Method and device for evaluating underground water pollution caused by carbon sequestration project

Abstract

The invention provides a method and device for evaluating underground water pollution caused by carbon sequestration engineering, and relates to the technical field of carbon sequestration, and the method comprises the steps: setting a plurality of monitoring points in an underground water region of the carbon sequestration engineering, and setting various types of monitoring sensors at each monitoring point, the monitoring sensor comprises a dissolved carbon dioxide sensor, a heavy metal ion sensor, a pH sensor and a total dissolved solid sensor; for any monitoring point, acquiring monitoring data of the monitoring point under a plurality of monitoring indexes based on a monitoring sensor arranged on the monitoring point, and transmitting the monitoring data to a data processing center in real time; and performing groundwater pollution assessment on the received monitoring data of each monitoring point under the plurality of monitoring indexes based on the data processing center to obtain a groundwater pollution assessment score corresponding to the groundwater area. According to the method, it is ensured that the pollution source can be found in time when appearing, and diffusion and aggravation of potential pollution are avoided.

Description

Technical Field

[0001] This application relates to the field of carbon sequestration technology, and in particular to a method and apparatus for assessing groundwater pollution caused by carbon sequestration projects. Background Technology

[0002] As global climate change becomes increasingly severe, carbon capture, utilization, and storage (CCLS) technologies, as one of the key supporting technologies for achieving carbon neutrality, have been widely adopted in high-carbon-emission industries such as energy and chemicals. Among these, carbon sequestration projects, by compressing and transporting industrial carbon dioxide (CO2) emissions and injecting them into deep underground geological reservoirs (such as depleted oil and gas fields and salt rock formations) for long-term storage, can significantly reduce atmospheric CO2 concentrations and play an irreplaceable role in mitigating global warming.

[0003] However, carbon sequestration projects pose a potential risk of CO2 leakage during long-term operation: if the sealing of the storage formation is compromised (e.g., wellbore corrosion, formation fracture propagation), the injected CO2 may breach the storage barrier and migrate into the shallow groundwater system. Upon contact with groundwater, CO2 triggers a series of physicochemical changes. On one hand, CO2 dissolves in water to form carbonic acid, leading to a significant decrease in groundwater pH. On the other hand, acidic groundwater can disrupt the stability of underground rock formations, promoting the dissolution of heavy metal ions (such as lead, cadmium, and mercury) and inorganic salts, increasing the total dissolved solids content in groundwater and ultimately causing groundwater pollution. This type of pollution not only damages the ecological function of groundwater resources but may also infiltrate drinking water sources through groundwater runoff, posing a serious threat to human health and the ecological environment. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, one objective of this application is to propose a method for assessing groundwater pollution caused by carbon sequestration projects, comprising: setting up multiple monitoring points in the groundwater area of ​​the carbon sequestration project, and setting up various types of monitoring sensors at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors, and total dissolved solids sensors; for any monitoring point, collecting monitoring data under multiple monitoring indicators based on the monitoring sensors set up at the monitoring point, and transmitting the monitoring data to a data processing center in real time; and based on the data processing center's assessment of groundwater pollution of each monitoring point under multiple monitoring indicators, obtaining a groundwater pollution assessment score corresponding to the groundwater area.

[0006] The second objective of this application is to provide a device for assessing groundwater pollution caused by carbon sequestration projects.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a non-transitory computer-readable storage medium.

[0009] The fifth objective of this application is to provide a computer program product.

[0010] To achieve the above objectives, the first aspect of this application proposes a method for assessing groundwater pollution caused by carbon sequestration projects, comprising: setting up multiple monitoring points in the groundwater area of ​​the carbon sequestration project, and setting up various types of monitoring sensors at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors, and total dissolved solids sensors; for any monitoring point, collecting monitoring data of the monitoring point under multiple monitoring indicators based on the monitoring sensors set up at the monitoring point, and transmitting the monitoring data to a data processing center in real time; and based on the data processing center, conducting a groundwater pollution assessment on the received monitoring data of each monitoring point under multiple monitoring indicators to obtain a groundwater pollution assessment score corresponding to the groundwater area.

[0011] According to one embodiment of this application, a groundwater pollution assessment is performed on the monitoring data of each monitoring point under multiple monitoring indicators received by the data processing center to obtain the groundwater pollution assessment score corresponding to the groundwater area. The process includes: determining the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed based on the data processing center; obtaining the number information of each monitoring point; forming a matrix based on the number information of the monitoring data sequences corresponding to all monitoring points, and inputting the matrix into a pre-trained groundwater pollution assessment model to obtain the groundwater pollution assessment score corresponding to the groundwater area.

[0012] According to one embodiment of this application, before determining the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed based on the data processing center, the method further includes: preprocessing the received monitoring data based on the data processing center, wherein the preprocessing includes at least cleaning and standardization processing.

[0013] According to one embodiment of this application, after obtaining the groundwater pollution assessment score corresponding to the groundwater area, the method further includes: comparing the groundwater pollution assessment score with a plurality of preset score intervals to determine the target score interval in which the groundwater pollution assessment score is located; determining the target pollution risk level corresponding to the target score interval, wherein the target pollution risk level is a low risk level, a medium risk level, or a high risk level; and executing the target strategy corresponding to the target pollution risk level.

[0014] According to one embodiment of this application, a training method for a groundwater pollution assessment model includes the following steps: obtaining a training sample set corresponding to a groundwater area, wherein each training sample in the training sample set includes a sequence of monitoring data samples corresponding to all monitoring points under multiple monitoring indicators and a true label of groundwater pollution assessment score; iteratively training the initial groundwater pollution assessment model based on the training sample set until the loss function value is lower than a preset threshold, thereby obtaining a trained groundwater pollution assessment model.

[0015] According to one embodiment of this application, a method for obtaining the true label of groundwater pollution assessment score includes: obtaining the weights corresponding to each monitoring point; for any training sample, obtaining the monitoring data sample sequence corresponding to each monitoring point in the training sample under multiple monitoring indicators; for any monitoring point, determining the monitoring point pollution assessment score corresponding to the monitoring point based on the monitoring data sample sequence corresponding to the monitoring point using an expert scoring method; and performing a weighted summation of the monitoring point pollution assessment scores based on the weights corresponding to each monitoring point to obtain the true label of groundwater pollution assessment score corresponding to the training sample.

[0016] To achieve the above objectives, a second aspect of this application proposes a groundwater pollution assessment device for carbon sequestration projects, comprising: a setting module for setting multiple monitoring points in the groundwater area of ​​the carbon sequestration project, and setting multiple types of monitoring sensors at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors, and total dissolved solids sensors; a data acquisition module for acquiring monitoring data of any monitoring point under multiple monitoring indicators based on the monitoring sensors set at the monitoring point, and transmitting the monitoring data to a data processing center in real time; and an assessment module for assessing groundwater pollution based on the monitoring data of each monitoring point under multiple monitoring indicators received by the data processing center, and obtaining a groundwater pollution assessment score corresponding to the groundwater area.

[0017] According to one embodiment of this application, the evaluation module is further configured to: determine the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed based on the data processing center; obtain the number information of each monitoring point; form a matrix based on the number information of the monitoring data sequences corresponding to all monitoring points respectively, and input the matrix into a pre-trained groundwater pollution assessment model to obtain the groundwater pollution assessment score corresponding to the groundwater area.

[0018] According to one embodiment of this application, the evaluation module is further configured to: preprocess the received monitoring data based on the data processing center, wherein the preprocessing includes at least cleaning and standardization processing.

[0019] According to one embodiment of this application, the assessment module is further configured to: compare the groundwater pollution assessment score with a plurality of preset score intervals to determine the target score interval in which the groundwater pollution assessment score is located; determine the target pollution risk level corresponding to the target score interval, wherein the target pollution risk level is a low risk level, a medium risk level, or a high risk level; and execute the target strategy corresponding to the target pollution risk level.

[0020] According to one embodiment of this application, the groundwater pollution assessment device caused by carbon sequestration projects further includes: a training module, used to: acquire a training sample set corresponding to the groundwater area, wherein each training sample in the training sample set includes a sequence of monitoring data samples corresponding to all monitoring points under multiple monitoring indicators and a true label of the groundwater pollution assessment score; and iteratively train the initial groundwater pollution assessment model according to the training sample set until the loss function value is lower than a preset threshold to obtain a trained groundwater pollution assessment model.

[0021] According to one embodiment of this application, the training module is further configured to: obtain the weights corresponding to each monitoring point; for any training sample, obtain the monitoring data sample sequence corresponding to each monitoring point under multiple monitoring indicators in the training sample; for any monitoring point, determine the monitoring point pollution assessment score corresponding to the monitoring point based on the monitoring data sample sequence corresponding to the monitoring point using an expert scoring method; and perform a weighted summation of the monitoring point pollution assessment scores based on the weights corresponding to each monitoring point to obtain the true label of the groundwater pollution assessment score corresponding to the training sample.

[0022] To achieve the above objectives, a third aspect of this application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to implement the groundwater pollution assessment method resulting from carbon sequestration projects as described in the first aspect of this application.

[0023] To achieve the above objectives, a fourth aspect of this application provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the groundwater pollution assessment method caused by carbon sequestration projects as described in the first aspect of this application.

[0024] To achieve the above objectives, a fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements a groundwater pollution assessment method resulting from carbon sequestration projects as described in the first aspect of this application.

[0025] This application achieves at least the following beneficial effects: By setting up multiple monitoring points and equipping them with various types of sensors, this application can monitor multiple key pollution indicators in groundwater in real time, such as dissolved carbon dioxide, heavy metal ions, pH value, and total dissolved solids. This real-time data acquisition and transmission to the data processing center ensures that pollution sources can be detected in a timely manner when they appear, avoiding the spread and aggravation of potential pollution. The real-time transmission of monitoring data to the data processing center, combined with data analysis from various sensors, allows for accurate assessment based on multiple monitoring indicators. By comprehensively analyzing multiple indicators, the degree of groundwater pollution can be assessed more objectively, rather than relying solely on a single pollution source or parameter. This multi-dimensional data assessment can provide managers of carbon sequestration projects with more scientific decision support and timely adjustments to sequestration strategies. Attached Figure Description

[0026] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0027] Figure 1 This is an exemplary schematic diagram illustrating a method for assessing groundwater pollution caused by carbon sequestration projects, as shown in one embodiment of this application.

[0028] Figure 2 This is an exemplary schematic diagram of a groundwater pollution assessment device resulting from a carbon sequestration project, as shown in one embodiment of this application.

[0029] Figure 3 This is a schematic diagram of an electronic device according to one embodiment of this application. Detailed Implementation

[0030] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0031] Figure 1 This is an exemplary schematic diagram illustrating a method for assessing groundwater pollution caused by carbon sequestration projects, as shown in this application. Figure 1 As shown, the method for assessing groundwater pollution caused by this carbon sequestration project includes the following steps:

[0032] S101, multiple monitoring points are set up in the groundwater area of ​​the carbon sequestration project, and various types of monitoring sensors are set up at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors and total dissolved solids sensors.

[0033] The monitoring points must cover the following three types of areas:

[0034] Category 1: Upstream area (1-2km): Located upstream of the carbon sequestration area, unaffected by leakage.

[0035] Category 2: Surrounding area of ​​the storage well (within 500m): Storage wells adjacent to the carbon sequestration area are used to monitor water quality changes around the storage wells.

[0036] Category 3: Downstream Area: Located downstream of the carbon sequestration area (along the direction of groundwater flow), monitoring the area through which the water flows.

[0037] Among them, the dissolved carbon dioxide sensor is used to monitor changes in carbon dioxide concentration in groundwater in real time and assess the impact of carbon sequestration on water quality.

[0038] Among them, the heavy metal ion sensor is used to detect the concentration of harmful heavy metal ions (such as lead, cadmium, mercury, arsenic, etc.) in groundwater to ensure water quality safety.

[0039] Among them, the pH sensor is used to monitor the acidity and alkalinity (pH value) of groundwater and promptly detect water quality changes that may be caused by the carbon sequestration process.

[0040] Among them, the total dissolved solids sensor is used to measure the concentration of dissolved solids in groundwater, helping to assess the overall pollution level of water bodies.

[0041] S102: For any monitoring point, the monitoring data of the monitoring point under multiple monitoring indicators is collected based on the monitoring sensors set on the monitoring point, and the monitoring data is transmitted to the data processing center in real time.

[0042] Each monitoring sensor can collect data according to a preset collection cycle and transmit the collected data to the data processing center.

[0043] Since the aforementioned monitoring sensors include dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors, and total dissolved solids sensors, each monitoring point includes four monitoring indicators: carbon dioxide concentration, harmful heavy metal ion concentration in groundwater, pH value of groundwater, and concentration of dissolved solids in groundwater.

[0044] It's easy to understand that, assuming there are 10 monitoring points in a groundwater area, at each sampling time, monitoring point 1 will collect four monitoring data points: carbon dioxide concentration, concentration of harmful heavy metal ions in groundwater, pH value of groundwater, and concentration of dissolved solids in groundwater; monitoring point 2 will collect four monitoring data points: carbon dioxide concentration, concentration of harmful heavy metal ions in groundwater, pH value of groundwater, and concentration of dissolved solids in groundwater; and so on.

[0045] S103, based on the data processing center's assessment of groundwater pollution at each monitoring point under multiple monitoring indicators, groundwater pollution assessment scores are obtained for the corresponding groundwater area.

[0046] In some embodiments, the data processing center determines the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed; obtains the number information of each monitoring point; forms a matrix based on the number information of the monitoring data sequences corresponding to all monitoring points, and inputs the matrix into a pre-trained groundwater pollution assessment model to obtain the groundwater pollution assessment score corresponding to the groundwater area.

[0047] For example, assuming the window length of the time window to be analyzed is set to 30 days and the sliding step is set to 1 day, then the first time window to be analyzed is from day 1 to day 30, the second time window to be analyzed is from day 2 to day 31, and so on.

[0048] In this application, the groundwater pollution assessment model may employ a Long Short-Term Memory (LSTM) network.

[0049] Before determining the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed, based on the data processing center, the process also includes: preprocessing the received monitoring data based on the data processing center. The preprocessing includes at least cleaning (handling errors that may occur in the sensors, such as invalid data caused by sensor failure, environmental interference, etc.) and standardization (standardizing the data from different monitoring sensors to facilitate multi-source data fusion and ensure that various types of data can be compared and analyzed in the same evaluation model).

[0050] The training method for the groundwater pollution assessment model includes the following steps: obtaining a training sample set corresponding to the groundwater area (for example, if there are no real samples, indoor simulation experimental data can be used to simulate the changes in groundwater indicators in the area under different carbon dioxide leakage levels, generating 500-1000 sets of training samples). Each training sample in the training sample set includes monitoring data sample sequences corresponding to all monitoring points under multiple monitoring indicators and the true label of the groundwater pollution assessment score. Based on the training sample set, the initial groundwater pollution assessment model is iteratively trained (the process is the same as described above, requiring the monitoring data sample sequences corresponding to all monitoring points to be formed into a matrix based on the numbering information and then input into the initial groundwater pollution assessment model) until the loss function value is lower than a preset threshold, thus obtaining the trained groundwater pollution assessment model.

[0051] The method for obtaining the true label of the groundwater pollution assessment score includes: obtaining the weights corresponding to each monitoring point (for example, the weight of the monitoring point in the first type of upstream area is 0.2, the weight of the monitoring point in the second type of well-surrounding area is 0.5, and the weight of the monitoring point in the third type of downstream area is 0.3); for any training sample, obtaining the monitoring data sample sequence corresponding to each monitoring point under multiple monitoring indicators; for any monitoring point, determining the pollution assessment score of the monitoring point based on the monitoring data sample sequence corresponding to the monitoring point using the expert scoring method; and weighted summing of the pollution assessment scores of the monitoring points based on the weights corresponding to each monitoring point to obtain the true label of the groundwater pollution assessment score corresponding to the training sample.

[0052] Furthermore, after obtaining the groundwater pollution assessment score corresponding to the groundwater area, the process also includes: comparing the groundwater pollution assessment score with multiple preset score intervals to determine the target score interval in which the groundwater pollution assessment score is located; determining the target pollution risk level corresponding to the target score interval, which may be a low-risk level, a medium-risk level, or a high-risk level; and implementing the target strategy corresponding to the target pollution risk level.

[0053] For example, the score range can be divided into multiple levels, such as 0-20 points for low risk, 21-50 points for medium risk, and 51 points and above for high risk.

[0054] For example, if the target pollution risk level is low, the groundwater pollution assessment log for the corresponding groundwater area can be updated without issuing an early warning.

[0055] For example, if the target pollution risk level is medium risk, the medium risk level alarm strategy corresponding to the medium risk level is implemented (for example, issuing a yellow alarm signal and sending alarm information to the electronic devices of relevant personnel to remind them to increase the detection frequency and implement some pollution control measures, such as reducing carbon injection or strengthening water quality improvement in local areas), and the groundwater pollution assessment log corresponding to the groundwater area is updated.

[0056] For example, if the target pollution risk level is high risk, the high risk level alarm strategy corresponding to the high risk level is implemented (for example, issuing a red alarm signal and sending alarm information to the electronic devices of relevant personnel to remind them to intervene on-site and implement pollution cleanup and water source protection measures), and the groundwater pollution assessment log corresponding to the groundwater area is updated.

[0057] This application proposes a method for assessing groundwater pollution caused by carbon sequestration projects, comprising: setting up multiple monitoring points in the groundwater area of ​​the carbon sequestration project, and setting up various types of monitoring sensors at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors, and total dissolved solids sensors; for any monitoring point, collecting monitoring data under multiple monitoring indicators based on the monitoring sensors set up at the monitoring point, and transmitting the monitoring data to a data processing center in real time; and conducting groundwater pollution assessment on the received monitoring data of each monitoring point under multiple monitoring indicators based on the data processing center, to obtain a groundwater pollution assessment score corresponding to the groundwater area.

[0058] This application achieves at least the following beneficial effects: By setting up multiple monitoring points and equipping them with various types of sensors, this application can monitor multiple key pollution indicators in groundwater in real time, such as dissolved carbon dioxide, heavy metal ions, pH value, and total dissolved solids. This real-time data acquisition and transmission to the data processing center ensures that pollution sources can be detected in a timely manner when they appear, avoiding the spread and aggravation of potential pollution. The real-time transmission of monitoring data to the data processing center, combined with data analysis from various sensors, allows for accurate assessment based on multiple monitoring indicators. By comprehensively analyzing multiple indicators, the degree of groundwater pollution can be assessed more objectively, rather than relying solely on a single pollution source or parameter. This multi-dimensional data assessment can provide managers of carbon sequestration projects with more scientific decision support and timely adjustments to sequestration strategies.

[0059] Figure 2 This is an exemplary schematic diagram of a groundwater pollution assessment device resulting from a carbon sequestration project, as shown in this application. Figure 2 As shown, the groundwater pollution assessment device 200 resulting from the carbon sequestration project includes a setup module 201, a data acquisition module 202, and an assessment module 203, wherein:

[0060] The module 201 is used to set up multiple monitoring points in the groundwater area of ​​the carbon sequestration project, and to set up multiple types of monitoring sensors at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors and total dissolved solids sensors.

[0061] The acquisition module 202 is used to acquire monitoring data of any monitoring point under multiple monitoring indicators based on the monitoring sensors set on the monitoring point, and transmit the monitoring data to the data processing center in real time.

[0062] The assessment module 203 is used to assess groundwater pollution based on the monitoring data received from each monitoring point under multiple monitoring indicators by the data processing center, and to obtain the groundwater pollution assessment score corresponding to the groundwater area.

[0063] This device, by setting up multiple monitoring points and equipping them with various types of sensors, can monitor multiple key pollution indicators in groundwater in real time, such as dissolved carbon dioxide, heavy metal ions, pH value, and total dissolved solids. This real-time data acquisition and transmission to the data processing center ensures that pollution sources can be detected in a timely manner when they appear, preventing the spread and aggravation of potential pollution. The real-time transmission of monitoring data to the data processing center, combined with data analysis from various sensors, allows for accurate assessment based on multiple monitoring indicators. By comprehensively analyzing multiple indicators, the degree of groundwater pollution can be assessed more objectively, rather than relying solely on a single pollution source or parameter. This multi-dimensional data assessment can provide carbon sequestration project managers with more scientific decision support and timely adjustments to sequestration strategies.

[0064] Furthermore, the evaluation module 203 is also used to: determine the monitoring data sequence corresponding to each monitoring point under multiple monitoring indicators within the current time window to be analyzed based on the data processing center; obtain the number information of each monitoring point; form a matrix based on the number information of the monitoring data sequences corresponding to all monitoring points, and input the matrix into the pre-trained groundwater pollution assessment model to obtain the groundwater pollution assessment score corresponding to the groundwater area.

[0065] Furthermore, the evaluation module 203 is also used to: preprocess the received monitoring data based on the data processing center, the preprocessing including at least cleaning and standardization.

[0066] Furthermore, the assessment module 203 is also used to: compare the groundwater pollution assessment score with multiple preset score intervals to determine the target score interval in which the groundwater pollution assessment score is located; determine the target pollution risk level corresponding to the target score interval, wherein the target pollution risk level is a low risk level, a medium risk level, or a high risk level; and execute the target strategy corresponding to the target pollution risk level.

[0067] Furthermore, the groundwater pollution assessment device 200 caused by carbon sequestration projects also includes: a training module, used to: acquire a training sample set corresponding to the groundwater area, wherein each training sample in the training sample set includes monitoring data sample sequences corresponding to all monitoring points under multiple monitoring indicators and groundwater pollution assessment score true labels; and iteratively train the initial groundwater pollution assessment model according to the training sample set until the loss function value is lower than a preset threshold to obtain a trained groundwater pollution assessment model.

[0068] Furthermore, the training module is also used to: obtain the weights corresponding to each monitoring point; for any training sample, obtain the monitoring data sample sequence corresponding to each monitoring point under multiple monitoring indicators; for any monitoring point, determine the pollution assessment score corresponding to the monitoring point based on the monitoring data sample sequence corresponding to the monitoring point using the expert scoring method; and perform a weighted summation of the pollution assessment scores of the monitoring points based on the weights corresponding to each monitoring point to obtain the true label of the groundwater pollution assessment score corresponding to the training sample.

[0069] To implement the above embodiments, this application also proposes an electronic device 300, such as... Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302 communicatively connected to the processor. The memory 302 stores instructions that can be executed by at least one processor. The instructions are executed by at least one processor 301 to implement the groundwater pollution assessment method caused by carbon sequestration projects as shown in the above embodiments.

[0070] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to implement the groundwater pollution assessment method caused by carbon sequestration projects as shown in the above embodiments.

[0071] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the groundwater pollution assessment method caused by carbon sequestration projects as shown in the above embodiments.

[0072] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0073] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0074] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0075] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for assessing groundwater pollution caused by carbon sequestration projects, characterized in that, The method comprises the following steps: a plurality of monitoring points are arranged in a groundwater area of a carbon sequestration project, and a plurality of types of monitoring sensors are arranged at each monitoring point, including dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors and total dissolved solids sensors; for any monitoring point, monitoring data of the monitoring point under a plurality of monitoring indicators is collected based on the monitoring sensors arranged at the monitoring point, and the monitoring data is transmitted to a data processing center in real time; the data processing center evaluates the monitoring data of each monitoring point under a plurality of monitoring indicators received by the data processing center to obtain a groundwater pollution evaluation score corresponding to the groundwater area.

2. The method of claim 1, wherein, The method of evaluating the groundwater pollution based on the data processing center and the monitoring data of each monitoring point under a plurality of monitoring indicators received by the data processing center to obtain a groundwater pollution evaluation score corresponding to the groundwater area comprises the following steps: the data processing center determines a monitoring data sequence corresponding to each monitoring point under a plurality of monitoring indicators in a current time window to be analyzed; obtain the number information of each monitoring point; based on the number information, the monitoring data sequence corresponding to each monitoring point is formed into a matrix, and the matrix is input into a pre-trained groundwater pollution evaluation model to obtain a groundwater pollution evaluation score corresponding to the groundwater area.

3. The method of claim 2, wherein, Before the data processing center determines a monitoring data sequence corresponding to each monitoring point under a plurality of monitoring indicators in a current time window to be analyzed, the method further comprises the following steps: the data processing center pre-processes the monitoring data received by the data processing center, and the pre-processing at least includes cleaning and standardization.

4. The method according to any one of claims 1 to 3, characterized in that, After obtaining the groundwater pollution evaluation score corresponding to the groundwater area, the method further comprises the following steps: comparing the groundwater pollution evaluation score with a plurality of preset score intervals to determine a target score interval in which the groundwater pollution evaluation score is located; determining a target pollution risk level corresponding to the target score interval, wherein the target pollution risk level is a low risk level, a medium risk level or a high risk level; executing a target strategy corresponding to the target pollution risk level.

5. The method of claim 2, wherein, The training method of the groundwater pollution evaluation model comprises the following steps: obtain a training sample set corresponding to the groundwater area, wherein each training sample in the training sample set comprises a monitoring data sample sequence corresponding to each monitoring point under a plurality of monitoring indicators and a groundwater pollution evaluation score real label; iteratively train an initial groundwater pollution evaluation model according to the training sample set until the loss function value is lower than a preset threshold to obtain a trained groundwater pollution evaluation model.

6. The method of claim 5, wherein, The method for obtaining the groundwater pollution evaluation score real label comprises the following steps: obtain the weight corresponding to each monitoring point; for any training sample, obtain a monitoring data sample sequence corresponding to each monitoring point under a plurality of monitoring indicators in the training sample. For any of the monitoring points, a monitoring point pollution evaluation score corresponding to the monitoring point is determined based on the expert scoring method based on the monitoring data sample sequence corresponding to the monitoring point. The monitoring point pollution evaluation scores are weighted and summed based on the respective weights corresponding to each of the monitoring points to obtain a true label of a groundwater pollution evaluation score corresponding to the training sample.

7. An apparatus for assessing groundwater pollution caused by carbon sequestration projects, characterized by, Comprise: The setting module is used for setting a plurality of monitoring points in the groundwater area of the carbon sequestration project, and a plurality of types of monitoring sensors are arranged at each of the monitoring points, and the monitoring sensors include dissolved carbon dioxide sensors, heavy metal ion sensors, pH sensors and total dissolved solids sensors; The acquisition module is used for acquiring monitoring data of the monitoring points under a plurality of monitoring indexes based on the monitoring sensors arranged at the monitoring points for any of the monitoring points, and transmitting the monitoring data to a data processing center in real time; The evaluation module is used for performing groundwater pollution evaluation on the monitoring data of each of the monitoring points under a plurality of monitoring indexes received by the data processing center, to obtain a groundwater pollution evaluation score corresponding to the groundwater area.

8. An electronic device comprising: At least one processor; And, A memory connected in communication with the at least one processor; wherein The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to enable the computer to perform the method according to any one of claims 1-6.

10. A computer program product comprising a computer program which, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

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