated using a pre-set formation uranium content calculation model. The pre-set formation uranium content calculation model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method.

[0050] In this embodiment, the pre-set uranium content calculation model for the formation was obtained by conducting numerical simulations of formations with different uranium contents, porosity, and mineralization using the Monte Carlo method. In an infinitely homogeneous uranium-bearing medium, under the condition that a pulsed neutron source emits a single neutron, uranium-235 undergoes a transient fission reaction with a thermal neutron, and the resulting ultrathermal neutron density distribution over time satisfies the following formula: (1) in, The uranium content of the strata, The thermal neutron lifetime of the homogeneous medium under study; This represents the macroscopic scattering cross section of the medium. It is a time-independent constant. Defined as follows: (2) in, and These represent the abundance and atomic weight of uranium-235, respectively. It is Avogadro's constant; The microscopic cross-section of thermal neutrons and uranium-235 undergoing thermal fission; This represents the average yield of superthermal neutrons produced per fission cycle. This is a reduction of the average logarithmic energy of a neutron-nucleus collision.

[0051] With output of A period of time after the pulsed neutron source finishes emitting the neutron pulse The total count of transient hyperthermal neutrons produced by thermal neutrons and thermal fission of uranium-235 can be expressed as: (3) Further integration yields: (4) According to the two-group diffusion theory, the thermal neutron density over time after fast neutrons generated by a pulsed neutron source are slowed down by the formation can be expressed as: (5) in, The thermal neutron density at time 0.

[0052] With output of A period of time after the pulsed neutron source finishes emitting the neutron pulse The thermal neutron count is: (6) Combining ultrathermal neutron flux distribution and thermal neutron flux distribution, the uranium content of the formation The relationship between the count ratio of ultrathermal neutrons and thermal neutrons can be established as follows: (7) Among them thermal neutron lifetime Macroscopic capture section of the strata The following relationship exists: (8) Combining formulas (7) and (8), the downhole uranium content can be characterized by thermal neutrons, ultrathermal neutrons, and macroscopic capture cross sections.

[0053] It should be noted that, using the Monte Carlo method, the stratigraphic model should include at least three types of stratigraphic mineralization: 0 ppm, 20,000 ppm, and 50,000 ppm; at least seven types of stratigraphic uranium grades: 0%, 0.0025%, 0.005%, 0.0075%, 0.01%, 0.02%, and 0.03%; and at least two types of porosity: 15% and 25%.

[0054] The ultrathermal neutron count extracted by ultrathermal neutrons increases with increasing formation uranium content, while the thermal neutron count and macroscopic trapping cross section count do not change with formation uranium content. With increasing porosity, the ultrathermal neutron count, thermal neutron count, and macroscopic trapping cross section values ​​increase. With increasing formation water salinity, the ultrathermal neutron count does not change with formation salinity, while the thermal neutron count and macroscopic trapping cross section increase with increasing formation salinity.

[0055] The formation uranium content characterization formula, composed of ultrathermal neutrons, thermal neutrons, and macroscopic capture cross sections, can be expressed by the following equation: (9) in, , , and The calibration coefficients of the formula are obtained by calibrating the response results under different porosity, mineralization, and uranium content conditions. The calibration coefficients of the above formula can be obtained through Monte Carlo numerical simulation, requiring at least three mineralization conditions (0 ppm, 20000 ppm, and 50000 ppm), seven formation uranium grades (0%, 0.0025%, 0.005%, 0.0075%, 0.01%, 0.02%, and 0.03%), and thermal neutron time spectra and ultrathermal neutron time spectra under two porosity conditions (15% and 25%). The formula coefficients are then obtained by fitting the data using the least squares method.

[0056] That is, the pre-set uranium content calculation model for the formation is: , in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

[0057] In this embodiment, after obtaining the information on the ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section, the uranium content of the formation can be obtained by substituting it into the aforementioned preset formation uranium content calculation model.

[0058] In the above implementation process, well logging data is acquired, including hyperthermal neutron counts, thermal neutron counts, and macroscopic trapping cross-section information. This data is obtained by logging after emitting pulsed neutrons into the well to be logged. Based on the hyperthermal neutron counts, thermal neutron counts, and macroscopic scattering cross-section information, a pre-set formation uranium content calculation model is used to calculate the formation uranium content. This model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method. By acquiring the hyperthermal neutron counts, thermal neutron counts, and macroscopic trapping cross-section information, a direct characterization relationship between the information and the formation uranium content is established using the pre-set formation uranium content calculation model. This model utilizes the Monte Carlo method to establish numerical simulation models under different uranium content, mineralization, and porosity conditions. Numerous random simulation experiments are conducted using the Monte Carlo method to simulate the transport process of radioactive particles in different models. Through in-depth analysis of the simulation data, the quantitative relationship between uranium content and the detection signal is accurately obtained, thereby achieving accurate detection of uranium content. Furthermore, by comparing the detection results under different mineralization and porosity models, the interference characteristics of these environmental factors on the detection signal are clearly identified, thereby effectively eliminating the environmental influences such as mineralization and porosity. This enables the detection of uranium content while eliminating the environmental influences of mineralization and porosity. Utilizing the neutron field characteristics after the interaction between neutrons and formation elements, and between neutrons and uranium-235, a uranium content evaluation method combining hyperthermal neutron count information, thermal neutron count information, and macroscopic capture cross-sections is established. This method can eliminate the errors caused by formation porosity and mineralization in the uranium content calculation process, improving the accuracy of formation uranium content evaluation and the efficiency of uranium ore detection.

[0059] The uranium content detection method provided in this embodiment has high sensitivity and can overcome the uranium content evaluation error caused by conventional natural gamma under uranium-radium imbalance conditions. It also eliminates the influence of formation mineralization on the uranium content evaluation of conventional ultrathermal neutron-thermal neutron ratio. This provides theoretical and technical support for sandstone-type uranium deposit content evaluation methods and the elimination of influencing factors on ultrathermal neutron-thermal neutron ratio uranium content evaluation parameters. Through simulated data experiments, the average absolute error of uranium content calculation is 0.006, compared to 0.036 for conventional ultrathermal neutron-thermal neutron ratio average uranium content calculation, representing an 83% reduction in error.

[0060] The following is a detailed explanation of the solution using specific examples: Based on the process of generating transient hyperthermal neutrons from the thermal neutron-induced uranium-235 fission reaction, a logging tool consisting of a DT source, a hyperthermal neutron detector, and a thermal neutron detector is used, such as... Figure 2As shown, the instrument housing 8 contains, from bottom to top, a DT controllable neutron source 1, a first composite material shield 2, a superthermal neutron He-3 detector 3, a second composite material shield 4, a thermal neutron He-3 detector 5, and the instrument housing 8. The logging tool is installed in the formation 6, and its specific parameters are shown below: The instrument housing 8 has a diameter of 91 mm. A first composite material shield 2 is filled between the DT controllable neutron source 1 and the superthermal neutron detector 3. The first composite material shield 2 has a length of 2-6 cm and a diameter of 80 mm, and is made of polytetrafluoroethylene (PTFE) containing 5% boron. The superthermal neutron detector 3 has a diameter of 25.4 mm, a length of 112 mm, and is 30 cm away from the DT controllable neutron source 1. It is filled with He-3 gas at 4 atmospheres. A second composite material shield 4 is filled between the superthermal neutron He-3 detector 3 and the thermal neutron He-3 detector 5. The second composite material shield 4 has a length of 2-6 cm, a diameter of 80 mm, and is made of PTFE containing 5% boron. The thermal neutron He-3 detector 5 has a diameter of 39 mm, a length of 237 mm, and is 60 cm away from the DT controllable neutron source 1. It is filled with He-3 gas at 6 atmospheres. The thermal neutron He-3 detector operates at 6 atmospheres.

[0061] The measurement timing cycle of the pulsed neutron source thermal neutron-hyperthermal neutron uranium ore logging tool is 1000 μs. During the first 40 μs of each cycle, the pulsed neutron generator 1 operates and generates neutrons. During the time from 40 μs to 1000 μs, the pulsed neutron generator does not operate. The hyperthermal neutron He-3 detector 3 and the thermal neutron He-3 detector 5 record 100 channels of hyperthermal and thermal neutron time spectra for a total of 1000 μs. The time spectra of multiple cycles are accumulated according to the corresponding channel addresses to obtain the hyperthermal and thermal neutron time spectra of a depth point.

[0062] Using the pulsed neutron source thermal neutron-hyperthermal neutron uranium ore logging tool described above, the thermal neutron time spectrum and hyperthermal neutron time spectrum are recorded, and hyperthermal neutron count, thermal neutron count, and macroscopic scattering cross section information are extracted to characterize the formation uranium content and eliminate the influence of porosity and mineralization on the uranium content characterization results. Specifically, the following steps are included: Step 1: Based on the neutron-induced 235U instantaneous fission theory and the thermal neutron two-group diffusion theory, the uranium content of the formation is characterized by a combination of ultrathermal neutron counting, thermal neutron counting, and macroscopic trapping cross-sections, as shown in Formula 10. (10) Among them thermal neutron lifetime Macroscopic capture section of the strata The following relationship exists: (11) Step 2.1: Using the Monte Carlo method, establish formation models with different uranium contents, porosity, and mineralization. Simulate continuous measurements on the wellbore using a pulsed neutron source thermal neutron-hyperthermal neutron uranium ore logging tool attached to the wellbore 7. The DT controllable neutron source 1 emits neutrons according to the designed timing sequence, and the time spectrum of the hyperthermal neutron detector is recorded as follows: Figure 3 The thermal neutron time spectrum information is shown below. Figure 4 As shown.

[0063] Step 2.2, according to Figure 3 Record the superthermal neutron time spectrum and extract the counts within the recording time range of 100-1000 μs as superthermal neutron count information. Figure 4 The thermal neutron time spectrum was recorded, and the counts within the recording time range of 100-1000 μs were extracted as thermal neutron count information. Single exponential fitting was used to process the counts within the time window of 300-700 μs in the thermal neutron time spectrum to extract the macroscopic capture section information of the formation.

[0064] Step 3: Based on the measurement response of thermal neutrons, hyperthermal neutrons, and macroscopic capture cross sections under strata with different uranium contents and different mineralization, and combined with the uranium content evaluation formula of the strata described in Step 1, a method for measuring uranium content by thermal neutron capture cross sections, hyperthermal neutron counts, and thermal neutron counts is formed, and its characterization formula is shown in Equation 12.

[0065] (12) in , , and The scale factor for the formula is obtained by scaling the response results under different porosity, mineralization, and uranium content conditions.

[0066] In this embodiment, the calibration coefficients of the uranium content characterization formula are obtained through Monte Carlo numerical simulation. As shown in step 2.1, at least three mineralization conditions (0 ppm, 20000 ppm, and 50000 ppm), seven formation uranium grades (0%, 0.0025%, 0.005%, 0.0075%, 0.01%, 0.02%, and 0.03%), and thermal neutron time spectra and ultrathermal neutron time spectra under two porosity formation conditions (15% and 25%) are obtained. The formula coefficients are obtained by fitting using the least squares method.

[0067] Figure 5The response diagrams for the superthermal neutron-thermal neutron count ratio under different uranium ore grades and mineralization conditions are shown. As the uranium ore grade increases, the superthermal neutron-thermal neutron count ratio increases. Under the same uranium ore grade, the superthermal neutron-thermal neutron count ratio decreases as the mineralization increases. The uranium grade characterization formula obtained by calibration under 0 mineralization conditions will result in uranium content calculation errors in mineralized water-bearing strata. Figure 6 The figure shows a comparison between the uranium content calculated using the conventional counting ratio and the new method, and the actual uranium content. The fission hyperthermal-thermal neutron uranium content detection method proposed in this example, which combines macroscopic trapping sections, can eliminate the influence of formation porosity and mineralization. The calculated uranium content is basically consistent with the actual uranium content of the formation, with an average absolute error of 0.006. The average absolute error of the conventional hyperthermal-thermal neutron uranium content calculation is 0.036.

[0068] Figure 1 This is a flowchart illustrating the uranium content detection method in the embodiments. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0069] Please refer to Figure 7 , Figure 7 The schematic diagram illustrates a structural schematic of a uranium content detection device according to an embodiment of this application. This embodiment provides a uranium content detection device, including an acquisition module 410 and a calculation module 420, wherein: The acquisition module 410 is used to acquire logging data, which includes ultrathermal neutron count, thermal neutron count and macroscopic capture section information. The logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. The calculation module 420 is used to calculate the uranium content of the formation based on the ultrathermal neutron count, thermal neutron count and macroscopic scattering cross section information using a preset formation uranium content calculation model. The preset formation uranium content calculation model is obtained by establishing a numerical simulation model of uranium content, mineralization and porosity conditions using the Monte Carlo method.

[0070] The pre-set uranium content calculation model for the formation is as follows: , in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and This is the scale factor.

[0071] The acquisition module 410 includes: The time spectrum unit is used to acquire time spectrum information, which is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. The extraction unit is used to obtain well logging data based on the time spectrum information.

[0072] The uranium content detection device includes a processor and a memory. The acquisition module 410 and the calculation module 420 are stored in the memory as program units, and the processor executes the program units stored in the memory to realize the corresponding functions.

[0073] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and uranium content detection can be achieved by adjusting the kernel parameters.

[0074] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0075] This invention provides a machine-readable storage medium storing a program that, when executed by a processor, implements the uranium content detection method.

[0076] This invention provides a processor for running a program, wherein the program executes the uranium content detection method during runtime.

[0077] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8As shown in the figure, the computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A06. The network interface A02 is used for communication with external terminals via a network connection. When the computer program is executed by the processor A01, it implements a uranium content detection method. The display screen A04 can be an LCD screen or an e-ink display screen. The input device A05 can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0078] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0079] In one embodiment, the uranium content detection method and apparatus provided in this application can be implemented as a computer program, and the computer program can be implemented in, for example... Figure 8 The computer device shown is used for operation. The computer device's memory can store the various program modules that make up the uranium content detection method apparatus, for example, Figure 7 The acquisition module 410 and calculation module 420 are shown. The computer program, composed of these modules, causes the processor to execute the steps in the uranium content detection methods of the various embodiments of this application described in this specification.

[0080] Figure 8 The computer device shown can be used as follows Figure 7 The acquisition module 410 in the uranium content detection method apparatus shown executes step 210. The computer device can execute step 220 via the calculation module 420.

[0081] This application provides an electronic device comprising: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the at least one processor implements the aforementioned uranium content detection method by executing the instructions stored in the memory. When the processor executes the instructions, it performs the following steps: Acquire well logging data, which includes ultrathermal neutron counts, thermal neutron counts, and macroscopic capture cross-section information. The well logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information, the uranium content of the formation is calculated using a pre-set formation uranium content calculation model. This pre-set formation uranium content calculation model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method.

[0082] In one embodiment, the pre-set uranium content calculation model for the formation is: , in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

[0083] In one embodiment, acquiring well logging data includes: The time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. Based on the time spectrum information, well logging data is obtained.

[0084] In one embodiment, the time spectrum information includes an ultrathermal neutron time spectrum and a thermal neutron time spectrum; The well logging data obtained based on the time spectrum information includes: The superthermal neutron count was determined based on the aforementioned superthermal neutron time spectrum. Based on the thermal neutron time spectrum, the thermal neutron count is determined; Single-exponential fitting is performed on the data within a preset time window in the thermal neutron time spectrum to obtain macroscopic capture cross-section information; Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic capture section information, well logging data is obtained.

[0085] In one embodiment, obtaining the time spectrum information includes: Obtain the initial time spectrum of multiple cycles, wherein the initial time spectrum is a multi-channel time spectrum of one cycle; The initial time spectra of each cycle are accumulated according to the corresponding channel address to obtain the time spectrum information.

[0086] In one embodiment, the time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after the logging tool emits pulsed neutrons into the well to be logged. The logging tool includes: a shell, and inside the shell, from bottom to top, a neutron source, a first composite material shield 2, an ultrathermal neutron detector, a second composite material shield 4, and a thermal neutron detector are arranged sequentially.

[0087] In one embodiment, obtaining the time spectrum information includes: The neutron source is controlled to operate in the first time period of each cycle, so as to emit pulsed neutrons into the well to be measured in each cycle. The multichannel ultrathermal neutron time spectrum detected by the ultrathermal neutron detector is obtained, and a first time spectrum is obtained based on the multichannel ultrathermal neutron time spectrum; The multichannel thermal neutron time spectrum detected by the thermal neutron detector is obtained, and a second time spectrum is obtained based on the multichannel thermal neutron time spectrum; Time spectrum information is obtained based on the first time spectrum and the second time spectrum.

[0088] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application 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.

[0089] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0090] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function 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 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0091] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable 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.

[0092] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0093] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0094] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0095] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0096] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method of detecting the presence of uranium, comprising: include: Acquire well logging data, which includes ultrathermal neutron counts, thermal neutron counts, and macroscopic capture cross-section information. The well logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information, the uranium content of the formation is calculated using a pre-set formation uranium content calculation model. This pre-set formation uranium content calculation model is based on a numerical simulation model of uranium content, mineralization, and porosity conditions established using the Monte Carlo method.

2. The method of claim 1, wherein, The pre-set uranium content calculation model for the formation is as follows: ， in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

3. The uranium content detection method according to claim 1, characterized in that, The acquisition of well logging data includes: The time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. Based on the time spectrum information, well logging data is obtained.

4. The uranium content detection method according to claim 3, characterized in that, The time spectrum information includes the ultrathermal neutron time spectrum and the thermal neutron time spectrum; The well logging data obtained based on the time spectrum information includes: The superthermal neutron count was determined based on the aforementioned superthermal neutron time spectrum. Based on the thermal neutron time spectrum, the thermal neutron count is determined; Single-exponential fitting is performed on the data within a preset time window in the thermal neutron time spectrum to obtain macroscopic capture cross-section information; Based on the aforementioned ultrathermal neutron count, thermal neutron count, and macroscopic capture section information, well logging data is obtained.

5. The uranium content detection method according to claim 3, characterized in that, The acquisition of time spectrum information includes: Obtain the initial time spectrum of multiple cycles, wherein the initial time spectrum is a multi-channel time spectrum of one cycle; The initial time spectra of each cycle are accumulated according to the corresponding channel address to obtain the time spectrum information.

6. The uranium content detection method according to claim 3, characterized in that, The time spectrum information is obtained by recording the time spectrum after the neutrons in the well interact with each other after the logging tool emits pulsed neutrons into the well to be logged. The logging tool includes: a shell, and inside the shell, from bottom to top, are arranged a neutron source, a first composite material shield, an ultrathermal neutron detector, a second composite material shield, and a thermal neutron detector.

7. The method of claim 6, wherein the step of detecting the presence of uranium is performed by detecting the presence of a uranium isotope. The acquisition of time spectrum information includes: The neutron source is controlled to operate in the first time period of each cycle, so as to emit pulsed neutrons into the well to be measured in each cycle. The multichannel ultrathermal neutron time spectrum detected by the ultrathermal neutron detector is obtained, and a first time spectrum is obtained based on the multichannel ultrathermal neutron time spectrum; The multichannel thermal neutron time spectrum detected by the thermal neutron detector is obtained, and a second time spectrum is obtained based on the multichannel thermal neutron time spectrum; Time spectrum information is obtained based on the first time spectrum and the second time spectrum.

8. A device for detecting the presence of uranium, comprising: include: The acquisition module is used to acquire logging data, which includes ultrathermal neutron count, thermal neutron count, and macroscopic capture section information. The logging data is obtained by logging after emitting pulsed neutrons into the well to be logged. The calculation module is used to calculate the uranium content of the formation based on the ultrathermal neutron count, thermal neutron count, and macroscopic scattering cross section information using a pre-set formation uranium content calculation model. The pre-set formation uranium content calculation model is obtained by establishing a numerical simulation model of uranium content, mineralization, and porosity conditions using the Monte Carlo method.

9. The device according to claim 8, characterized in that The pre-set uranium content calculation model for the formation is as follows: ， in, This is a macroscopic capture section of the strata. For ultrathermal neutron counting, For counting thermal neutrons, , , and For scale coefficients, This represents the uranium content of the strata.

10. The uranium content detection device according to claim 8, characterized in that, The acquisition module includes: The time spectrum unit is used to acquire time spectrum information, which is obtained by recording the time spectrum after the neutrons in the well interact with each other after a pulsed neutron is emitted into the well to be tested. The extraction unit is used to obtain well logging data based on the time spectrum information.

11. An electronic device, characterized in that, The electronic device includes: At least one processor; A memory connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor implements the uranium content detection method according to any one of claims 1 to 7 by executing the instructions stored in the memory.

12. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform the uranium content detection method according to any one of claims 1 to 7.

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