Reservoir attribute inversion method, device and equipment and storage medium

Abstract

The invention discloses a reservoir attribute inversion method, a reservoir attribute inversion device, reservoir attribute inversion equipment and a storage medium in the field of geophysical exploration, which are used for carrying out regional reservoir inversion prediction according to detected microseismic data and logging data and input drilling data and geological data, and comprises the following steps of: 1, acquiring the microseismic data and the logging data; using an anti-interference detector to detect micro-seismic data and detector tilt acceleration data in the area; step 2, data processing; and step 3, intelligent inversion. According to the method, the anti-interference performance is high, the physical interference resistance of the detector is improved through the anti-interference detector, the interfered seismic wave channels are screened, the subsequent data precision is improved, reservoir inversion is carried out on the collected data through the neural network model for deep learning, and reservoir inversion operation with higher efficiency and higher precision is carried out.

Description

Technical Field

[0001] The present invention belongs to the field of geophysical exploration, and specifically relates to a reservoir attribute inversion method, device, equipment and storage medium. Background Art

[0002] Reservoir property inversion is the process of inferring the physical properties and structural characteristics of underground rock reservoirs through mathematical models and algorithms using seismic data and related geological information. Seismic data is one of the main data sources for reservoir property inversion. Through the acquisition and processing of seismic data, the reflection wave information of underground rock reservoirs can be obtained, and then the physical properties and structural characteristics of the reservoirs can be inferred. Commonly used seismic reservoir inversion methods include post-stack inversion and pre-stack inversion. Well logging data is another important data source for reservoir property inversion. Well logging data can directly reflect the physical properties and structural characteristics of the reservoir, so it can be used as a constraint condition for seismic data inversion to improve the accuracy and reliability of the inversion. The methods of well logging data constraints include well logging curve reconstruction and well logging data assimilation.

[0003] With the advancement of science and technology and the increase in exploration needs, reservoir attribute inversion technology has undergone a transformation from simple to complex and from qualitative to quantitative. In the early days, it mainly relied on simple comparisons of geological models and logging data, and later gradually introduced inversion methods of seismic data, such as reflection seismic tomography, inversion waveforms, and reflection seismic inversion. In recent years, with the rise of artificial intelligence and machine learning technologies, reservoir attribute inversion technology has reached a new level, achieving more intelligent and accurate inversion.

[0004] In the existing reservoir property inversion methods, seismic data is still the most important data source, and the collection of seismic data reflection waves is completed by the connected and installed detectors. The detectors can well complete the collection of seismic wave information, but in some special environments such as strong winds and heavy rains, the detectors are easily affected by external physical interference, causing the detectors to tilt. When the tilt angle is greater than 40°, it will affect the detection accuracy of the detector, resulting in an increase in the subsequent reservoir inversion calculation error.

[0005] To this end, it is necessary to propose a reservoir property inversion method, device, equipment and storage medium that can enhance the stability of the detector, isolate external physical interference, use a neural learning network to deeply learn historical reservoir properties and automatically perform reservoir inversion based on the collected data. Summary of the invention

[0006] In order to solve the above problems, the purpose of the present invention is to provide a reservoir property inversion method, device, equipment and storage medium, which can improve the detector's ability to resist physical interference through anti-interference detectors, screen the disturbed seismic channels, improve the subsequent data accuracy, and perform reservoir inversion on the collected data through a deep learning neural network model to perform more efficient and higher-precision reservoir inversion operations.

[0007] In order to achieve the above object, the technical solution of the present invention is as follows: a reservoir attribute inversion method for performing regional reservoir inversion prediction based on detected microseismic data and logging data, input drilling data and geological data, comprising:

[0008] Step 1: Acquisition of microseismic data and well logging data: using well logging instruments to detect physical parameters in the well and physical properties of rock formations in the area to be inverted; using anti-interference geophones to detect microseismic data and geophone tilt acceleration data in the area to be inverted; the anti-interference geophones detect microseismic data under the protection of anti-interference components that resist physical interference; and the geophone tilt acceleration data is detected by an acceleration sensor installed on the anti-interference geophones;

[0009] Step 2: Data processing: microseismic data screening, denoising and logging data environment correction;

[0010] Step 3: Intelligent inversion: Input the processed microseismic data and logging data into the trained neural network model, and input the drilling data and geological data to obtain the regional reservoir inversion volume.

[0011] The principle of the basic scheme is to improve the stability and accuracy of the detector through anti-interference detectors, screen out seismic wave data with large errors, reduce the impact of individual data with large errors on reservoir inversion results, enhance the signal-to-noise ratio of the data through data denoising and environmental correction processing, and then improve the efficiency, accuracy and intelligence of reservoir inversion calculations through the operation of neural network models.

[0012] The beneficial effects of the basic scheme are: 1. This method integrates information from multiple data sources, including microseismic data, well logging data, drilling data and geological data, which can more comprehensively reflect the physical properties and structural characteristics of the reservoir. In addition, the learning ability of the neural network model can capture the complex relationship between data and improve the accuracy of reservoir inversion.

[0013] 2. Through reservoir inversion prediction, the number of unnecessary exploration wells can be reduced and exploration costs can be reduced. This method can provide more accurate reservoir information, help optimize oil and gas development plans, and improve development efficiency.

[0014] Furthermore, the anti-interference detector in step one includes a detector, and the portion of the outer periphery exposed to the surface under the detector working condition is covered with an anti-interference component, the anti-interference component includes a fixed plate, a plurality of fixed piles are fixedly connected to the outer periphery of the fixed plate, a support rod inclined to point above the detector is fixedly connected to the top of the fixed pile, and a protective film is fixedly connected to the support rod around the circumference.

[0015] The beneficial effects of the basic solution are: 1. The design of the anti-interference component can significantly reduce the impact of external interference factors on the data acquisition of the detector, such as wind, sand, rain, hail, etc. This helps to improve the accuracy and reliability of the collected microseismic data.

[0016] 2. The design of the fixing plate and the fixing pile can ensure the stability of the device. The combined structure of the support rod and the protective film can further enhance the wind resistance and stability of the entire equipment, ensuring that it can still work normally in harsh environments.

[0017] 3. By reducing the direct effects of external factors on the detector, the anti-interference component can reduce the risk of wear and damage to the equipment, thereby extending the service life of the equipment. The protective film can also prevent impurities such as wind, sand, and rain from entering the detector, reducing corrosion and damage to internal components.

[0018] 4. Since the anti-interference components can reduce the interference and damage to the detector caused by external factors, the maintenance frequency and cost of the equipment can be reduced. The design of vulnerable parts such as protective films is also easy to replace and maintain, reducing the difficulty and complexity of maintenance work.

[0019] Furthermore, the fixed pile includes a pile body, the outer wall of the pile body is fixedly connected to the fixing plate, a threaded hole is opened on the top wall of the pile body, a fixing bolt is threadedly matched in the threaded hole, and a spiral tip is fixedly connected to the bottom end of the fixing bolt.

[0020] The beneficial effects of the basic scheme are: 1. Matching of fixing bolts and threaded holes: Through thread matching, the fixing bolts can be tightly fixed in the threaded holes on the top wall of the pile body. This connection method is not only simple and reliable, but also can withstand greater tension or pressure, enhancing the stability of the structure.

[0021] 2. The spiral tip fixed at the bottom of the fixing bolt can easily penetrate the ground surface during installation, achieving fast and stable fixation. This design reduces the resistance and time during installation and improves work efficiency. Since the thread fit is adjustable, the tightness of the fixing bolt can be adjusted according to actual needs. This design makes the installation process more flexible and can adapt to different surface conditions and installation requirements.

[0022] 3. The design of the spiral tip can increase the friction between the pile and the ground, thereby improving the pull-out resistance of the pile. This design is particularly important in areas with strong winds or soft ground, and can ensure the stability of the pile. Since the fixing bolts are tightly fixed in the threaded holes on the top wall of the pile through threads, they can withstand large tensile forces. This design makes it difficult for the pile to be pulled out when subjected to external forces, further enhancing the stability of the structure.

[0023] Furthermore, an arc-shaped plate is fixedly connected to the outer periphery of the fixing plate where the fixing pile is not connected, the arc-shaped plate extends toward the ground, and a plurality of fixing cones are fixedly connected to the bottom wall of the fixing plate.

[0024] The beneficial effects of the foundation scheme are: 1. The curved plate extends underground and forms a certain angle with the ground surface. This design can increase the contact area between the fixed plate and the ground surface, thereby improving the stability of the entire structure. The design of the curved plate can also disperse the force of factors such as surface vibration or wind on the fixed plate, reducing the risk of structural damage caused by excessive force on a single point.

[0025] 2. The design of the fixing cone enables the fixing plate to quickly penetrate the ground surface and be fixed. This design is particularly suitable for situations where it is difficult to fix in soft soil or sand. The pointed design of the fixing cone can reduce the resistance of penetrating the ground surface and improve the installation efficiency.

[0026] 3. The fixing cone can penetrate deep below the ground surface and form a close contact with the soil, thereby increasing the stability of the fixing plate. The dispersed arrangement of multiple fixing cones can further improve the stability of the entire structure and prevent structural damage caused by excessive force at a single point.

[0027] Furthermore, the protective film has several through holes for passing the cables of the detector. The detector is equipped with an acceleration sensor for detecting the tilt acceleration of the detector. The tilt acceleration data is used to calculate the tilt angle of the detector, and the tilt angle is used to determine the availability of the detection data of the detector.

[0028] The beneficial effects of the basic solution are: 1. The through holes opened on the protective film allow the cables of the detector to pass through easily, thus achieving neat arrangement and management of the cables. This design not only improves the neatness of the equipment, but also reduces the potential risks caused by the clutter of cables.

[0029] 2. The neat arrangement and management of cables helps reduce the risk of equipment displacement or damage caused by cable dragging or entanglement. This design improves the stability of the equipment and ensures the accuracy of data collection.

[0030] 3. The accelerometer installed on the detector can detect the tilt acceleration of the detector in real time. This design enables the equipment to promptly detect and respond to tilt changes caused by factors such as surface vibration and wind, thereby ensuring the accuracy of data collection.

[0031] 4. By monitoring the tilt acceleration of the detector, the risk of tipping or displacement of the equipment can be discovered in time. This design helps to screen the data in advance, filter out the detector data with a tilt angle of more than 40° that has a greater impact on the seismic wave data, and reduce the calculation error of the reservoir inversion method.

[0032] Furthermore, the microseismic data screening process in step 2 refers to calculating the tilt of the geophone based on the data of the acceleration sensor, and screening out unusable geophone data according to the tilt angle of the geophone.

[0033] The beneficial effects of the basic solution are: 1. The tilt of the detector can be monitored in real time by the acceleration sensor, and its tilt angle can be accurately calculated. This step helps to timely detect measurement errors caused by equipment tilt, thereby filtering out data with large errors. Tilt angle monitoring and data filtering can significantly improve the accuracy and reliability of data, providing a high-quality data source for subsequent data analysis.

[0034] 2. Screening out unusable data based on the tilt angle of the detector can ensure that only stable and accurate data is used for subsequent analysis. This screening method helps to avoid the interference of noise and outliers in the data on the analysis results and improve the accuracy and reliability of data analysis.

[0035] 3. Accelerometers are not only used for data screening and processing, but can also be used as a monitoring tool for equipment stability. By real-time monitoring of the tilt angle of the detector, possible equipment failures or abnormal conditions can be discovered in time, so that necessary maintenance measures can be taken.

[0036] 4. Data screening and processing based on acceleration sensors can be automated, reducing manual intervention and data processing time. This automated processing method can significantly improve data processing efficiency and reduce labor costs.

[0037] Furthermore, the trained neural network model in step three refers to a neural network model that uses the extracted regional stratum spatial position, seismic information and reservoir parameters as learning samples to input the neural network model output reservoir attribute inversion model for repeated learning until the accuracy reaches the required level.

[0038] The beneficial effects of the basic scheme are: 1. The neural network model has a strong nonlinear fitting ability and can capture and learn the complex nonlinear relationships in the sample data. By taking the regional stratum spatial position, seismic information and reservoir parameters as input, the model can learn the intrinsic connection and law between these parameters, thereby improving the accuracy of the prediction.

[0039] 2. The trained neural network model can make fast and accurate predictions and judgments based on the input data. This provides data-driven decision support for seismic interpretation, reservoir prediction, etc., and helps reduce the errors and uncertainties of human judgment.

[0040] 3. During the training process, the neural network model will continuously learn and optimize its parameters to improve its ability to predict unknown data. By using a large number of learning samples for training, the model can learn a wider range of features and information, thereby enhancing its generalization ability to new data.

[0041] 4. Neural network models can automate data processing processes, reduce manual intervention and data processing time, which helps improve the efficiency and quality of data processing and reduce labor costs.

[0042] Furthermore, the present invention also provides a reservoir attribute inversion device, applicable to the reservoir attribute inversion method according to any one of claims 1 to 7, comprising:

[0043] Data acquisition module, used to collect microseismic data, well logging data and geophone tilt acceleration data;

[0044] The data processing module is used to process the collected data, calculate the detector inclination angle to screen the microseismic data, and the detector data with an inclination angle greater than 40° is judged as unusable, and the screened microseismic data is denoised and the logging data is environmentally corrected;

[0045] A neural network module is used to invert and calculate microseismic data, well logging data, drilling data and geological data according to parameter sample learning and obtain a reservoir inversion volume;

[0046] The report module is used to visualize and display reports based on the calculated reservoir inversion volume and detector tilt angle.

[0047] The beneficial effects of the basic scheme are: 1. Through the collaborative work of the data acquisition module and the data processing module, the quality of the data input to the neural network module can be significantly improved, which helps to improve the accuracy and reliability of reservoir attribute inversion.

[0048] 2. The neural network module uses powerful learning and fitting capabilities to accurately invert reservoir properties, which helps to solve the problems of insufficient accuracy and large errors that may exist in traditional inversion methods.

[0049] 3. The report module provides users with intuitive and clear reservoir attribute information through visual display and report generation. This helps users better understand the reservoir conditions and provides strong decision support for subsequent oil and gas exploration and development.

[0050] 4. The entire reservoir property inversion device realizes an automated and intelligent workflow, reducing manual intervention and data processing time. This helps to improve work efficiency and reduce labor costs.

[0051] Furthermore, the present invention also provides an electronic device, comprising:

[0052] processor;

[0053] Memory;

[0054] and a computer program, wherein the computer program is stored in the memory, the computer program comprising

[0055] Instructions, when the instructions are executed by the processor, enable the electronic device to execute the reservoir property inversion method described in any one of claims 1-7.

[0056] Furthermore, the present invention also provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the reservoir property inversion method described in any one of claims 1-7. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 Schematic diagram of a reservoir attribute inversion method in an embodiment of the present invention.

[0058] Figure 2 It is an axonometric diagram of an anti-interference detector in a reservoir property inversion method according to an embodiment of the present invention.

[0059] Figure 3 It is a lateral cross-sectional view of an anti-interference detector in a reservoir property inversion method according to an embodiment of the present invention.

[0060] Figure 4 Schematic diagram of a reservoir property inversion device in an embodiment of the present invention.

[0061] The figure marks in the drawings of the specification include: 1. detector; 2. fixed plate; 3. fixed cone; 4. arc plate; 5. pile body; 6. fixing bolt; 7. through hole; 8. protective film; 9. support rod; 10. acceleration sensor; 11. spiral tip. DETAILED DESCRIPTION

[0062] The following is further described in detail through specific implementation methods:

[0063] Example 1

[0064] Basically as attached Figure 1 A reservoir property inversion method is shown, which is used to perform regional reservoir inversion prediction based on detected microseismic data and well logging data, input drilling data and geological data, including:

[0065] Step 1: Acquisition of microseismic data and well logging data: using well logging instruments to detect physical parameters in the well and physical properties of rock formations in the area; using anti-interference geophones to detect microseismic data and geophone tilt acceleration data in the area to be inverted; the anti-interference geophones detect microseismic data under the protection of anti-interference components that resist physical interference; and the geophone tilt acceleration data is detected by an acceleration sensor installed on the anti-interference geophones;

[0066] Step 2: Data processing: microseismic data screening, denoising and logging data environment correction. Microseismic data screening refers to calculating the tilt of the geophone based on the data of the acceleration sensor, and filtering out unusable geophone data according to the tilt angle of the geophone;

[0067] Step three, intelligent inversion, extracting the spatial position of the regional layer, seismic information and reservoir parameters as learning samples and inputting them into the neural network model to output the reservoir attribute inversion model for repeated learning. After the accuracy reaches the required level, the processed microseismic data and logging data are input into the neural network model, and the drilling data and geological data are input to obtain the regional reservoir inversion volume.

[0068] Example 2

[0069] The difference from the above embodiment is that, as shown in the attached Figure 2 , Figure 3 As shown: the anti-interference detector 1 in step 1 includes a detector 1, a portion of the outer periphery of the detector 1 exposed to the surface under working conditions is covered with an anti-interference component, the anti-interference component includes a fixed plate 2, a plurality of fixed piles are welded to the outer periphery of the fixed plate 2, a support rod 9 tilted and pointing upward from the detector 1 is welded to the top of the fixed pile, a protective film 8 is circumferentially bonded to the support rod 9, an arc plate 4 is welded to the outer periphery of the fixed plate 2 where the fixed pile is not connected, the arc plate 4 extends toward the ground, and a plurality of fixed cones 3 are welded to the bottom wall of the fixed plate 2;

[0070] The fixed pile comprises a pile body 5, the outer wall of the pile body 5 is welded to the fixing plate 2, a threaded hole is opened on the top wall of the pile body 5, a fixing bolt 6 is threadedly matched in the threaded hole, and a spiral tip 11 is welded to the bottom end of the fixing bolt 6.

[0071] The protective film 8 is provided with a plurality of through holes 7 for passing the cable of the detector 1. The detector 1 is provided with an acceleration sensor 10 for detecting the tilt acceleration of the detector 1. The tilt acceleration data is used to calculate the tilt angle of the detector 1, and the tilt angle is used to determine the availability of the detection data of the detector 1.

[0072] The specific implementation process is as follows: install the anti-interference detector 1, and put the fixed plate 2 on the outside of the detector 1. First, compact the fixed plate 2 so that the fixed cone 3 on the bottom wall of the fixed plate 2 and the arc-shaped plate 4 on the periphery are deeply embedded in the ground, providing a certain pull-out resistance for the fixed plate 2. At the same time, press the ground around the detector 1 to prevent the dust and gravel on the ground from being blown up by the wind and impacting the detector 1. Then twist the fixing bolt 6 to make the spiral tip 11 at the bottom end of the fixing bolt 6 penetrate into the ground to provide a stronger grip. The protective film 8 is sleeved on the fixed pile by sleeve-joining the support rod 9. The protective film 8 is made of inelastic material to withstand the impact of strong wind, rain, dust and hail from the outside. The connection is made more stable by pouring water between the support rod 9 and the protective film 8. Then the cable of the detector 1 is passed through the through hole 7 opened on the protective film 8, which is convenient for arranging the cables and arranging the detectors 1 in sequence. The acceleration sensor 10 is installed on the top of the detector 1 to detect the inclination of the detector 1. When the inclination is too large, it will have a serious impact on the accuracy of the seismic wave data detected by the detector 1. Therefore, once the inclination angle is greater than 40°, the data detected by the detector is screened out to reduce the impact on the reservoir property inversion results.

[0073] Example 3

[0074] Corresponding to the above embodiment, as shown in the attached Figure 4 As shown: This embodiment provides a reservoir attribute inversion device, which is mainly composed of a data acquisition module, a data processing module, a neural network module and a reporting module. Among them:

[0075] The data acquisition module is used to collect microseismic data, well logging data and geophone tilt acceleration data;

[0076] The data processing module is used to process the collected data, calculate the detector inclination angle to screen the microseismic data, and the detector data with an inclination angle greater than 40° is judged as unusable. The screened microseismic data is denoised and the logging data is environmentally corrected.

[0077] The neural network module is used to invert and calculate microseismic data, logging data, drilling data and geological data according to parameter sample learning and obtain a reservoir inversion body.

[0078] The report module is used to visualize and display reports based on the calculated reservoir inversion volume and detector tilt angle.

[0079] The specific implementation process is as follows: the microseismic data detected by the detector, the logging data detected by the logging instrument and the detector tilt acceleration detected by the acceleration sensor are collected by the data acquisition module and transmitted to the data processing module. The detector tilt angle is calculated according to the algorithm. When the angle is greater than 40°, the seismic wave data detected by the detector is screened out, and then the screened seismic wave data is denoised by the data processing module, and the logging data is environmentally corrected. The processed seismic wave data and logging data are input into the neural network module together with the drilling data and geological data. The trained neural network module performs reservoir inversion calculation to obtain and output the reservoir inversion body. The reporting module visualizes the detector data screening results and the reservoir inversion body in a report to remind the staff to repair and calibrate the tilted detector.

[0080] Example 4

[0081] Corresponding to the above embodiment, this embodiment further provides an electronic device, including:

[0082] processor;

[0083] Memory;

[0084] And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes the method according to any one of claims 1.

[0085] The specific implementation process is as follows: The electronic device may include: a processor, a memory and a communication unit. These components communicate through one or more buses. Those skilled in the art can understand that the electronic device structure does not constitute a limitation on the embodiments of the present invention. It can be a bus structure or a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0086] The communication unit is used to establish a communication channel so that the electronic device can communicate with other devices.

[0087] The processor is the control center of the electronic device. It uses various interfaces and lines to connect the various parts of the entire electronic device. It runs or executes software programs and / or modules stored in the memory, and calls the data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor can include only a central processing unit (CPU). In an embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0088] Memory, used to store the execution instructions of the processor, the memory can be implemented by any type of volatile or non-volatile storage device or a combination of them, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0089] When the execution instructions in the memory are executed by the processor, the electronic device is enabled to execute part or all of the steps in the above method embodiments.

[0090] Example 5

[0091] Corresponding to the above embodiment, this embodiment further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described in claim 1.

[0092] The specific implementation process is as follows: the computer readable storage medium can be a magnetic disk, an optical disk, a read-only memory (English: read-only memory, abbreviated: ROM) or a random access memory (English: random access memory, abbreviated: RAM) and the like.

[0093] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0094] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A reservoir attribute inversion method for performing regional reservoir inversion prediction based on detected microseismic data and well logging data, input drilling data and geological data, characterized in that: include: Step 1: Acquisition of microseismic data and well logging data: using well logging instruments to detect physical parameters in the well and physical properties of rock formations in the area to be inverted; using anti-interference geophones to detect microseismic data and geophone tilt acceleration data in the area to be inverted; the anti-interference geophones detect microseismic data under the protection of anti-interference components that resist physical interference; and the geophone tilt acceleration data is detected by an acceleration sensor installed on the anti-interference geophones; Step 2: Data processing: microseismic data screening, denoising and logging data environment correction; Step 3: Intelligent inversion: Input the processed microseismic data and logging data into the trained neural network model, and input the drilling data and geological data to obtain the regional reservoir inversion volume.

2. The reservoir attribute inversion method according to claim 1, characterized in that: The anti-interference detector (1) in step 1 comprises a detector (1), wherein the outer periphery of the detector (1) exposed to the surface under working conditions is covered with an anti-interference component, wherein the anti-interference component comprises a fixed plate (2), wherein a plurality of fixed piles are fixedly connected to the outer periphery of the fixed plate (2), wherein the top of the fixed pile is fixedly connected to a support rod (9) inclined and pointing upwards from the detector (1), and a protective film (8) is fixedly connected to the support rod (9) in the circumferential direction.

3. The reservoir attribute inversion method according to claim 2, characterized in that: The fixed pile comprises a pile body (5), the outer wall of the pile body (5) is fixedly connected to the fixed plate (2), the top wall of the pile body (5) is provided with a threaded hole, a fixing bolt (6) is threadedly matched in the threaded hole, and a spiral tip (11) is fixedly connected to the bottom end of the fixing bolt (6).

4. The reservoir attribute inversion method according to claim 3, characterized in that: An arc-shaped plate (4) is fixedly connected to the outer periphery of the fixing plate (2) where the fixing pile is not connected. The arc-shaped plate (4) extends toward the ground. A plurality of fixing cones (3) are fixedly connected to the bottom wall of the fixing plate (2).

5. The reservoir attribute inversion method according to claim 2, characterized in that: The protective film (8) is provided with a plurality of through holes (7) for passing the cable of the detector (1). The detector (1) is provided with an acceleration sensor (10) for detecting the tilt acceleration of the detector (1). The tilt acceleration data is used to calculate the tilt angle of the detector, and the tilt angle is used to determine the availability of the detection data of the detector.

6. The reservoir attribute inversion method according to claim 1, characterized in that: The microseismic data screening process in step 2 refers to calculating the tilt of the geophone based on the data of the acceleration sensor, and screening out unusable geophone data according to the tilt angle of the geophone.

7. The reservoir attribute inversion method according to claim 1, characterized in that: The trained neural network model in step three refers to the neural network model that uses the spatial position of the extracted regional strata, seismic information and reservoir parameters as learning samples to input the neural network model output reservoir attribute inversion model for repeated learning until the accuracy reaches the required level.

8. A reservoir attribute inversion device, applicable to the reservoir attribute inversion method according to any one of claims 1 to 7, characterized in that: include: Data acquisition module, used to collect microseismic data, well logging data and geophone tilt acceleration data; The data processing module is used to process the collected data, calculate the detector inclination angle to screen the microseismic data, and the detector data with an inclination angle greater than 40° is judged as unusable. The screened microseismic data is denoised and the logging data is environmentally corrected; A neural network module is used to invert and calculate microseismic data, well logging data, drilling data and geological data according to parameter sample learning and obtain a reservoir inversion volume; The report module is used to visualize and display reports based on the calculated reservoir inversion volume and detector tilt angle.

9. An electronic device, characterized in that: include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, which, when executed by the processor, enable the electronic device to perform the reservoir property inversion method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the reservoir property inversion method according to any one of claims 1 to 7.

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