Safety risk control method for geological storage of carbon dioxide and electronic equipment

Abstract

The invention provides a safety risk control method for geological storage of carbon dioxide and electronic equipment. A distributed optical fiber sensing system is arranged in at least one injection well of the target sealing and storage area in the axial direction of a shaft and penetrates through a main cover layer and a reservoir; the method comprises the following steps: acquiring background data through a distributed optical fiber sensing system, and establishing a multi-parameter baseline model including a temperature field, a strain field and background noise; temperature, strain and sound wave vibration signals are collected in real time, and key features are extracted; the key features extracted in real time are compared with a preset risk feature library, the types of risk events are identified, and the identified risk events are graded according to the spatial range and intensity of the abnormal signals; and according to the type and the grade of the risk event, generating and executing a corresponding control instruction. According to the embodiment of the invention, the optical fibers are distributed in the whole area along the shaft and the target stratum, a three-dimensional monitoring network covering the sealing body is constructed, and the hysteresis quality of traditional point type measurement and periodic exploration is overcome.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular, relates to a safety risk control method for carbon dioxide geological storage and an electronic device. BACKGROUND

[0002] In carbon dioxide geological storage (CCS) projects, ensuring that the injected carbon dioxide is stored in the underground reservoir for a long time and safely is one of the core technical challenges. Carbon dioxide may leak through undiscovered faults, fractures, or poor cementing quality wellbores, not only leading to a decrease in storage efficiency, but also moving up to shallow groundwater or the surface, causing environmental and safety risks. Therefore, real-time and accurate monitoring of the storage area is crucial.

[0003] Traditional monitoring techniques mainly rely on wellbore pressure monitoring, surface deformation measurement (InSAR), and periodic cross-well seismic exploration. These methods have obvious limitations: pressure monitoring can only reflect local information near the wellbore; surface deformation measurement has low spatial resolution and a lagging response; and seismic exploration is costly and cannot achieve continuous real-time monitoring, making it difficult to capture sudden and local leakage events. SUMMARY

[0004] The purpose of the embodiments of the present application is to provide a safety risk control method for carbon dioxide geological storage and an electronic device to solve the above technical problems.

[0005] In a first aspect, the present application provides a safety risk control method for carbon dioxide geological storage, the method comprising the following steps: In at least one injection well in the target storage area, a distributed optical fiber sensing system is arranged along the wellbore axis and through the main caprock and reservoir, which can synchronously collect temperature, strain, and acoustic vibration signals; Before carbon dioxide injection begins, background data is collected by the distributed optical fiber sensing system to establish a multi-parameter baseline model including temperature field, strain field, and background noise; During carbon dioxide injection, the temperature, strain, and acoustic vibration signals are collected in real time, and key features are extracted, including spatial gradient mutation points, time series abnormal fluctuations, and coupling relationships of multi-physical field signals; The real-time extracted key features are compared with a preset risk feature library to identify the type of risk event, and the identified risk event is classified according to the spatial range and intensity of the abnormal signal; According to the type and level of the risk event, corresponding control instructions are generated and executed, including adjusting carbon dioxide injection parameters, starting downhole safety valves, or issuing warning information.

[0006] In an optional embodiment, the coupling relationship of the extracted multi-physical field signals specifically comprises: analyzing the coincidence degree of the temperature anomaly drop area and the tensile strain anomaly increase area in space and time, and when the coincidence degree exceeds a first threshold, determining as a potential carbon dioxide leakage signal.

[0007] In an optional embodiment, the risk event type at least includes one of carbon dioxide channeling along a fracture or a fault, caprock integrity damage, and wellbore sealing failure, wherein the caprock integrity damage is identified according to that a sustained upward tensile strain anomaly zone is monitored at the caprock bottom interface.

[0008] In an optional embodiment, the risk level classification at least includes three levels of low, medium and high, and the classification is based on the spatial continuity, change rate of the abnormal signal and whether it appears in multiple physical field signals at the same time.

[0009] In an optional embodiment, when the identified risk event is “carbon dioxide channeling along a fracture” and the risk level is “high”, the generated control instruction is to automatically trigger the downhole safety valve to close and at the same time reduce the surface injection pressure to below a safety threshold.

[0010] In an optional embodiment, the method further comprises: periodically comparing the current monitoring data with a historical baseline model, and evaluating the long-term sealing stability of the seal by analyzing the long-term trend of the caprock strain and the reservoir temperature.

[0011] In an optional embodiment, the collected acoustic vibration signals are analyzed to identify and locate acoustic events of specific frequencies generated by carbon dioxide flow or micro-fracturing of the formation.

[0012] In an optional embodiment, the generated control instruction and related risk event information are displayed in real time on a visual decision interface, which simultaneously integrates downhole fiber monitoring data and surface injection parameters.

[0013] In an optional embodiment, the pre-set risk feature library is pre-established by numerical simulation, indoor physical simulation experiment or by referring to historical monitoring data of the same geological region.

[0014] In a second aspect, the present application provides an electronic device comprising a processor and a memory, wherein the memory stores machine executable instructions capable of being executed by the processor, and the processor can execute the machine executable instructions to implement the method of any one of the preceding embodiments.

[0015] Embodiments of the present application overcome the hysteresis of traditional point measurement and periodic exploration by laying optical fibers along the whole wellbore and target formation to build a three-dimensional monitoring network covering the seal.

[0016] By fusing temperature, strain, acoustic wave and other multi-parameter information, and performing correlation coupling analysis, different risk types such as carbon dioxide leakage and formation shear slip can be effectively filtered out and accurately identified, and a leap from “abnormal alarm” to “risk qualification” can be realized.

[0017] By linking the monitored risk signals with injection parameters (pressure, displacement) in real time, injection strategies can be automatically or assistedly adjusted by the operator to actively control risks and suppress the leakage in the embryonic state.

[0018] By establishing a historical data baseline and comparing it with real-time data, the change of caprock integrity and the long-term stability of the carbon dioxide plume can be evaluated, and data support can be provided for the long-term safety evaluation of the storage project.

[0019] The method can be implemented synchronously with drilling and completion engineering (such as installing optical fibers outside the casing), without occupying additional operation cycles, and through modular risk level determination, it is convenient for field personnel to understand and execute the corresponding emergency procedures. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0021] Figure 1 A flowchart of a carbon dioxide migration state recognition method based on optical fiber monitoring data provided by the embodiments of the present application is shown in the figure. Figure 2 A structural diagram of a carbon dioxide migration state recognition device based on optical fiber monitoring data provided by the embodiments of the present application is shown in the figure. Figure 3 An electronic device structure diagram provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described below in combination with the drawings in the embodiments of the present application.

[0023] Figure 1 A flowchart of a safety risk control method for carbon dioxide geological storage provided by the embodiments of the present application is shown in the figure. Figure 1 As shown in the figure, the method comprises the following steps: S110, in at least one injection well in the target storage area, a distributed optical fiber sensing system is arranged along the wellbore axis and through the main caprock and reservoir, and the system can synchronously collect temperature, strain and acoustic wave vibration signals.

[0024] Distributed optical fiber sensing system uses optical fiber as sensing medium, and realizes distributed measurement of temperature, strain and acoustic vibration signals by using light scattering effect (Brillouin scattering for strain measurement, Raman scattering for temperature measurement, Rayleigh scattering for vibration measurement). It has high spatial resolution (0.1-1m) and long distance monitoring capability.

[0025] The low-permeability rock layer (such as shale, salt rock) above the main cap rock reservoir is the key sealing barrier to prevent carbon dioxide from escaping upward; the porous rock layer (such as sandstone) with porosity and permeability is used to store carbon dioxide.

[0026] It can extend axially from the wellhead to the bottom of the reservoir, ensuring that the optical fiber passes through the main cap rock (covering the top to bottom interface of the cap rock) and the reservoir (covering the full thickness of the reservoir).

[0027] It can also be installed by mechanical fixation on the inner wall of the casing or by embedding in the cement sheath, ensuring that the optical fiber is tightly coupled with the formation medium and reducing measurement errors.

[0028] S120, before the start of carbon dioxide injection, collect background data by the distributed optical fiber sensing system, and establish a multi-parameter baseline model including temperature field, strain field and background noise; The background data is the original monitoring data before carbon dioxide injection, reflecting the natural state of the formation; the multi-parameter baseline model is the temperature, strain and acoustic signal reference established based on the background data, which is used for subsequent anomaly comparison.

[0029] The temperature field is the distribution of temperature at each point in space (T(z), z is the depth of the wellbore); the strain field is the distribution of strain at each point in the formation (ε(z)); and the background noise is the acoustic signal background without injection.

[0030] Background data collection and preprocessing can be realized by the following steps: Collect 7 days of data before injection: temperature T0(z,t), strain ε0(z,t), and acoustic wave A0(t) (z is the depth, t is the time).

[0031] Wavelet threshold denoising (acoustic signal), 3σ criterion to remove outliers (remove data points deviating from the mean by 3 times the standard deviation), and Kriging interpolation (convert discrete sampling points to continuous field distribution).

[0032] Temperature field baseline model construction: ; : time average of temperature at depth z, (N is the number of samples); : temperature standard deviation, representing the natural fluctuation range.

[0033] Strain field baseline model construction: ; (strain time mean); : strain standard deviation.

[0034] Background noise baseline model construction: (power spectral density of acoustic signal, f is frequency).

[0035] S130, during the carbon dioxide injection process, real-time acquisition of temperature, strain and acoustic vibration signals, and extraction of key features, the key features including spatial gradient mutation point, time series abnormal fluctuation and coupling relationship of multi-physical field signals; In some embodiments, the extraction of the coupling relationship of the multi-physical field signals specifically includes: analyzing the coincidence degree of the temperature abnormal decline area and the tensile strain abnormal increase area in space and time, and when the coincidence degree exceeds a first threshold, determining as a potential carbon dioxide leakage signal.

[0036] The spatial gradient mutation point is the position where the spatial distribution gradient of the physical quantity (temperature / strain) suddenly changes significantly, reflecting the mutation of medium properties (such as crack interface); the time series abnormal fluctuation is the significant fluctuation of the monitoring value deviating from the baseline trend with time; the multi-physical field coupling relationship is the correlation of temperature, strain and acoustic field signals (such as the synchronism of temperature drop and strain increase).

[0037] Among them, the real-time temperature T(z, t), strain ε(z, t), acoustic wave A(z, t) is continuously collected according to S110 during the injection process.

[0038] Spatial gradient mutation point: calculate temperature gradient (Δz is the spatial sampling interval, such as 0.5m), when ( , is the baseline temperature gradient standard deviation) is determined as the mutation point; the strain gradient mutation point is the same.

[0039] Time series abnormal fluctuation: calculate the deviation of real-time value and baseline , when (3σ criterion) is determined as abnormal fluctuation; the strain abnormal fluctuation is the same.

[0040] Multi-physical field coupling relationship (take carbon dioxide leakage as an example): identify temperature abnormal area (temperature is lower than baseline 3σ); identify tensile strain abnormal area (tensile strain is higher than baseline 3σ); calculate spatial coincidence degree ( is and overlapping length, Total abnormal length) ; calculate time coincidence Length of time when both are abnormal, When C > 0.7 (first threshold), determine as potential leakage signal.

[0041] Short-time Fourier transform (STFT) is performed on the acoustic signal A (z, t) to obtain the time-frequency diagram A (z, t, f), and the characteristic frequency band energy is calculated (Carbon dioxide flow: 0.1-10Hz; formation microfracture: 1-20kHz), when (Baseline noise energy 5 times), identify as specific frequency event.

[0042] S140, compare the real-time extracted key features with the preset risk feature library, identify the risk event type, and classify the identified risk event according to the spatial range and intensity of the abnormal signal; In some embodiments, the risk event type at least includes one of carbon dioxide channeling along the fracture or fault, caprock integrity damage, and wellbore sealing failure, wherein the caprock integrity damage is identified according to the monitoring of a continuous, upward tensile strain abnormal zone at the bottom interface of the caprock.

[0043] In some embodiments, the risk level classification at least includes three levels of low, medium and high, and the classification is based on the spatial continuity, change rate of the abnormal signal and whether it appears in multiple physical field signals at the same time.

[0044] In some embodiments, the preset risk feature library is pre-established by numerical simulation, indoor physical simulation experiment or by referring to the historical monitoring data of the same geological area of the sealed well.

[0045] Risk feature library is a preset risk event typical feature database (such as signal mode of caprock damage and wellbore failure) ; caprock integrity damage: cracks in caprock due to stress change, showing a continuous upward tensile strain abnormal zone at the bottom interface of the caprock; risk level: low / medium / high level classified by severity (according to spatial continuity, change rate of abnormal signal, and multiple physical field synergy).

[0046] In some embodiments, the typical risk features can be extracted by numerical simulation (such as TOUGH2-MP simulation of carbon dioxide migration), indoor physical simulation (autoclave simulation of caprock fracture), and historical data, for example: Carbon dioxide channeling along the fracture: characteristic vector = (vertical continuous spatial gradient mutation point, C > 0.7, low-frequency acoustic energy anomaly) ; ​​Cap integrity compromised: feature vector = (anomalous band of tensile strain at the bottom of the cap consistently upwards, rate of change of strain ).

[0047] Risk identification (feature comparison): calculate the cosine similarity between the real-time feature vector (including spatial gradient distribution, C, acoustic energy, etc.) and the vectors in the risk feature library : , take the maximum corresponding risk type as the identification result.

[0048] Risk level classification: input parameters: spatial continuity (abnormal area continuous length / total monitoring length, 0-1), rate of change (με / h), multi-physical field synergy M (number of physical fields with anomalies at the same time, 1-3); level score: ; decision: R<0.3→low risk; → medium risk; → high risk.

[0049] S150, according to the type and level of the risk event, generate and execute corresponding control instructions, including adjusting carbon dioxide injection parameters, starting downhole safety valve or issuing warning information.

[0050] In some embodiments, when the identified risk event is "carbon dioxide channeling along the fracture" and the risk level is "high", the generated control instruction is to automatically trigger the downhole safety valve to close, and at the same time reduce the surface injection pressure to below the safety threshold.

[0051] In some embodiments, the method further comprises: periodically comparing the current monitoring data with the historical baseline model, and evaluating the long-term sealing stability of the seal by analyzing the long-term trend of cap strain and reservoir temperature.

[0052] In some embodiments, the collected acoustic vibration signals are analyzed to identify and locate acoustic events of specific frequencies generated by carbon dioxide flow or micro-fracture of the formation.

[0053] In some embodiments, the generated control instructions and related risk event information are displayed in real time on a visual decision interface, which simultaneously integrates downhole fiber monitoring data and surface injection parameters.

[0054] Control instructions are countermeasures generated based on risk type and level (such as adjusting injection parameters, closing safety valve); downhole safety valve: an emergency shut-off device installed in the wellbore to prevent carbon dioxide channeling; visual decision interface: a real-time display platform integrating monitoring data and control instructions.

[0055] Control instruction generation rule: high risk + CO2 migration along the fracture: automatically trigger the downhole safety valve to close (solenoid action signal), and generate injection pressure adjustment instruction at the same time: The original reservoir pressure is the safety threshold, and the real-time pressure is adjusted by the PID controller to make the real-time pressure ; Medium risk + caprock damage: generate injection rate adjustment instruction: (reduce the rate to reduce the formation pressure); Low risk: generate warning information (text + sound and light alarm).

[0056] Instruction execution and feedback: issue instructions to wellhead equipment through the SCADA system, and monitor the execution effect (such as whether the pressure reaches the target) in real time; if the abnormality is not alleviated within 10 minutes, automatically upgrade the instruction (such as low risk → medium risk measures).

[0057] Visual decision interface: integrate downhole optical fiber data (temperature / strain spatial distribution map, acoustic time-frequency map) and surface parameters (pressure, rate), display risk type, level, instruction status and abnormal position mark in real time, support historical data trend analysis (such as caprock strain long-term curve ).

[0058] In addition, periodically (such as every quarter) compare the current monitoring data with the historical baseline model, and evaluate the sealing stability through the long-term trend of the caprock strain and the reservoir temperature trend If and , the seal is stable.

[0059] Based on the same inventive concept, the embodiments of the present application also provide a safety risk control device for carbon dioxide geological storage. In at least one injection well in the target storage area, a distributed optical fiber sensing system is arranged along the wellbore axis and through the main caprock and reservoir. The system can synchronously collect temperature, strain and acoustic vibration signals; as shown in Figure 2 , the device comprises: The acquisition module 201 is used to collect background data through the distributed optical fiber sensing system before the start of carbon dioxide injection, and establish a multi-parameter baseline model including temperature field, strain field and background noise; The extraction module 202 is used to collect temperature, strain and acoustic vibration signals in real time during the carbon dioxide injection process, and extract key features, including spatial gradient mutation point, time series abnormal fluctuation and coupling relationship of multi-physical field signals; ​The identification module 203 is configured to compare the real-time extracted key features with the preset risk feature library, identify a risk event type, and grade the identified risk event according to a spatial range and intensity of the abnormal signal. The generation module 204 is configured to generate and execute a corresponding control instruction according to the type and grade of the risk event, the control instruction including adjusting a carbon dioxide injection parameter, starting a downhole safety valve, or issuing a warning information.

[0060] The device embodiment corresponds to the foregoing method embodiment, and can be understood with reference to each other.

[0061] Referring to Figure 3 The electronic device 300 provided in the embodiments of the present application at least includes a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301, and the processor 301 implements the method provided in the embodiments of the present application when executing the computer program.

[0062] The electronic device 300 provided in the embodiments of the present application can further include a bus 303 connecting different components (including the processor 301 and the memory 302). The bus 303 represents one or more of several types of bus structures, including a memory bus, a peripheral bus, a local bus, and the like.

[0063] The memory 302 can include a readable storage medium in the form of a volatile memory, such as a random access memory (RAM) 3021 and / or a cache memory 3022, and can further include a read-only memory (ROM) 3023. The memory 302 can also include a program tool 3025 having a set of (at least one) program modules 3024, including but not limited to an operating system, one or more application programs, other program modules, and program data, each of these examples or some combination thereof can include the implementation of a network environment.

[0064] The processor 301 can be one processing element or a collective term for a plurality of processing elements. For example, the processor 301 can be a central processing unit (CPU), or one or more integrated circuits configured to implement methods provided by embodiments of the present application. Specifically, the processor 301 can be a general-purpose processor, including but not limited to a CPU, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component, and the like.

[0065] The electronic device 300 can communicate with one or more external devices 304 (such as a keyboard, a remote control, and the like) by means of the I / O interface 305. Also, the electronic device 300 can communicate with one or more devices that enable a user to interact with the electronic device 300 (such as a personal computer, a phone, and the like) and / or one or more devices that enable the electronic device 300 to communicate with one or more other electronic devices 300 (such as a router, a modem, and the like). Such communication can occur via the I / O interface 305. Also, the electronic device 300 can communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or the public network, such as the Internet) by means of the network adapter 306. As Figure 3 illustrated, the network adapter 306 communicates with the other components of the electronic device 300 via the bus 303. It should be understood that although not shown, other hardware and / or software components that are commonly used in computing can also be included in the electronic device 300, such as a microcode, a device driver, a redundant processor, an external disk drive array, a RAID subsystem, a tape drive, and a data backup storage subsystem, and the like. Figure 3 It should be understood that, although not shown in the

[0066] It should be understood that, Figure 3 The electronic device 300 as shown is merely an example, and should not impose any limitation on the functions and use range of embodiments of the present application.

[0067] The computer readable storage medium provided by the embodiments of the present application is introduced as follows. The computer readable storage medium provided by the embodiments of the present application stores computer instructions, and the computer instructions are executed by a processor to implement the method provided by the embodiments of the present application. Specifically, the computer instructions can be built-in or installed in the processor, so that the processor can implement the method provided by the embodiments of the present application by executing the built-in or installed computer instructions.

[0068] In addition, the method provided by the embodiments of the present application can also be implemented as a computer program product, which includes program codes and implements the method provided by the embodiments of the present application when the program codes are run on a processor.

[0069] The computer program product provided by the embodiments of the present application can adopt one or more computer readable storage media, and the computer readable storage media can be, but are not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any appropriate combination of the above. Specifically, more specific examples (non-exhaustive list) of the computer readable storage media include an electrical connection with one or more wires, a portable disc, a hard disk, a RAM, a ROM, an Erasable Programmable Read Only Memory (EPROM), an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination of the above.

[0070] The computer program product provided by the embodiments of the present application can adopt a CD-ROM and include program codes, and can also run on an electronic device such as a computer. However, the computer program product provided by the embodiments of the present application is not limited to this. In the embodiments of the present application, the computer readable storage medium can be any tangible medium containing or storing program codes, which can be used or combined with an instruction execution system, device or component.

[0071] It should be noted that although several units or sub-units of the apparatus are mentioned in the above detailed description, such division is only exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided into units embodied by multiple units.

[0072] Furthermore, although the operations of the method(s) herein can be described in a particular, sequential order, this order is not meant to be a limitation and one or more of the operations described can be performed in parallel, or in a different order, including before or after other operations described. The various steps described can be implemented in hardware, software, or a combination thereof. The subject specification can be implemented by computer software implemented by one or more processors of a computing device.

[0073] While the preferred embodiments of the application have been described above, it should be understood that they have been presented by way of example only, and not limitation. Numerous changes to the embodiments can be made in addition to those described and nevertheless accomplish the same objectives of the application. Thus, while the application is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in order to elucidate the application. It should be understood, therefore, that the application is not to be limited to the particular embodiments described but it is intended to cover any and all modifications and equivalents within the scope of the appended claims.

[0074] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the application can be practiced otherwise than as specifically described herein.

Claims

1. A method for safety risk control for geological storage of carbon dioxide, characterized by, The method comprises the following steps: deploying a distributed optical fiber sensing system along the wellbore axis and through the main caprock and reservoir in at least one injection well in the target storage area, the system being capable of synchronously collecting temperature, strain and acoustic vibration signals; collecting background data through the distributed optical fiber sensing system before the start of carbon dioxide injection, establishing a multi-parameter baseline model including temperature field, strain field and background noise; in the process of carbon dioxide injection, real-time collection of the temperature, strain and acoustic vibration signals, and extraction of key features, including spatial gradient mutation points, time series abnormal fluctuations and coupling relationships of multi-physical field signals; comparing the real-time extracted key features with a pre-set risk feature library, identifying the type of risk event, and classifying the identified risk event according to the spatial range and intensity of abnormal signals; generating and executing corresponding control instructions according to the type and level of the risk event, the control instructions including adjusting carbon dioxide injection parameters, starting downhole safety valves or issuing warning information.

2. The method of claim 1, wherein, The extraction of the coupling relationship of multi-physical field signals specifically includes: analyzing the spatial and temporal coincidence degree of the temperature abnormal drop area and the tensile strain abnormal increase area, and determining a potential carbon dioxide leakage signal when the coincidence degree exceeds a first threshold.

3. The method of claim 1, wherein, The risk event type at least includes one of carbon dioxide channeling along a fracture or fault, caprock integrity damage, and wellbore sealing failure, wherein the caprock integrity damage is identified based on the monitoring of a sustained upward tensile strain anomaly zone at the bottom interface of the caprock.

4. The method of claim 1, wherein, The risk level classification at least includes low, medium and high three levels, and the classification is based on the spatial continuity, change rate of abnormal signals and whether they appear in multiple physical field signals at the same time.

5. The method of claim 4, wherein, When the identified risk event is "carbon dioxide channeling along a fracture" and the risk level is "high", the generated control instruction is to automatically trigger the downhole safety valve to close and at the same time reduce the ground injection pressure to below the safety threshold.

6. The method of claim 1, wherein, The method further comprises: periodically comparing the current monitoring data with the historical baseline model, and evaluating the long-term sealing stability of the storage body by analyzing the long-term trend of caprock strain and reservoir temperature.

7. The method of claim 1, wherein, The collected acoustic vibration signals are analyzed to identify and locate acoustic events of specific frequencies generated by carbon dioxide flow or micro-fracturing of the formation.

8. The method of claim 1, wherein, The generated control instructions and related risk event information are displayed in real time on a visual decision interface, which simultaneously integrates downhole optical fiber monitoring data and ground injection parameters.

9. The method of claim 1, wherein, The pre-set risk feature library is pre-established through numerical simulation, indoor physical simulation experiment or by referring to the historical monitoring data of the same geological area.

10. An electronic device, comprising: A processor and a memory, the memory storing machine executable instructions executable by the processor, the processor being capable of executing the machine executable instructions to implement the method of any one of claims 1 to 9.

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