Dynamic and static combined CO2 migration monitoring and safety early warning method and device and storage medium

Abstract

The invention discloses a dynamic and static combined migration monitoring and safety early warning method and device and a storage medium, and relates to the technical field of oil and gas field development and engineering monitoring. The method comprises the following steps: constructing a static geological model based on three-dimensional seismic exploration data and non-seismic geophysical data, and performing multi-dimensional analysis on the static geological model to obtain geological risk factors; based on the vertical seismic profile data and the microseismic data of the time-shifted well, constructing a dynamic geologic model, and performing multi-dimensional analysis on the dynamic geologic model to obtain dynamic parameters; the static geologic model and the dynamic geologic model are fused and subjected to joint inversion, and a migration path model is generated to predict the migration direction; and setting a comprehensive early warning threshold value, and triggering graded early warning when the dynamic parameters exceed the comprehensive early warning threshold value. According to the invention, accurate prediction of the migration path and active early warning of storage safety are realized.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development and engineering monitoring technology, specifically to a dynamic and static combined monitoring system. Methods, equipment and storage media for migration monitoring and safety early warning. Background Technology

[0002] Geological sequestration is a key means of mitigating the greenhouse effect, but its long-term safety depends heavily on the protection of the underground sequestration sites. Precise understanding of migration behavior. Existing monitoring technologies are usually applied independently, which has obvious limitations: First, the accuracy of static models is insufficient. Static models built solely based on 3D seismic data have limited accuracy under complex geological conditions and do not integrate non-seismic data (such as electromagnetic and gravity data), making it difficult to comprehensively characterize key geological structures such as fault systems. Second, dynamic monitoring is isolated. While time-lapse well seismic and microseismic monitoring can effectively capture dynamic information, they lack the constraints of high-precision static background models, resulting in strong interpretability and difficulty in accurately characterizing migration behavior. The first problem is the lack of early warning capabilities. Traditional methods lack a deep integration mechanism of dynamic and static data, making it impossible to establish a closed loop from monitoring to early warning, and making it difficult to proactively prevent and control geological risks such as natural faults.

[0003] In summary, existing time-shifted seismic or well-drilled seismic methods also have certain technical shortcomings. The main problem is that single methods have limitations, static seismic data cannot reflect temporal changes, and dynamic monitoring lacks the support of static background models, resulting in strong ambiguity in interpretation. Furthermore, the simple superposition of multiple methods does not achieve deep fusion. Summary of the Invention

[0004] This invention addresses existing To address the issues of multiple interpretations and the lack of deep fusion in the simple superposition of multiple methods in motion monitoring technology, a combined dynamic and static approach is proposed. Migration monitoring and safety early warning methods, equipment, storage media, and program products have enabled the monitoring of... Accurate prediction of transport paths and proactive early warning of storage security.

[0005] The present invention is achieved through the following technical solution.

[0006] Firstly, the present invention provides a combination of dynamic and static elements. A migration monitoring and safety early warning method, the method comprising:

[0007] A static geological model is constructed based on three-dimensional seismic exploration data and non-seismic geophysical data. Geological risk factors are obtained by performing multi-dimensional analysis on the static geological model.

[0008] A dynamic geological model is constructed based on time-lapse well vertical seismic profile data and microseismic data. Dynamic parameters are obtained through multi-dimensional analysis of the dynamic geological model, and these dynamic parameters include: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Based on spatial distribution characteristics of microseismic events;

[0009] The static geological model and the dynamic geological model are fused and jointly inverted to generate... Migration path model for prediction Direction of movement;

[0010] Set a comprehensive early warning threshold, and base the dynamic geological model on the aforementioned threshold. When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

[0011] In some embodiments, before constructing a static geological model based on three-dimensional seismic exploration data and non-seismic geophysical data, the method further includes:

[0012] Coherence attributes are extracted from the 3D seismic data, and the data that meets the coherence attribute requirements are used as the 3D seismic exploration data.

[0013] Using geophysical methods, spatial geological feature data are extracted from raw non-seismic geophysical data and used as the non-seismic geophysical data.

[0014] In some embodiments, dynamic parameters are obtained by performing multi-dimensional analysis on the dynamic geological model, including:

[0015] Using the dynamic geological model, based on the time-lapse well vertical seismic profile data, the following can be obtained: Based on spatial distribution characteristics of seismic data in time-lapse wells;

[0016] Using the dynamic geological model, based on the microseismic monitoring data, the following can be obtained: Spatial distribution characteristics of microseismic events.

[0017] In some embodiments, the static geological model and the dynamic geological model are fused and jointly inverted to generate... Migration path model for prediction The direction of movement includes:

[0018] The data obtained through the dynamic geological model Based on the spatial distribution characteristics parameters of earthquakes in time-lapse wells, the aforementioned The spatial distribution characteristics of microseismic events are integrated into the static geological model;

[0019] Using the time-lapse well vertical seismic profile data as constraints, the static geological model is inverted to generate... transport path model;

[0020] Based on the above Migration path model, prediction The dominant channel and leading edge position of transport.

[0021] In some embodiments, a comprehensive early warning threshold is set, and the dynamic geological model is based on the... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered, including:

[0022] Based on the dynamic prediction results of the geological risk factors and the dynamic parameters, the comprehensive early warning threshold is set.

[0023] The dynamic geological model is based on the If the value of the dynamic parameter obtained from the migration path model is greater than the comprehensive early warning threshold, a graded early warning is triggered and monitoring data is output.

[0024] In some embodiments, the method further includes: feeding the monitoring data back to the static geological model to dynamically update the static geological model.

[0025] Secondly, the present invention provides a combination of dynamic and static elements. Migration monitoring and safety early warning equipment, the equipment comprising:

[0026] The static geological model construction module is used to: construct a static geological model based on three-dimensional seismic exploration data and non-seismic geophysical data, wherein geological risk factors are obtained through multi-dimensional analysis of the static geological model;

[0027] A dynamic geological model construction module is used to: construct a dynamic geological model based on time-lapse well vertical seismic profile data and microseismic data, wherein dynamic parameters are obtained through multi-dimensional analysis of the dynamic geological model, and the dynamic parameters include: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Based on spatial distribution characteristics of microseismic events;

[0028] The migration path model construction module is used to: fuse the static geological model and the dynamic geological model and perform joint inversion to generate... Migration path model for prediction Direction of movement;

[0029] The tiered early warning module is used to: set a comprehensive early warning threshold, and, based on the dynamic geological model,... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

[0030] Thirdly, the present invention provides a combination of dynamic and static elements. Migration monitoring and safety early warning equipment, the equipment comprising:

[0031] At least one processor;

[0032] At least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions implementing the method described in any of the above when executed by the at least one processor.

[0033] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform the method described in any of the preceding embodiments.

[0034] Fifthly, the present invention provides a computer program product comprising instructions that, when executed by a computer, cause the computer to perform any of the methods described above.

[0035] Compared with existing technologies, this invention has the following advantages and beneficial effects: it provides a deep fusion of static background and dynamic response. The migration monitoring and safety early warning scheme establishes a mechanism for cross-verification and collaborative inversion of multi-source data to achieve [monitoring / monitoring / safety early warning]. Accurate prediction of transport paths and proactive early warning of storage security. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A dynamic and static combination according to an embodiment of the present invention Flowchart of migration monitoring and safety early warning methods.

[0038] Figure 2 For the dynamic and static combination according to embodiments of the present invention Migration monitoring and safety early warning process.

[0039] Figure 3 The diagram illustrates the steps according to an embodiment of the present invention.

[0040] Figure 4 A dynamic and static combination according to an embodiment of the present invention Structural block diagram of migration monitoring and safety early warning equipment.

[0041] Figure 5 A dynamic and static combination according to an embodiment of the present invention A schematic diagram of the structure of the migration monitoring and safety early warning equipment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0043] On the one hand, the present invention provides a combination of dynamic and static... Migration monitoring and safety early warning methods. Figure 1 A dynamic and static combination according to an embodiment of the present invention Flowchart of migration monitoring and safety early warning methods. (Reference) Figure 1 The combination of dynamic and static Migration monitoring and safety early warning methods include: S10 to S40.

[0044] Figure 2 For the dynamic and static combination according to embodiments of the present invention Migration monitoring and safety early warning process. Figure 3 The following is a schematic diagram of the steps according to an embodiment of the present invention. Figures 1 to 3 S10 to S40 of the method of the present invention will be described in detail.

[0045] In S10, a static geological model is constructed based on three-dimensional seismic exploration data and non-seismic geophysical data. Geological risk factors can be obtained by conducting multi-dimensional analysis of the static geological model.

[0046] For example, before constructing a static geological model based on 3D seismic exploration data and non-seismic geophysical data, the method further includes: acquiring 3D seismic exploration data (seismic background attribute extraction) and non-seismic geophysical data (non-seismic background attribute extraction).

[0047] Specifically, firstly, coherence attributes are extracted from the 3D seismic data, and data that meets the coherence attribute requirements are used as 3D seismic exploration data (i.e., static seismic background data). See [link to relevant documentation]. Figure 3Figure (a) shows the static seismic attribute map; then, using geophysical methods, spatial geological feature data are extracted from the raw non-seismic geophysical data as non-seismic geophysical data (i.e., static non-seismic background data). See [reference needed]. Figure 3 Figure (b) shows the static non-seismic attribute map. After acquiring 3D seismic exploration data and non-seismic geophysical data, a high-precision 3D static geological model incorporating elements such as stratigraphic structure, reservoir distribution, and fault systems can be constructed by comprehensively utilizing these data. The inclusion of non-seismic data makes the static geological model more comprehensive and complete. This static geological model provides a spatial framework and geological constraints for dynamic monitoring data.

[0048] In S20, a dynamic geological model is constructed based on time-lapse well vertical seismic profile data and microseismic data. Dynamic parameters are obtained through multi-dimensional analysis of the dynamic geological model, including: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Spatial distribution characteristics of microseismic events.

[0049] For example, using a dynamic geological model, based on time-lapse well vertical seismic profile (VSP) data, to obtain... Based on the spatial distribution characteristics of seismic activity in time-lapse wells; using a dynamic geological model and microseismic monitoring data, [the following parameters are obtained]. Spatial distribution characteristics of microseismic events.

[0050] Specifically, for vertical seismic profile data in time-lapse wells, receiving instruments can be deployed in the injection well or monitoring well, and excitation instruments can be deployed on the surface or in adjacent wells to determine... Before and during injection, seismic data acquisition in the well was repeated at multiple time points. See [link / reference]. Figure 3 Figure (d) shows the seismic description in a dynamic time-lapse well. Quantization was achieved through differential processing and acoustic impedance inversion techniques. Wave impedance changes caused by transport, inversion The spatiotemporal evolution characteristics of saturation, etc., are used to obtain... Spatial distribution characteristics of earthquakes in time-lapse wells. The spatial distribution characteristics of seismic activity in time-lapse wells include: Saturation (typically exceeding 20%), vertical distribution thickness (typically ranging from several meters to tens of meters), etc. For receiving instruments, highly sensitive and consistent electronic detectors or distributed fiber optic instruments can be selected. For excitation instruments, highly repeatable and consistent controlled ground or well-drilled artificial sources can be selected. Differential processing and wave impedance inversion techniques can be implemented using existing seismic data processing software.

[0051] For microseismic data, microseismic monitoring arrays can be deployed in wells or on the surface to capture... See the microseismic signals induced during the injection process. Figure 3 Figure (c) illustrates the dynamic microseismic description. High-precision positioning techniques were used to determine the spatial distribution of microseismic events, analyze stress field changes, and assess caprock integrity and fault activation risk. The spatial distribution characteristics of microseismic events include: plane wave range, leading edge location (usually ranging from a few meters to several hundred meters), etc.

[0052] By fusing the vertical seismic profile data and microseismic data from the aforementioned time-lapse wells, a dynamic distribution result can be obtained, which better reflects the situation before and after injection. For dynamic changes, see Figure 3 In (f), the dynamic microseismic description and dynamic time-shifted well seismic fusion are shown.

[0053] In S30, the static geological model and the dynamic geological model are merged and jointly inverted to generate... Migration path model for prediction Direction of movement.

[0054] For example, the static geological model is fused with the dynamic geological model (see...). Figure 3 (e) shows the static seismic attributes and static non-seismic attributes fused together and jointly inverted to generate... Migration path model for prediction The direction of migration includes: firstly, the direction obtained through dynamic geological models. Based on the spatial distribution characteristics of earthquakes in time-lapse wells, The spatial distribution characteristics of microseismic events are integrated into a static geological model; then, using time-lapse well vertical seismic profile data as constraints, the static geological model is inverted to generate... Transport path model; finally, based on Migration path model, prediction The dominant channel and leading edge position of transport.

[0055] Specifically, the seismic inversion obtained from time-lapse wells can be... Dynamic information such as saturation changes and stress field changes revealed by microseismic events ( Spatial distribution characteristic parameters and related information are integrated into the static geological model. Accurate data is generated through joint inversion (e.g., using raw well seismic data as constraints to optimize the static geological model). Transport path model. Then, based on the fusion model, identification. The dominant transport pathway and leading edge location (for predicting transport direction) are shown in [reference needed]. Figure 3(g) shows the combination of dynamic and static elements. Migration monitoring map. For example, when microseismic events cluster near faults identified by static geological models, and seismic data from time-lapse wells show continuous changes in wave impedance in the area, the fault can be identified as a potential dominant migration pathway.

[0056] In S40, a comprehensive early warning threshold is set, and based on the dynamic geological model... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

[0057] For example, a comprehensive early warning threshold is set, and a dynamic geological model is based on... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered, including: first, setting a comprehensive early warning threshold based on the dynamic prediction results of geological risk factors and dynamic parameters; then, based on the dynamic geological model... If the value of the dynamic parameter obtained from the migration path model exceeds the comprehensive early warning threshold, a tiered early warning is triggered, and monitoring data is output.

[0058] Specifically, this involves combining geological risk factors from static geological models (such as the degree of development of natural faults and the thickness of caprock) with dynamic prediction results from dynamic geological models (such as...). (Movement speed, pressure changes), and set a comprehensive early warning threshold. For example, use 20m as the distance threshold, such as... Figure 3 As shown in (h), the arrow position When the distance between the migration range and the natural crack reaches a threshold distance, a risk warning is issued.

[0059] When dynamic parameters exceed the threshold, the system triggers a tiered early warning (e.g., low, medium, high risk) and outputs a risk spatial distribution map. For high-risk areas, it may be recommended to adjust injection parameters (e.g., injection pressure, rate) or deploy emergency monitoring wells.

[0060] In some embodiments, for example, the monitoring data after the early warning is fed back to the static geological model. Specifically, the early warning data is compared with the monitoring data, their differences are analyzed, and the static background model is fine-tuned to make it closer to the actual stratigraphic characteristics, so as to realize the dynamic updating of the geological model and form a closed-loop optimization.

[0061] This invention provides a method for achieving deep integration of static background and dynamic response. The migration monitoring and safety early warning scheme establishes a mechanism for cross-verification and collaborative inversion of multi-source data to achieve [monitoring / monitoring / safety early warning]. Accurate prediction of migration paths and proactive early warning of storage safety are crucial for the development of remaining oil and gas resources and dynamic monitoring of gas storage facilities.

[0062] On the other hand, the present invention provides a combination of dynamic and static methods. Migration monitoring and safety early warning equipment. Figure 4 A dynamic and static combination according to an embodiment of the present invention Structural block diagram of transport monitoring and safety early warning equipment. (Reference) Figure 4 The combination of dynamic and static The migration monitoring and safety early warning equipment includes: a static geological model construction module, a dynamic geological model construction module, The module includes a migration path model construction module and a hierarchical early warning module.

[0063] The static geological model construction module is used to construct static geological models based on 3D seismic exploration data and non-seismic geophysical data. Geological risk factors are obtained through multi-dimensional analysis of the static geological models.

[0064] The dynamic geological model construction module is used to construct a dynamic geological model based on time-lapse well vertical seismic profile data and microseismic data. The dynamic geological model is analyzed in multiple dimensions to obtain dynamic parameters, including: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Spatial distribution characteristics of microseismic events.

[0065] The migration path model construction module is used to: fuse static and dynamic geological models and perform joint inversion to generate... Migration path model for prediction Direction of movement.

[0066] The tiered early warning module is used to: set comprehensive early warning thresholds and, based on the dynamic geological model... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

[0067] The combination of dynamic and static For other details regarding migration monitoring and safety early warning equipment, please refer to the previous section on the combination of dynamic and static monitoring. The relevant descriptions of migration monitoring and safety early warning methods will not be repeated here.

[0068] When implementing the functions of the integrated modules described above in hardware, this embodiment of the invention provides the dynamic and static combination involved in the above embodiments. A structure for transport monitoring and safety early warning equipment. Figure 5 A dynamic and static combination according to an embodiment of the present invention Schematic diagram of the movement monitoring and safety early warning equipment. (Reference) Figure 5 The combination of dynamic and static The migration monitoring and security early warning device includes: at least one processor; and at least one memory. The at least one memory is coupled to the at least one processor and stores instructions for execution by the at least one processor, which, when executed by the at least one processor, implement the method described above.

[0069] A processor can be a set of logic blocks, modules, and circuits that implement or execute the various exemplary logic blocks, modules, and circuits described in connection with embodiments of the present invention. The processor can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in connection with embodiments of the present invention. A processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, etc.

[0070] The memory may be read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0071] In one implementation, the memory can exist independently of the processor. The memory can be connected to the processor via a bus and used to store instructions or program code. When the processor calls and executes the instructions or program code stored in the memory, it can implement the methods provided in the embodiments of the present invention. In another implementation, the memory can also be integrated with the processor.

[0072] On the other hand, the present invention also provides a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing computer program instructions that, when executed on a computer, cause the computer to perform the method as described in any of the above embodiments.

[0073] Exemplary examples show that the aforementioned computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical discs (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in this invention may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0074] This invention provides a computer program that, when run on a computer, causes the computer to perform the method of any of the above embodiments.

[0075] This invention provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the method of any of the above embodiments.

[0076] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A combination of dynamic and static methods The migration monitoring and safety early warning method is characterized by, The method includes: A static geological model is constructed based on three-dimensional seismic exploration data and non-seismic geophysical data. Geological risk factors are obtained by performing multi-dimensional analysis on the static geological model. A dynamic geological model is constructed based on time-lapse well vertical seismic profile data and microseismic data. Dynamic parameters are obtained through multi-dimensional analysis of the dynamic geological model, and these dynamic parameters include: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Based on spatial distribution characteristics of microseismic events; The static geological model and the dynamic geological model are fused and jointly inverted to generate... Migration path model for prediction Direction of movement; Set a comprehensive early warning threshold, and base the dynamic geological model on the aforementioned threshold. When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

2. The method according to claim 1, characterized in that, Before constructing a static geological model based on 3D seismic exploration data and non-seismic geophysical data, the method further includes: Coherence attributes are extracted from the 3D seismic data, and the data that meets the coherence attribute requirements are used as the 3D seismic exploration data. Using geophysical methods, spatial geological feature data are extracted from raw non-seismic geophysical data and used as the non-seismic geophysical data.

3. The method according to claim 1, characterized in that, Dynamic parameters were obtained by performing multi-dimensional analysis on the dynamic geological model, including: Using the dynamic geological model, based on the time-lapse well vertical seismic profile data, the following can be obtained: Based on spatial distribution characteristics of seismic data in time-lapse wells; Using the dynamic geological model, based on the microseismic monitoring data, the following can be obtained: Spatial distribution characteristics of microseismic events.

4. The method according to any one of claims 1 to 3, characterized in that, The static geological model and the dynamic geological model are fused and jointly inverted to generate... Migration path model for prediction The direction of movement includes: The data obtained through the dynamic geological model Based on the spatial distribution characteristics parameters of earthquakes in time-lapse wells, the aforementioned The spatial distribution characteristics of microseismic events are integrated into the static geological model; Using the time-lapse well vertical seismic profile data as constraints, the static geological model is inverted to generate... transport path model; Based on the above Migration path model, prediction The dominant channel and leading edge position of transport.

5. The method according to claim 1, characterized in that, Set a comprehensive early warning threshold, and base the dynamic geological model on the aforementioned threshold. When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered, including: Based on the dynamic prediction results of the geological risk factors and the dynamic parameters, the comprehensive early warning threshold is set. The dynamic geological model is based on the If the value of the dynamic parameter obtained from the migration path model is greater than the comprehensive early warning threshold, a graded early warning is triggered and monitoring data is output.

6. The method according to claim 5, characterized in that, The method further includes: feeding the monitoring data back to the static geological model to dynamically update the static geological model.

7. A combination of dynamic and static methods The migration monitoring and safety early warning equipment is characterized in that, The device includes: The static geological model construction module is used to: construct a static geological model based on three-dimensional seismic exploration data and non-seismic geophysical data, wherein geological risk factors are obtained through multi-dimensional analysis of the static geological model; A dynamic geological model construction module is used to: construct a dynamic geological model based on time-lapse well vertical seismic profile data and microseismic data, wherein dynamic parameters are obtained through multi-dimensional analysis of the dynamic geological model, and the dynamic parameters include: Based on the spatial distribution characteristics of earthquakes in time-lapse wells, Based on spatial distribution characteristics of microseismic events; The migration path model construction module is used to: fuse the static geological model and the dynamic geological model and perform joint inversion to generate... Migration path model for prediction Direction of movement; The tiered early warning module is used to: set a comprehensive early warning threshold, and, based on the dynamic geological model,... When the dynamic parameters obtained from the migration path model exceed the comprehensive early warning threshold, a tiered early warning is triggered.

8. A combination of dynamic and static The migration monitoring and safety early warning equipment is characterized in that, The device includes: At least one processor; At least one memory coupled to the at least one processor and storing instructions for execution by the at least one processor, the instructions implementing the method of any one of claims 1 to 6 when executed by the at least one processor.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.

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