Method and system for monitoring and early warning fracturing flow-back fluid component leakage in real time based on underground water conductivity

Abstract

The invention discloses a method and a system for real-time monitoring and early warning of fracturing flow-back fluid component leakage based on underground water conductivity, and relates to the technical field of underground water environment monitoring and pollution early warning. Comprising the following steps: arranging a plurality of conductivity sensors at key positions of an underground water layer; performing data cleaning and de-noising processing on the conductivity data; analyzing the conductivity data after data cleaning and denoising processing based on a preset analysis algorithm; whether the monitored underground water layer conductivity change amplitude exceeds a preset threshold value or not is judged, if the monitored underground water layer conductivity change amplitude exceeds the preset threshold value, different levels of early warning are triggered according to the conductivity change amplitude, early warning countermeasures are started, and if not, the underground water layer conductivity change continues to be monitored. According to the invention, through continuous monitoring of the plurality of conductivity sensors, early signals of underground water pollution around the fracturing flowback operation area are effectively captured in time; data are automatically analyzed, an early warning signal is sent out, man-made misjudgment is reduced, emergency measures are rapidly started when early warning is triggered, and the risk of environmental pollution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of groundwater environment monitoring and pollution early warning, and in particular to a method and system for real-time monitoring and early warning of fracturing flowback fluid component leakage based on groundwater conductivity. Background Art

[0002] Hydraulic fracturing technology is widely used in the development of shale gas. It injects a large amount of water and chemical additives under high pressure to fracture the rock formation to obtain shale gas. However, during the fracturing flowback operation, some of the flowback fluid and chemical additives may seep into the groundwater system, causing the risk of groundwater pollution. At present, although measures are taken to recycle and treat the flowback fluid in fracturing flowback operations, groundwater pollution incidents still occur from time to time, especially because the composition of fracturing flowback fluid is complex and it is difficult to detect pollution problems in the early stage.

[0003] Existing monitoring technologies mainly rely on chemical analysis, physical monitoring and other means, but these methods often require time-consuming water sample collection and laboratory analysis, and it is difficult to reflect changes in groundwater quality in real time. Especially in the face of sudden pollution incidents, there is a lack of effective early warning mechanism, and it is impossible to effectively warn and promptly deal with possible environmental problems. There is an urgent need for a method that can monitor groundwater quality in real time and continuously, and promptly warn of groundwater pollution risks during shale gas extraction, so as to effectively deal with the problem of leakage and pollution of fracturing return fluid components in fracturing return operation areas.

[0004] Therefore, it is an urgent problem for technical personnel in this field to propose a method and system for real-time monitoring and early warning of leakage of fracturing return fluid components based on groundwater conductivity to solve the difficulties existing in the prior art. Summary of the invention

[0005] The present invention provides a method and system for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity, aiming to solve the problem of early detection and early warning of groundwater pollution risks during hydraulic fracturing flowback in fracturing flowback operation areas.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A method for real-time monitoring and early warning of leakage of fracturing flowback fluid components based on groundwater conductivity comprises the following steps:

[0008] S1. Arrange multiple conductivity sensors at key locations of the groundwater layer to monitor the conductivity changes of the groundwater layer and obtain the conductivity data of the groundwater layer;

[0009] S2. Perform data cleaning and denoising on the conductivity data;

[0010] S3. Analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm;

[0011] S4. Set the conductivity change threshold to determine whether the change in the conductivity of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, enter S5, otherwise continue to monitor the change in the conductivity of the groundwater layer;

[0012] S5. Trigger different levels of warnings according to the magnitude of conductivity changes and initiate warning response measures.

[0013] Optionally, the multiple conductivity sensors in S1 are arranged at the upstream of the fracturing and flowback operation area, on both sides of the fracturing and flowback operation area, and downstream of the fracturing and flowback operation area.

[0014] Optionally, the specific content of data cleaning and denoising of the conductivity data in S2 is: firstly, data cleaning is performed to remove obvious abnormal data and abnormal formats, and the cleaned conductivity data is smoothed to eliminate random noise interference.

[0015] Optionally, the specific content of analyzing the conductivity data after data cleaning and denoising based on a preset analysis algorithm in S3 is:

[0016] Use time series analysis or machine learning models to perform real-time analysis on the conductivity data after data cleaning and denoising, and identify the changing trend and abnormal fluctuation of conductivity by comparing it with the background conductivity.

[0017] Optionally, the conductivity change threshold set in S4 is 20% to 50%.

[0018] Optionally, in S5, different levels of warnings are triggered according to the magnitude of conductivity change, and specific contents of starting warning response measures are as follows:

[0019] When the conductivity rises by 20% to 40%, a first-level warning is issued, indicating that there may be pollution but it is not serious;

[0020] When the conductivity rises by 40% to 50%, a second-level warning is issued, indicating that moderate pollution may exist;

[0021] When the conductivity rises by more than 50% or reaches twice the background conductivity, a level 3 warning is issued, indicating that there is a serious risk of contamination and that immediate action must be taken.

[0022] Optionally, the early warning response measures include:

[0023] Immediately stop fracturing flowback operations after the warning is triggered, and collect and analyze water samples on site;

[0024] Investigate potential pollution sources and find leakage points;

[0025] Establish groundwater barriers or take water extraction and purification measures in contaminated areas to prevent the spread of pollution.

[0026] Optionally, the early warning includes multiple methods such as sound and light alarm, SMS notification, email notification and mobile application notification.

[0027] A system for early warning of leakage of fracturing return fluid components based on real-time monitoring of groundwater conductivity, using any of the above methods for early warning of leakage of fracturing return fluid components based on real-time monitoring of groundwater conductivity, comprising: a data acquisition module, a data processing module, a data analysis module, an early warning judgment module and an early warning trigger module;

[0028] A data acquisition module is provided, wherein a plurality of conductivity sensors are arranged at key positions of the groundwater layer to monitor the conductivity change of the groundwater layer and obtain the conductivity data of the groundwater layer;

[0029] A data processing module is used to clean and denoise the conductivity data;

[0030] A data analysis module, used to analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm;

[0031] The early warning judgment module sets the conductivity change threshold to determine whether the conductivity change of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, the early warning trigger module is entered, otherwise the conductivity change of the groundwater layer continues to be monitored;

[0032] The early warning trigger module triggers different levels of early warning according to the magnitude of conductivity change and initiates early warning response measures.

[0033] It can be seen from the above technical solution that compared with the prior art, the present invention provides a method and system for real-time monitoring and early warning of fracturing return fluid component leakage based on groundwater conductivity, which has the following beneficial effects: the present invention can timely and effectively capture early signals of fracturing return fluid component leakage and contamination through continuous monitoring by multiple conductivity sensors; based on dynamic threshold setting, it can accurately identify the impact of fracturing return fluid on groundwater components; and it can automatically analyze data and issue early warning signals to reduce human misjudgment. When the early warning is triggered, it can quickly initiate emergency measures to reduce the risk of environmental pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0035] Figure 1 A flow chart of a method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity provided by the present invention;

[0036] Figure 2 A system structure block diagram of a system for early warning of leakage of fracturing return fluid components based on real-time monitoring of groundwater conductivity provided by the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Reference Figure 1 As shown, the present invention discloses a method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity, comprising the following steps:

[0039] S1. Arrange multiple conductivity sensors at key locations of the groundwater layer to monitor the conductivity changes of the groundwater layer and obtain the conductivity data of the groundwater layer;

[0040] S2. Perform data cleaning and denoising on the conductivity data;

[0041] S3. Analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm;

[0042] S4. Set the conductivity change threshold to determine whether the change in the conductivity of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, enter S5, otherwise continue to monitor the change in the conductivity of the groundwater layer;

[0043] S5. Trigger different levels of warnings according to the magnitude of conductivity changes and initiate warning response measures.

[0044] Furthermore, the multiple conductivity sensors in S1 are arranged at the upstream of the fracturing return flow operation area, on both sides of the fracturing return flow operation area, and downstream of the fracturing return flow operation area.

[0045] Specifically, the layout of conductivity sensors should take into account the geological structure, hydrological conditions, and the impact range of fracturing flowback operations. The following are specific layout locations and quantity recommendations:

[0046] Layout principles

[0047] Covering key groundwater flow paths: Conductivity sensors should be placed along the main groundwater flow paths to monitor the impact of fracturing flowback fluid on water quality in real time;

[0048] Close to the fracturing return operation area: Conductivity sensors should be arranged upstream, on both sides and downstream of the fracturing return operation area, especially in the downstream of the operation area and in the area where potential pollution spreads. Densely arranged conductivity sensors can capture early signals of pollutants;

[0049] Arrangement at different hydrological levels: If there are multiple aquifers in the groundwater, it is recommended to arrange conductivity sensors at different depths to monitor the changes in conductivity in each aquifer;

[0050] The specific location of the conductivity sensor should be adjusted according to the hydrogeological conditions and the scale of the fracturing flowback operation;

[0051] The number of conductivity sensors to be arranged should be determined based on the basin area, number of fracturing wells, groundwater flow direction and operation scale;

[0052] Small-scale fracturing flowback operation area (basin area <50km 2 )

[0053] Total number of sensors: 6 to 8

[0054] Layout range: One sensor is arranged along the upstream recharge area of ​​the fracturing flowback operation area, one sensor is arranged in the diffusion direction on both sides, and 3 to 5 sensors are arranged in the downstream groundwater flow direction.

[0055] Medium-scale fracturing flowback operation area (basin area 50~200km 2 )

[0056] Total number of sensors: 10 to 15

[0057] Layout range: One sensor is arranged along the upstream recharge area of ​​the fracturing return operation area, 1 to 2 sensors are arranged in the diffusion direction on both sides, and 7 to 10 sensors are arranged in the downstream groundwater flow path and confluence area.

[0058] Large-scale fracturing flowback operation area (basin area> 200km 2 )

[0059] Total number of sensors: 15 to 25

[0060] Layout range: 1 to 2 sensors are arranged along the upstream recharge area of ​​the fracturing backflow operation area, 2 to 3 sensors are arranged in the diffusion direction on both sides, and 10 to 17 sensors are arranged in the downstream groundwater flow path.

[0061] Furthermore, the specific contents of data cleaning and denoising of the conductivity data in S2 are as follows: firstly, data cleaning is performed to remove obvious abnormal data and abnormal formats, and the cleaned conductivity data is smoothed to eliminate random noise interference.

[0062] Specifically, the main purpose of data cleaning is to remove erroneous, invalid or abnormal data to ensure the accuracy and consistency of the data. The following are the specific contents and common methods:

[0063] Data cleaning includes missing data processing, outlier processing, duplicate data processing, and formatting problem processing.

[0064] Data cleaning is carried out using methods such as missing value filling, linear interpolation, sliding window method, historical data filling method, threshold detection method, box plot method, and sliding mean method.

[0065] Denoising refers to eliminating or reducing random noise in conductivity sensor data to improve signal clarity. Since conductivity sensors may be affected by environmental noise, electromagnetic interference, etc., irregular noise fluctuations will appear in conductivity data. Denoising helps improve data quality and the accuracy of analysis results.

[0066] De-noising is performed using methods such as sliding average method, median filter method, Kalman filter, Fourier transform denoising, and wavelet transform denoising.

[0067] Due to the complexity of the groundwater system and the variability of the conductivity monitoring process, the denoising algorithm can be dynamically adjusted according to the real-time changes in the monitoring environment; in the case of drastic changes in conductivity, the degree of smoothing is reduced to retain more original signals; in the case of a relatively stable monitoring environment, the denoising intensity is increased to improve the stability of the data.

[0068] Furthermore, the specific contents of analyzing the conductivity data after data cleaning and denoising based on the preset analysis algorithm in S3 are as follows:

[0069] Use time series analysis or machine learning models to perform real-time analysis on the conductivity data after data cleaning and denoising, and identify the changing trend and abnormal fluctuation of conductivity by comparing it with the background conductivity.

[0070] Specifically, the trend analysis of conductivity is to analyze the time series of conductivity to capture long-term trends and changing patterns. Commonly used algorithms include: linear regression analysis, time series analysis (ARIMA model), exponential smoothing, anomaly detection algorithm (threshold detection, three sigma principle, sliding window detection), sliding window detection, and machine learning models;

[0071] Machine learning models include support vector machines (SVM), neural networks, and pollution source analysis algorithms;

[0072] Pollution source tracing analysis algorithms include regression analysis and spatial interpolation analysis.

[0073] Furthermore, the conductivity change threshold set in S4 is 20% to 50%.

[0074] Furthermore, in S5, different levels of warnings are triggered according to the magnitude of conductivity change, and the specific contents of the warning response measures are as follows:

[0075] When the conductivity rises by 20% to 40%, a first-level warning is issued, indicating that there may be pollution but it is not serious;

[0076] When the conductivity rises by 40% to 50%, a second-level warning is issued, indicating that moderate pollution may exist;

[0077] When the conductivity rises by more than 50% or reaches twice the background conductivity, a level 3 warning is issued, indicating that there is a serious risk of contamination and that immediate action must be taken.

[0078] Specifically, the background conductivity is determined as follows:

[0079] Before setting the conductivity threshold, you first need to understand the background conductivity of the monitoring area. Background conductivity is usually affected by the natural composition of groundwater, rock mineral solubility, precipitation, and human activities. You can obtain a baseline value for background conductivity by following the steps below:

[0080] Historical data analysis: Determine the normal conductivity range of groundwater by statistically analyzing the historical conductivity data in the monitoring area. Usually, at least one year of historical data needs to be collected to cover the natural fluctuations in different seasons.

[0081] Spatial difference analysis: The conductivity of different locations is spatially compared, especially the conductivity of the fracturing area, adjacent areas and distant areas, and the normal range differences of these areas are calculated.

[0082] Water quality baseline survey: Before conducting fracturing backflow operations, a water quality baseline survey is conducted to measure the initial conductivity of the groundwater in detail and serve as a comparison standard for subsequent monitoring.

[0083] Furthermore, the early warning response measures include:

[0084] Immediately stop fracturing flowback operations after the warning is triggered, and collect and analyze water samples on site;

[0085] Investigate potential pollution sources and find leakage points;

[0086] Establish groundwater barriers or take water extraction and purification measures in contaminated areas to prevent the spread of pollution.

[0087] Furthermore, the early warning includes multiple methods such as sound and light alarm, SMS notification, email notification and mobile application notification.

[0088] Embodiment 1:

[0089] A shale gas field is carrying out hydraulic fracturing flowback operations. There is a shallow groundwater resource supply area nearby, which poses a potential risk of groundwater pollution. In order to ensure the quality of groundwater, the changes in the conductivity of shallow groundwater during the fracturing flowback operation are monitored in real time to provide timely warnings of potential contamination of the fracturing flowback fluid.

[0090] (1) Conductivity sensor layout: A total of 6 conductivity sensors are laid out in the upstream, both sides and downstream groundwater runoff discharge areas of the fracturing flowback operation area, and in the residential water use area. The specific layout is as follows:

[0091] One conductivity sensor is arranged upstream of the fracturing return operation area to monitor the unaffected background conductivity of groundwater; two conductivity sensors are arranged in potential pollution diffusion areas on both sides of the fracturing return operation area; two conductivity sensors are arranged at key nodes of the downstream groundwater flow path; and one conductivity sensor is arranged near the downstream residents' water well to monitor the safety of the water source.

[0092] (2) System initialization: After the conductivity sensors are deployed, the system is initialized and all conductivity sensors are connected to the data processing module via wireless communication. By collecting initial data, the background conductivity of groundwater in the area is set to 500 μS / cm, based on which a dynamic change threshold of 20% to 50% is set.

[0093] (3) Data collection and transmission: Each conductivity sensor collects groundwater conductivity data in real time, and the conductivity data is transmitted to the data processing unit in real time via wireless communication. The collection frequency is set to once an hour to ensure data continuity and timeliness.

[0094] (4) Data cleaning and denoising: The data processing unit performs preliminary cleaning on the collected data and filters out abnormal fluctuations caused by occasional errors in the conductivity sensor or electromagnetic interference. For example, for sudden single-point abnormal values ​​(such as instantaneous conductivity fluctuations exceeding 1000μS / cm), the system will mark them as abnormal data and remove them.

[0095] (5) Data analysis: The cleaned data is input into the preset analysis algorithm, which analyzes the change trend of conductivity based on the comparison of historical data and real-time data. For example, the data of a certain sensor continues to grow in a short period of time (24 hours), and the conductivity rises from 500μS / cm to 750μS / cm, which exceeds the preset primary and secondary threshold ranges of 20% to 50%.

[0096] (6) Threshold detection and warning: When the conductivity change range monitored by the conductivity sensor is between the preset 20% and 40% threshold (i.e., between 600 and 700 μS / cm), the system automatically triggers the first-level warning. If the conductivity continues to increase and enters the 40% to 50% threshold (i.e., between 700 and 750 μS / cm), the system upgrades to the second-level warning.

[0097] (7) Emergency response measures: After triggering the secondary warning, the system automatically notifies the fracturing backflow operator to suspend operations and initiate emergency investigation measures, including: on-site water sample collection and laboratory analysis to confirm whether chemical pollutants have entered the groundwater; and investigate whether there is any backflow fluid leakage or equipment failure at the operation site, especially during the secondary fracturing backflow process.

[0098] (8) Result feedback and treatment: Laboratory analysis results showed that the water sample contained some fracturing flowback fluid components, and it was speculated that the fracturing flowback fluid entered the groundwater system. Subsequently, the operator closed the site and took groundwater pumping treatment measures to reduce the spread of pollution.

[0099] (9) Subsequent monitoring: After a period of treatment, the groundwater conductivity gradually recovered to about 500μS / cm, the system lifted the warning and returned to normal monitoring mode. At the same time, the relevant departments adjusted the treatment measures for fracturing flowback operations to ensure environmental safety during future operations.

[0100] Conclusion: The present invention monitors the changes in groundwater quality in real time by arranging conductivity sensors in the fracturing return operation area, and can promptly warn and take countermeasures in the early stage of pollution, thus successfully avoiding the further spread of pollution. The groundwater quality around the fracturing return operation area has been effectively protected, and the reliability and emergency response capabilities of the present invention have been verified.

[0101] Example 2

[0102] In a shale gas mining area, when hydraulic fracturing flowback operations were carried out, the groundwater source was threatened by potential pollution. For this reason, an early warning system based on real-time monitoring of groundwater conductivity was deployed in the area. The changes in conductivity data were used to determine whether there was contamination from fracturing flowback fluid, and corresponding countermeasures were taken. This example will detail how to use conductivity monitoring for early warning, as well as the response process when pollution occurs.

[0103] (1) Monitoring points: A total of 5 monitoring wells were set up in the groundwater recharge area around the fracturing backflow operation area and the area that may be affected by pollution. Each monitoring well is equipped with a high-precision conductivity sensor. These conductivity sensors can collect conductivity data in real time and transmit the data to the data analysis module through the wireless communication module. The specific layout of the monitoring wells is as follows:

[0104] Monitoring well 1: located upstream of the fracturing flowback operation area, monitoring the unaffected background conductivity of groundwater;

[0105] Monitoring well 2: Located in the key area 10m below the fracturing flowback collection pool, it is used to monitor the potential leakage and pollution risks of the fracturing flowback collection pool;

[0106] Monitoring Well 3 and Monitoring Well 4: Located on both sides of the fracturing flowback operation area, close to residential areas to prevent pollution from affecting residents' domestic water use;

[0107] Monitoring Well 5: Located 500m downstream of the fracturing flowback operation area, it serves as the main monitoring point for potential pollution.

[0108] (2) Data collection and analysis:

[0109] The system collects the conductivity of each monitoring point once an hour, and the data is transmitted to the data analysis module in real time.

[0110] The data analysis module compares the historical background conductivity with the real-time conductivity and uses the dynamic threshold method to detect abnormal situations. Assuming the background conductivity is 600μS / cm, when the conductivity of a monitoring point rises by 20% (i.e., reaching 720μS / cm), the system triggers a first-level warning; if it exceeds 40% and is less than 50% (i.e., reaching 840μS / cm), the system triggers a second-level warning.

[0111] (3) Early warning trigger mechanism:

[0112] Level 1 warning trigger: One morning, the conductivity of monitoring well 2 rose from the normal 600μS / cm to 720μS / cm, and the system immediately issued a level 1 warning signal. At this time, the staff of the data center received the warning notification and checked the historical data and change trend of the monitoring point. The analysis showed that this was a significant abnormal change, and it was initially determined that it might be related to the infiltration of fracturing return fluid.

[0113] Level 2 warning triggered: In the following two hours, the conductivity of monitoring well 2 continued to rise to 850μS / cm, and the system immediately upgraded to a level 2 warning and automatically sent a notification to the emergency response team. Data analysts further analyzed the conductivity data of this well and nearby wells and found that the conductivity of monitoring well 5 also had a clear upward trend. It was initially determined that the source of pollution may have begun to spread to other areas.

[0114] (4) Countermeasures:

[0115] On-site emergency response:

[0116] After receiving the second-level warning, the emergency team immediately went to the vicinity of monitoring wells 2 and 5 for on-site sampling and collected groundwater samples for laboratory analysis, focusing on detecting major ions, heavy metals, total dissolved solids, and other components in the water that may come from fracturing return fluids.

[0117] At the same time, the fracturing flowback operation was immediately suspended, and a comprehensive inspection was carried out on the specific location of the fracturing construction, the flowback fluid treatment process and possible leakage points.

[0118] Pollution source detection and control:

[0119] According to the results of water sample analysis, it was confirmed that the total dissolved solids (TDS) in the groundwater had increased significantly, and there were chemical substances similar to the composition of fracturing return fluid. Combined with on-site verification, it was preliminarily confirmed that the pollution was caused by leakage from the fracturing return fluid collection pool.

[0120] Pollution control measures: The emergency team took the following measures:

[0121] Repair the fracturing flowback fluid collection pool to prevent further leakage of fracturing flowback fluid.

[0122] (5) Further treatment and monitoring

[0123] Long-term monitoring: After repairing the fracturing flowback fluid collection pool, continue to conduct regular conductivity monitoring of the affected area, and monitor once every 2 hours in the initial stage. After confirming that the pollution trend is effectively controlled, gradually reduce the monitoring frequency.

[0124] (6) System improvement and summary: Through this early warning and response, the system timely discovered and effectively controlled the contamination of groundwater by fracturing return fluid. In the future, in similar environments, the early warning system will be further optimized:

[0125] In cases where there may be missed alerts or false alerts, increase monitoring frequency and adjust threshold settings to ensure a more sensitive early warning response.

[0126] Add more monitoring points to form a more complete groundwater monitoring network to ensure that the spread of pollution is discovered in time and countermeasures are taken quickly.

[0127] Summary: This example demonstrates how to quickly detect leakage of fracturing flowback fluid components through a real-time monitoring and early warning system of groundwater conductivity in actual scenarios, and effectively control the spread of pollution and protect water safety through a series of response measures.

[0128] and Figure 1 Corresponding to the method described above, the embodiment of the present invention also provides a system for early warning of leakage of fracturing return fluid components based on real-time monitoring of groundwater conductivity, which is used to Figure 1 The specific implementation of the method is shown in the following diagram: Figure 2As shown, it specifically includes: a data acquisition module, a data processing module, a data analysis module, a warning judgment module and a warning trigger module;

[0129] A data acquisition module is provided, wherein a plurality of conductivity sensors are arranged at key positions of the groundwater layer to monitor the conductivity change of the groundwater layer and obtain the conductivity data of the groundwater layer;

[0130] A data processing module is used to clean and denoise the conductivity data;

[0131] A data analysis module, used to analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm;

[0132] The early warning judgment module sets the conductivity change threshold to determine whether the conductivity change of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, the early warning trigger module is entered, otherwise the conductivity change of the groundwater layer continues to be monitored;

[0133] The early warning trigger module triggers different levels of early warning according to the magnitude of conductivity change and initiates early warning response measures.

[0134] Specifically, it also includes a wireless communication module used for communication between various modules.

[0135] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0136] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity, characterized in that: The following steps are involved: S1. Arrange multiple conductivity sensors at key locations of the groundwater layer to monitor the conductivity changes of the groundwater layer and obtain the conductivity data of the groundwater layer; S2. Perform data cleaning and denoising on the conductivity data; S3. Analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm; S4. Set the conductivity change threshold to determine whether the change in the conductivity of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, enter S5, otherwise continue to monitor the change in the conductivity of the groundwater layer; S5. Trigger different levels of warnings according to the magnitude of conductivity changes and initiate warning response measures.

2. A method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 1, characterized in that: The multiple conductivity sensors in S1 are arranged at the upstream of the fracturing return operation area, on both sides of the fracturing return operation area, and downstream of the fracturing return operation area.

3. A method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 1, characterized in that: The specific contents of data cleaning and denoising of the conductivity data in S2 are as follows: firstly, data cleaning is performed to remove obvious abnormal data and abnormal formats, and then the cleaned conductivity data is smoothed to eliminate random noise interference.

4. The method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 1, characterized in that: The specific contents of the analysis of the conductivity data after data cleaning and denoising in S3 based on the preset analysis algorithm are as follows: Use time series analysis or machine learning models to perform real-time analysis on the conductivity data after data cleaning and denoising, and identify the changing trend and abnormal fluctuation of conductivity by comparing it with the background conductivity.

5. The method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 1, characterized in that: The conductivity change threshold value set in S4 is 20% to 50%.

6. A method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 1, characterized in that: In S5, different levels of warnings are triggered according to the magnitude of conductivity changes, and the specific contents of the warning response measures are as follows: When the conductivity rises by 20% to 40%, a first-level warning is issued, indicating that there may be pollution but it is not serious; When the conductivity rises by 40% to 50%, a second-level warning is issued, indicating that moderate pollution may exist; When the conductivity rises by more than 50% or reaches twice the background conductivity, a level 3 warning is issued, indicating that there is a serious risk of contamination and that immediate action must be taken.

7. A method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 6, characterized in that: The early warning response measures include: Immediately stop fracturing flowback operations after the warning is triggered, and collect and analyze water samples on site; Investigate potential pollution sources and find leakage points; Establish groundwater barriers or take water extraction and purification measures in contaminated areas to prevent the spread of pollution.

8. The method for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity according to claim 6, characterized in that: The early warning includes sound and light alarms, SMS notifications, email notifications and mobile application notifications.

9. A system for early warning of leakage of fracturing flowback fluid components based on real-time monitoring of groundwater conductivity, characterized in that: A method for real-time monitoring and early warning of leakage of fracturing flowback fluid components based on groundwater conductivity as described in any one of claims 1 to 8, comprising: a data acquisition module, a data processing module, a data analysis module, an early warning judgment module and an early warning trigger module; A data acquisition module is provided, wherein a plurality of conductivity sensors are arranged at key positions of the groundwater layer to monitor the conductivity change of the groundwater layer and obtain the conductivity data of the groundwater layer; A data processing module is used to clean and denoise the conductivity data; A data analysis module, used to analyze the conductivity data after data cleaning and denoising based on a preset analysis algorithm; The early warning judgment module sets the conductivity change threshold to determine whether the conductivity change of the monitored groundwater layer exceeds the preset threshold. If it exceeds the preset threshold, the early warning trigger module is entered, otherwise the conductivity change of the groundwater layer continues to be monitored; The early warning trigger module triggers different levels of early warning according to the magnitude of conductivity change and initiates early warning response measures.

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