Method for determining methane emission source based on multiple features of sewer network and storage medium

Abstract

The present disclosure relates to a method for determining a methane emission source based on multi-feature fusion of a sewer network and a storage medium, the method comprising: performing multiple mobile walk-through detections on multiple lines in a study area to determine multiple methane plumes and first positions of the methane plumes; determining emission feature scores of the methane plumes; determining geochemical feature scores of the methane plumes; determining geographic feature scores of the methane plumes based on first distances between the methane plumes and the nearest sewer network nodes and standard distances; determining plume confidence of each methane plume based on the emission feature scores, the geochemical feature scores and the geographic feature scores; dividing regional range data corresponding to the study area into multiple grids to obtain multiple grids, and determining grid confidence corresponding to each grid based on the first positions and the plume confidence; and determining a position of the methane emission source based on the grid confidence. Thus, the accuracy of identifying and locating the methane emission source in the sewer network is improved.

Description

Technical Field

[0001] This disclosure relates to the field of atmospheric monitoring technology, and in particular to a method and storage medium for determining methane emission sources based on the fusion of multiple features of drainage pipe networks. Background Technology

[0002] The impact of human activities on the global climate system is clear—since industrialization, greenhouse gas emissions have reached unprecedented levels, resulting in global temperatures 1.09°C (0.95–1.2°C) higher than pre-industrial levels. Reducing anthropogenic greenhouse gas emissions, under the constraints of the Paris Agreement, has become a global consensus in addressing climate change.

[0003] Methane is the second largest greenhouse gas source after carbon dioxide, characterized by its short atmospheric lifetime and significant potential contribution to global warming. Recent research indicates that its warming potential over a 20-year period is more than 80 times that of carbon dioxide. Therefore, implementing specific emission reduction measures for methane is considered a crucial pathway to gaining more time to control global warming.

[0004] During the transportation of sewage and wastewater through drainage pipe networks, methane, after being generated in the liquid phase, undergoes mass transfer and stripping from the water-gas interface via gas lift. It then accumulates as a gas in the headspace above the pipeline and is ultimately released into the atmosphere through nodes connected to the atmosphere, such as septic tanks, various functional wells, pumping stations, and downstream sewage treatment plant structures. If the methane emission sources in the drainage pipe network can be accurately identified, the release of methane into the atmosphere can be effectively blocked. However, current technologies do not offer high accuracy in identifying methane emission sources. Summary of the Invention

[0005] In view of this, this disclosure proposes a scheme for determining methane emission sources based on the fusion of multiple features of drainage pipe networks.

[0006] According to one aspect of this disclosure, a method for determining methane emission sources is provided. The method includes: conducting multiple mobile surveys along multiple lines within a study area to determine multiple methane plumes and their first locations; determining an emission characteristic score for each methane plume; determining a geochemical characteristic score for the methane plume based on the concentration of at least one indicator detected at the methane plume; determining a geographical characteristic score for the methane plume based on a first distance and a standard distance between the methane plume and the nearest drainage network node; determining a plume confidence level for each methane plume based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score; dividing the regional data corresponding to the study area into multiple grids; determining a grid confidence level for each grid based on the first location and the plume confidence level; and determining the location of the methane emission source based on the grid confidence level.

[0007] In one possible implementation, the methane plume includes: a continuous methane plume and a non-continuous methane plume. The step of performing multiple mobile surveys along multiple lines within the study area to determine multiple methane plumes and their initial locations includes: obtaining multiple methane concentration sequence data through the mobile surveys, the methane concentration sequence data containing multiple methane concentration values ​​and the geographic coordinates of each methane concentration value; identifying the methane plume and its original location based on the methane concentration sequence data; and determining the initial location of the continuous plume and the initial location of the non-continuous plume on each line based on the original location.

[0008] In one possible implementation, determining the first position of the continuous plume and the first position of the non-continuous plume on each of the lines based on the original position includes: clustering the methane plumes detected on each line based on the original position corresponding to each line to obtain a continuous methane plume cluster and / or a non-continuous methane plume cluster; aligning the positions of the methane plumes in the continuous methane plume cluster on the same line to obtain the first position of each methane plume in the continuous methane plume cluster; and using the original position of the methane plume in the non-continuous methane plume cluster as its first position.

[0009] In one possible implementation, determining the emission characteristic score of each methane plume includes: clustering the methane plumes detected on the same route to obtain at least one methane plume cluster; and determining the emission characteristic score of each methane plume in each methane plume cluster corresponding to the route based on the number of navigation trips on the route and the number of methane plumes in each methane plume cluster corresponding to the route.

[0010] In one possible implementation, determining the geochemical characteristic score of the methane plume based on the concentration of at least one indicator detected at the methane plume includes: determining at least one indicator index based on the concentration of the at least one indicator; determining a first score corresponding to the at least one indicator index based on the relationship between the at least one indicator index and a preset threshold range; and weighting each of the first scores corresponding to the methane plume to obtain the geochemical characteristic score of the methane plume.

[0011] In one possible implementation, determining the geographic feature score of the methane plume based on a first distance and a standard distance between the methane plume and the nearest drainage network node includes:

[0012] Based on the first location of the methane plume and the second location of each of the drainage network nodes, a first distance between the methane plume and the nearest drainage network node is determined; based on the first distance and the standard distance, the geographical feature score is determined.

[0013] In one possible implementation, determining the plume confidence of each methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographic characteristic score includes: determining an initial plume confidence of the methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographic characteristic score; obtaining a conflict factor if the geochemical characteristic score and the geographic characteristic score satisfy a first condition, or if the escaping characteristic score and the geochemical characteristic score satisfy a second condition; and adjusting the initial plume confidence using the conflict factor to obtain the plume confidence.

[0014] In one possible implementation, dividing the regional range data corresponding to the study area into multiple grids, and determining the grid confidence level corresponding to each grid based on the first location and the plume confidence level, includes: determining the methane plume corresponding to the grid and the plume confidence level corresponding to the grid based on the first location; and determining the grid confidence level corresponding to the grid based on the plume confidence level corresponding to the grid.

[0015] In one possible implementation, determining the location of the methane emission source based on the grid confidence level includes: determining a first number of navigation runs within a region defined by the grid; determining a grid confidence density based on the first number of navigation runs and the grid confidence level corresponding to the grid; determining a first target grid based on the relationship between each grid confidence density and a density threshold; performing a secondary verification on the target region defined by the first target grid; and determining the location of the methane emission source based on the verification results.

[0016] According to another aspect of this disclosure, a methane escaping source determination apparatus is provided, the apparatus comprising:

[0017] The first location determination unit is used to perform multiple mobile surveys on multiple lines within the study area to determine multiple methane plumes and the first location of the methane plumes.

[0018] An efflux characteristic score determination unit is used to determine the efflux characteristic score of each methane plume.

[0019] A geochemical feature scoring unit is used to determine the geochemical feature score of the methane plume based on the concentration of at least one indicator detected at the methane plume.

[0020] The geographic feature scoring unit is used to determine the geographic feature score of the methane plume based on the first distance and the standard distance between the methane plume and the nearest drainage network node.

[0021] A plume confidence determination unit is used to determine the plume confidence of each methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographical characteristic score.

[0022] The grid confidence determination unit is used to divide the regional range data corresponding to the study area into grids to obtain multiple grids, and determine the grid confidence corresponding to each grid based on the first location and the plume confidence.

[0023] The methane emission source location determination unit is used to determine the location of the methane emission source based on the grid confidence level.

[0024] In one possible implementation, the methane plume includes: a continuous methane plume and a non-continuous methane plume, and the first position determination unit is further configured to:

[0025] Through the mobile survey, multiple methane concentration sequence data can be obtained. The methane concentration sequence data includes multiple methane concentration values ​​and the geographic coordinates of each methane concentration value.

[0026] Based on the methane concentration sequence data, the methane plume and its original location were identified.

[0027] Based on the original positions, the first positions of the continuous plumes and the first positions of the non-continuous plumes on each of the lines are determined.

[0028] In one possible implementation, the first position determining unit is further configured to:

[0029] Based on the original positions corresponding to each of the lines, the methane plumes detected on each of the lines are clustered to obtain persistent methane plume clusters and / or non-persistent methane plume clusters.

[0030] Align the positions of the methane plumes in the continuous methane plume clusters on the same line to obtain the first position of each methane plume in the continuous methane plume cluster.

[0031] The original position of the methane plume in the non-persistent methane plume cluster is taken as its first position.

[0032] In one possible implementation, the evaporation feature scoring and determining unit is further configured to:

[0033] Clustering of methane plumes detected on the same line yields at least one methane plume cluster.

[0034] Based on the number of navigation trips on the route and the number of methane plumes in each methane plume cluster corresponding to the route, the emission characteristic score of each methane plume in each methane plume cluster corresponding to the route is determined.

[0035] In one possible implementation, the geodesic feature scoring and determination unit is further configured to:

[0036] Based on the concentration of the at least one indicator, at least one indicator index is determined;

[0037] Based on the relationship between the at least one indicator and a preset threshold range, a first score corresponding to the at least one indicator is determined;

[0038] The geochemical characteristic score of the methane plume is obtained by weighting each of the first scores corresponding to the methane plume.

[0039] In one possible implementation, the geographic feature scoring and determination unit is further configured to:

[0040] Based on the first position of the methane plume and the second positions of each of the drainage network nodes, the first distance between the methane plume and the nearest drainage network node is determined.

[0041] The geographic feature score is determined based on the first distance and the standard distance.

[0042] In one possible implementation, the plume confidence determination unit is further configured to:

[0043] Based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score, the initial plume confidence level of the methane plume is determined;

[0044] If the geochemical feature score and the geographic feature score satisfy the first condition, or if the escaping feature score and the geochemical feature score satisfy the second condition, a conflict factor is obtained.

[0045] The initial plume confidence level is adjusted using the conflict factor to obtain the plume confidence level.

[0046] In one possible implementation, the grid confidence determination unit is further configured to:

[0047] Based on the first location, determine the methane plume corresponding to the grid and the plume confidence level corresponding to the grid;

[0048] The grid confidence level is determined based on the plume confidence level corresponding to the grid.

[0049] In one possible implementation, the methane escaping source location determination unit is further configured to:

[0050] Determine the first number of walks within the area defined by the grid;

[0051] The grid confidence density is determined based on the first number of navigation trips and the grid confidence corresponding to the grid.

[0052] Based on the relationship between the confidence density and the density threshold of each grid, the first target grid is determined;

[0053] A second verification is performed on the target area defined by the first target grid, and the location of the methane emission source is determined based on the verification results.

[0054] According to another aspect of this disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0055] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described method.

[0056] According to another aspect of this disclosure, a computer program product is provided, including a computer program or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program, when executed by a processor, implements the steps of the above-described method.

[0057] In this embodiment, the methane plume identified by the mobile survey method is scored across three dimensions: emission characteristics, geochemical characteristics, and geographical characteristics. This approach fully considers influencing factors and accurately evaluates the identified methane plume's persistence, correlation with the drainage network, and proximity to drainage network nodes. This improves the accuracy and reliability of determining whether a methane plume originates from the drainage network, i.e., it enhances the accuracy and reliability of plume confidence. Furthermore, the regional data corresponding to the study area is divided into grids. Using these grids as positioning units, the entire drainage network's nodes are comprehensively covered, reducing the probability of missing nodes. Based on the first location and plume confidence, the likelihood of a grid containing a methane plume from the drainage network can be accurately determined, i.e., the grid-level confidence (grid confidence) is determined. The grid confidence is then used to indicate the methane emission source. Therefore, the method of this disclosure improves the accuracy of identifying and locating methane emission sources in the drainage network.

[0058] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0059] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0060] Figure 1 This is a flowchart illustrating the method for determining methane emission sources provided in this embodiment of the disclosure.

[0061] Figure 2 This is a schematic diagram of the structure of the methane emission source determination device provided in the embodiments of this disclosure.

[0062] Figure 3 This is a schematic diagram of the structure of an electronic device for determining methane emission sources, provided in an embodiment of this disclosure. Detailed Implementation

[0063] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0064] As used herein, the terms “comprising,” “including,” “having,” or variations thereof are open-ended and include one or more of the stated features, integrals, elements, steps, components, or functions, but do not exclude the presence or addition of one or more other features, integrals, elements, steps, components, functions, or groups thereof.

[0065] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0066] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another. Therefore, without departing from the teachings of the inventive concept, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0067] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0068] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0069] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0070] During the transportation of sewage and wastewater through drainage pipe networks, methane, after being generated in the liquid phase, undergoes mass transfer and stripping from the water-gas interface via gas lift. It then accumulates as a gas in the headspace above the pipeline and is eventually released into the atmosphere through nodes connected to the atmosphere, such as septic tanks, various functional wells, pumping stations, and downstream sewage treatment plant structures. If the methane emission sources in the drainage pipe network can be accurately identified, the release of methane into the atmosphere from the drainage network can be effectively prevented.

[0071] Currently, the main methods for monitoring gas emissions from drainage pipe network nodes include: mobile monitoring, static culvert monitoring, and exhaust gas measurement. Among these, the static culvert method and exhaust gas measurement are relatively inefficient. Furthermore, these two methods involve random selection of monitored nodes within the drainage pipe network, relying heavily on experience, and making it difficult to accurately cover major emission sources. Because these two methods have limited coverage, they struggle to obtain emission data from a wide range of drainage pipe networks, reducing the accuracy of identifying methane emission sources.

[0072] Although mobile monitoring is highly efficient, it relies solely on methane concentration thresholds for source tracing, resulting in a single standard. This makes it prone to misidentifying methane plumes escaping from non-drainage network nodes as originating from the drainage network, and also to missing methane plumes actually escaping from drainage network nodes. Therefore, this method cannot accurately pinpoint methane emission sources.

[0073] This disclosure proposes a method for identifying methane emission sources. Considering the characteristics of methane emission from drainage pipe network nodes, a multi-feature fusion approach is used to evaluate the confidence level of methane plumes. Then, based on the methane plume confidence level, a grid-level confidence level is determined. This method not only comprehensively covers the drainage pipe network but also reduces the probability of false positives and false negatives in identifying methane plume sources, thus improving the accuracy of identifying methane emission sources in the drainage pipe network.

[0074] Figure 1 This is a schematic flowchart illustrating the method for determining methane emission sources provided in embodiments of this disclosure. Figure 1As shown, the method includes:

[0075] S11, Multiple mobile surveys are conducted along multiple lines within the study area to determine multiple methane plumes and their first locations.

[0076] In this disclosure, mobile monitoring can be performed using a mobile monitoring platform. The mobile monitoring platform is equipped with at least high-precision measurement capabilities for methane (CH4) and its carbon-13 isotope (C13). The mobile monitoring platform includes concentration acquisition and detection functions, as well as positioning functions. Specifically, the first device used to acquire CH4 concentration values ​​operates at a frequency no less than 1 Hz and no more than 10 Hz; the acquisition accuracy error is less than 5 ppb + 0.05%. ppb is a dimensionless unit of concentration, representing one billionth of the solute's mass in the solution. The first device has a sensitivity error of less than 1 ppb and a stability error (i.e., annual drift under uncalibrated conditions) of less than 2 ppb.

[0077] Mobile mobile monitoring platform used for data collection The second device for collecting concentration values ​​has a sampling frequency not higher than 1 Hz, and the sampling accuracy error is less than 5‰ ± 3.5‰.

[0078] In a mobile monitoring platform, the first device and the second device can be integrated into the same device, or the same device can have the functions of both the first and second devices. This disclosure does not limit this aspect.

[0079] The positioning accuracy error of the mobile navigation platform is no greater than 0.5 meters, and the positioning frequency is no higher than 1 Hz.

[0080] In this embodiment of the disclosure, the study area may include a drainage pipe network. The pipe layout path in the drainage pipe network can be considered as a route. For example, the study area can be a region in a city. In this region, the drainage pipe network is set under roads, and the roads where the drainage pipes are laid can be considered as routes. Multiple mobile monitoring tests can be performed on each route. In one example, no less than 10 mobile monitoring tests can be performed on each route.

[0081] The first location can be the geographic coordinates of the methane plume. These geographic coordinates can be provided by a mobile monitoring platform or calculated based on the geographic coordinates provided by the mobile monitoring platform.

[0082] S12, determine the emission characteristic score of each methane plume.

[0083] Emission characteristic score can characterize the persistence of a methane plume. This persistence can be measured by duration. For example, the persistence can be estimated from the concentration of the methane plume, thus obtaining the emission characteristic score. This is merely an example; the method for determining the emission characteristic score will be described in detail below. This disclosure does not limit the method for determining the emission characteristic score. The value of the emission characteristic score is positively correlated with the persistence of the methane plume.

[0084] S13, Based on the concentration of at least one indicator detected at the methane plume, determine the geochemical characteristic score of the methane plume.

[0085] In embodiments of this disclosure, indicators can be determined based on the characteristics of methane escaping from a drainage network. An indicator index can be calculated based on the concentration of the indicator. The indicator index reflects the likelihood that the methane plume originates from the drainage network. Exemplarily, indicators may include methane and carbon dioxide. In another example, indicators may include methane carbon-13 isotopes and / or methane carbon-2 isotopes. These are merely examples of indicators and do not exhaustively list all indicators; other indicators are also within the scope of this disclosure.

[0086] In this embodiment of the disclosure, a mobile monitoring platform can be used to collect the concentration of the indicator, or other equipment can be used for collection. This embodiment of the disclosure does not limit the scope of the collection. The geochemical characteristic score of the methane plume can characterize the correlation between the methane plume and the drainage network. The value of the geochemical characteristic score is positively correlated with the strength of this correlation.

[0087] S14. Based on the first distance between the methane plume and the nearest drainage network node, and the standard distance, determine the geographical feature score of the methane plume.

[0088] The standard distance can be a constant. It can be fitted based on historical data of the distance between the detected methane plume and the drainage network nodes, taking into account the density of the drainage network and the distance from which the methane plume dissipates. Geographic feature scores can characterize the proximity of the methane plume to the drainage network nodes.

[0089] S15, based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score, determine the plume confidence level of each methane plume.

[0090] The plume confidence score is a quantitative representation of the probability that a methane plume originates from a drainage network. In this embodiment, the plume confidence score is determined based on the methane plume's emission characteristic score, geochemical characteristic score, and geographical characteristic score. In effect, three dimensions are used to comprehensively evaluate the probability of a methane plume originating from a drainage network, enriching the evaluation indicators and making the evaluation more comprehensive and reliable. This improves the reliability and accuracy of the plume confidence score.

[0091] S16, divide the regional range data corresponding to the study area into grids to obtain multiple grids, and determine the grid confidence level corresponding to each grid based on the first location and the plume confidence level.

[0092] Regional extent data refers to electronic data reflecting the extent of the study area. The grid precision can be determined according to actual needs. In one example, the regional extent data can be divided into multiple 100m × 100m grids.

[0093] Grid confidence can be a quantitative representation of the probability that a grid contains a methane plume from a drainage network. Based on a first location, methane plumes corresponding to a grid can be selected. Using the plume confidence of these methane plumes, the grid confidence can be determined. For example, the plume confidence of the methane plumes corresponding to a grid can be multiplied together to obtain a product, and the grid confidence can be determined based on this product. The above is merely an example; the method for determining grid confidence will be described below. This disclosure does not limit the method for determining grid confidence.

[0094] S17, Based on the grid confidence level, determine the location of the methane emission source.

[0095] The grid confidence score is positively correlated with the probability that the corresponding grid contains a methane emission source. Therefore, the location of a methane emission source can be determined based on the grid confidence score. For example, drainage network nodes in grids with a confidence score higher than a preset grid confidence score threshold can be identified as methane emission sources. This is just an example; other methods will be introduced below.

[0096] In this embodiment, the methane plume identified by the mobile survey method is scored across three dimensions: emission characteristics, geochemical characteristics, and geographical characteristics. This approach fully considers influencing factors and accurately evaluates the identified methane plume's persistence, correlation with the drainage network, and proximity to drainage network nodes. This improves the accuracy and reliability of determining whether a methane plume originates from the drainage network, i.e., it enhances the accuracy and reliability of plume confidence. Furthermore, the regional data corresponding to the study area is divided into grids. Using these grids as positioning units, the entire drainage network's nodes are comprehensively covered, reducing the probability of missing nodes. Based on the first location and plume confidence, the likelihood of a grid containing a methane plume from the drainage network can be accurately determined, i.e., the grid-level confidence (grid confidence) is determined. The grid confidence is then used to indicate the methane emission source. Therefore, the method of this disclosure improves the accuracy of identifying and locating methane emission sources in the drainage network.

[0097] In one possible implementation, the methane plume includes: a continuous methane plume and a non-continuous methane plume. The step of performing multiple mobile surveys along multiple lines within the study area to determine multiple methane plumes and their initial locations includes: obtaining multiple methane concentration sequence data through the mobile surveys, the methane concentration sequence data containing multiple methane concentration values ​​and the geographic coordinates of each methane concentration value; identifying the methane plume and its original location based on the methane concentration sequence data; and determining the initial location of the continuous plume and the initial location of the non-continuous plume on each line based on the original location.

[0098] A persistent methane plume refers to the continuous or recurring emission of methane gas at a specific location. Persistent methane plumes are characterized by long-term release. A non-persistent methane plume refers to the discontinuous, intermittent, or brief release and diffusion of methane gas in the atmosphere. Non-persistent methane plumes typically do not exhibit long-term release characteristics.

[0099] Multiple methane concentration values ​​can be collected during a single mobile monitoring operation. Each methane concentration value corresponds to a specific collection time and location (geographic coordinates). The methane concentration sequence data can be obtained by arranging the methane concentration values ​​according to their collection time sequence. The methane concentration sequence data must include at least: the methane concentration value and the geographic coordinates. Multiple mobile monitoring operations along a single route can yield multiple methane concentration sequence data.

[0100] This disclosure does not limit the method for identifying methane plumes from methane concentration sequence data. For example, a dynamic moving window method can be used to process methane concentration sequence data to identify methane plumes. Hypothesis testing or unsupervised learning methods can also be used to determine methane plumes. Specific methods for identifying methane plumes are not the focus of this disclosure and will not be elaborated upon here.

[0101] For an identified methane plume, the geographic coordinates corresponding to the peak value of at least one methane concentration value can be used as the original location of the methane plume. The methane plume can be correlated with the original location.

[0102] This disclosure does not limit the determination of the first position based on the original position. Exemplarily, one of the original positions of various methane plumes that can be part of the same continuous methane plume can be used as the first position of that methane plume. The original position of a non-continuous methane plume can be directly used as its first position. Another embodiment will be used below to illustrate a method for determining the first position based on the original position.

[0103] Multiple detections of the same line may detect the same persistent methane plume. Due to the characteristics of the mobile survey method, the original location of this same persistent methane plume may be different, and there is a certain probability that a persistent methane plume will be mistakenly identified as a non-persistent methane plume. The persistence capabilities of persistent and non-persistent methane plumes differ greatly, which will affect the accuracy of the emission characteristic score of the determined methane plume. Therefore, the embodiments of this disclosure do not directly use the original location, but determine the first location based on the original location. This can improve the accuracy of the emission characteristic.

[0104] In one possible implementation, determining the first position of the continuous plume and the first position of the non-continuous plume on each of the lines based on the original position includes: clustering the methane plumes detected on each line based on the original position corresponding to each line to obtain a continuous methane plume cluster and / or a non-continuous methane plume cluster; aligning the positions of the methane plumes in the continuous methane plume cluster on the same line to obtain the first position of each methane plume in the continuous methane plume cluster; and using the original position of the methane plume in the non-continuous methane plume cluster as its first position.

[0105] Multiple mobile patrols can be performed on a single line to identify multiple methane plumes. Therefore, each line can correspond to multiple original locations.

[0106] For example, clustering can be performed based on the route, selecting either the x-coordinate of the original location, the y-coordinate, or both, to obtain at least one methane plume cluster. Clusters containing only one methane plume are defined as non-persistent methane plume clusters. Clusters containing more than one methane plume are defined as persistent methane plume clusters.

[0107] For example, a buffer zone centered on the original location can be defined. For instance, a 5-meter buffer zone can be established. That is, a single line can correspond to multiple buffer zones, each of which can correspond to a methane plume. For buffer zones corresponding to the same line, the methane plumes corresponding to buffer zones with overlapping areas are classified as persistent methane plume clusters. The methane plumes corresponding to buffer zones that do not overlap with other buffer zones are classified as non-persistent methane plume clusters.

[0108] A persistent methane plume cluster can contain multiple persistent methane plumes. A non-persistent methane plume cluster can contain one non-persistent methane plume. The original position of the non-persistent methane plume can be directly used as its first position.

[0109] For multiple persistent methane plumes within a persistent methane plume cluster, the concentration value of each persistent methane plume can be used as the first weight. The original positions corresponding to each persistent methane plume are weighted to determine the weighted position. This weighted position is the geographic coordinate corresponding to the persistent methane plume cluster. This weighted position is used as the first position of each persistent methane plume within the persistent methane plume cluster. This allows for the alignment of multiple persistent methane plumes within the persistent methane plume cluster. For ease of understanding, formula (1) is used to represent the process of determining the first position of a persistent methane plume.

[0110] (1)

[0111] in, Indicates the first position of the continuous methane plume. This indicates the original position of the j-th persistent methane plume in the persistent methane plume cluster. denoted by , represents the concentration value of the j-th persistent methane plume in the persistent methane plume cluster, and p represents the number of persistent methane plumes contained in the persistent methane plume cluster.

[0112] For continuous methane plumes, this determined first position includes the concentration information of the methane plume, and the determined first position can improve the rationality and accuracy of the plume confidence.

[0113] In this embodiment, methane plumes on the same path are clustered based on their original locations. Different strategies are used to determine the first location for persistent and non-persistent methane plume clusters, making the first locations corresponding to different types of methane plumes more reasonable and improving the rationality and accuracy of determining the plume confidence level.

[0114] In one possible implementation, determining the emission characteristic score of each methane plume includes: clustering the methane plumes detected on the same route to obtain at least one methane plume cluster; and determining the emission characteristic score of each methane plume in each methane plume cluster corresponding to the route based on the number of navigation trips on the route and the number of methane plumes in each methane plume cluster corresponding to the route.

[0115] Methane plume clusters can include: persistent methane plume clusters and non-persistent methane plume clusters. The clustering methods have been exemplarily described above and will not be repeated here. This disclosure does not limit the method of methane plume clustering.

[0116] After multiple mobile monitoring tests, if a methane plume is detected on the line, the line can correspond to at least one methane plume cluster. The number of methane plumes contained in a single methane plume cluster can reflect the persistence of the methane plumes in the cluster, and can therefore be used to determine the emission characteristic score of the methane plumes in that cluster.

[0117] For ease of understanding, the process of scoring the escape feature can be represented by formula (2).

[0118] (2)

[0119] in, This represents the emission characteristic score of each methane plume in the b-th methane plume cluster on the a-th route; This represents the number of methane plumes in the b-th methane plume cluster; This represents the number of navigation trips on the a-th route, and min() indicates that the smaller of the two values ​​in parentheses should be selected.

[0120] In this embodiment of the disclosure, the emission characteristic score of a methane plume can be determined by using the number of methane plumes in a methane plume cluster and the number of runs of the corresponding line. This not only reflects the persistence of the methane plume intuitively, but also is simple to calculate and requires little computation.

[0121] In one possible implementation, determining the geochemical characteristic score of the methane plume based on the concentration of at least one indicator detected at the methane plume includes: determining at least one indicator index based on the concentration of the at least one indicator; determining a first score corresponding to the at least one indicator index based on the relationship between the at least one indicator index and a preset threshold range; and weighting each of the first scores corresponding to the methane plume to obtain the geochemical characteristic score of the methane plume.

[0122] Indicator parameters can indicate the likelihood that a methane plume originates from a drainage network. Exemplarily, indicator parameters may include: the ratio of methane to carbon dioxide detected at the methane plume, the ratio of the amount of methane carbon-13 isotope to a standard amount, and the ratio of the amount of methane carbon-2 isotope to a standard amount. These are merely examples. Indicator parameters can be adjusted according to different indicators, and this disclosure does not limit the specific form of the indicator parameters.

[0123] In this embodiment of the disclosure, multiple threshold intervals can be pre-determined based on historical data of the indicator. The mean and standard deviation of the indicator can be calculated based on the historical data. Multiple threshold intervals are established using these mean and standard deviation, each corresponding to a first score for the indicator. The determination of the threshold intervals can be based on the values ​​of the attribution parameters of the historical data; for example, confidence intervals with attribution parameters of 99% and 95% can be determined based on the mean and standard deviation of the historical data as the threshold intervals.

[0124] Thus, when using threshold intervals, the first score corresponding to an indicator can be determined by identifying the threshold interval into which the indicator falls. A single methane plume can correspond to at least one indicator. That is, a single methane plume can correspond to at least one first score. The geochemical feature score of the plume is obtained by weighted summing of the first scores corresponding to a single plume. Here, the weights of the first scores are not limited. In one example, the weights of all first scores can be equal.

[0125] In this embodiment, the relationship between indicator indicators and threshold ranges is used to determine a first score corresponding to each indicator indicator in a hierarchical manner, and the first scores are weighted and summed to determine the geochemical feature score. This improves the accuracy of evaluating the correlation between methane plumes and drainage networks. That is, it makes the geochemical feature score more suitable for calculating plume confidence, thereby improving the reliability of plume confidence.

[0126] In one possible implementation, determining the geographic feature score of the methane plume based on a first distance and a standard distance between the methane plume and the nearest drainage network node includes: determining a first distance between the methane plume and the nearest drainage network node based on a first location of the methane plume and a second location of each drainage network node; and determining the geographic feature score based on the first distance and the standard distance.

[0127] Based on the first and second positions of the methane plume, the distances between the methane plume and each drainage network node are determined. The distance with the smallest value is determined as the first distance. The drainage network node corresponding to the smallest distance is the drainage network node closest to the methane plume.

[0128] For ease of understanding, the process of determining geographic feature scores is illustrated by using formula (3) as an example.

[0129] (3)

[0130] in, The geographic characteristic score of the methane plume is represented by d, where d represents the first distance corresponding to the methane plume. Indicates standard distance.

[0131] Using the method disclosed herein can improve the accuracy of evaluating the proximity of methane plumes to drainage networks. Specifically, it makes geographic feature scoring more suitable for calculating plume confidence levels, thereby improving the reliability of plume confidence levels.

[0132] In one possible implementation, determining the plume confidence of each methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographic characteristic score includes: determining an initial plume confidence of the methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographic characteristic score; obtaining a conflict factor if the geochemical characteristic score and the geographic characteristic score satisfy a first condition, or if the escaping characteristic score and the geochemical characteristic score satisfy a second condition; and adjusting the initial plume confidence using the conflict factor to obtain the plume confidence.

[0133] In this embodiment, the initial plume confidence score is obtained by weighted summation of the emission characteristic score, geochemical characteristic score, and geographic characteristic score corresponding to the methane plume. Weights can be assigned to the emission characteristic score, geochemical characteristic score, and geographic characteristic score according to actual conditions. The sum of the weights of each of the emission characteristic score, geochemical characteristic score, and geographic characteristic score can be 1. In practical applications, conflicts may occur among these three scores, affecting the accuracy and reliability of the plume confidence score. Therefore, a conflict factor can be used to adjust the initial plume confidence score.

[0134] The first condition can be that the geochemical feature score is not less than a first threshold, and the geographic feature score is not greater than a second threshold. The second threshold is less than the first threshold. The second condition can be that the escape feature score is not less than the first threshold, and the geochemical feature score is not greater than the second threshold.

[0135] Under the condition that either the first condition or the second condition is met, the conflict factor can take values ​​within the first threshold range. The upper limit of the first threshold range is greater than the first threshold. The lower limit of the first threshold range is greater than the second threshold but less than the first threshold.

[0136] For ease of understanding, formula (4) is used to represent the process of determining the confidence level of the plume.

[0137] (4)

[0138] Where C represents the plume confidence level of the methane plume, and k represents the conflict factor corresponding to the methane plume. This indicates the emission characteristic score corresponding to the methane plume. This indicates the geochemical feature score corresponding to the methane plume. This indicates the geographic feature score corresponding to the methane plume. The weights of the escape feature scores are indicated. This represents the weight corresponding to the geomorphic feature score. This indicates the weight corresponding to the geographic feature score.

[0139] In this embodiment, not only are the evaluation scores of multi-dimensional features fused, but also the feature scores that may conflict are adjusted, thereby improving the reliability of the plume confidence score. In this way, the plume confidence score can comprehensively and reliably reflect the relationship between the methane plume and the drainage network, making it a reliable basis for determining whether a methane plume originates from the drainage network.

[0140] In one possible implementation, dividing the regional range data corresponding to the study area into multiple grids, and determining the grid confidence level corresponding to each grid based on the first location and the plume confidence level, includes: determining the methane plume corresponding to the grid and the plume confidence level corresponding to the grid based on the first location; and determining the grid confidence level corresponding to the grid based on the plume confidence level corresponding to the grid.

[0141] In this embodiment of the disclosure, the regional data can be divided into multiple grids. Each grid can correspond to a geographic coordinate range. For each grid, a methane plume whose first location falls within the geographic coordinate range corresponding to the grid can be considered as the methane plume detected within that grid, i.e., the methane plume corresponding to that grid.

[0142] The methane plume corresponding to the grid can include persistent methane plumes and / or non-persistent methane plumes. Furthermore, the grid can correspond to a cluster of persistent methane plumes and / or a cluster of non-persistent methane plumes. Of course, a cluster of non-persistent methane plumes can contain only one non-persistent methane plume.

[0143] In this embodiment of the disclosure, a first probability can be determined based on the plume confidence of persistent methane plumes within a persistent methane plume cluster: all methane plumes within the cluster originate from the drainage network. Based on the first probabilities corresponding to each grid cell, a second probability can be determined: all persistent methane plumes within the grid cell do not originate from the drainage network. Based on the plume confidence of non-persistent methane plumes within a non-persistent methane plume cluster, a third probability can be determined: all non-persistent methane plumes within the grid cell do not originate from the drainage network. The grid confidence of the grid cell is then determined based on the second and third probabilities.

[0144] For ease of understanding, formulas (5) and (6) can be used to represent the process of determining grid confidence.

[0145] (5)

[0146] in, This represents the first probability corresponding to the k-th persistent methane plume cluster in grid g; This represents the plume confidence of the j-th persistent methane plume within the k-th persistent methane plume cluster; m indicates that the k-th persistent methane plume cluster contains a total of m persistent methane plumes.

[0147] (6)

[0148] in, This represents the grid confidence of grid g, where N represents the number of persistent methane plume clusters corresponding to that grid. This represents the plume confidence of the Lth non-persistent methane plume corresponding to this grid (or the non-persistent methane plume in the corresponding Lth non-persistent methane plume cluster), where H represents the number of non-persistent methane plumes corresponding to this grid. This represents the second probability corresponding to that grid. This represents the third probability corresponding to that grid.

[0149] Using the method disclosed herein, the probability that all methane plumes corresponding to a grid originate from a drainage network can be accurately determined, thereby improving the accuracy of grid confidence.

[0150] In one possible implementation, determining the location of the methane emission source based on the grid confidence level includes: determining a first number of navigation runs within a region defined by the grid; determining a grid confidence density based on the first number of navigation runs and the grid confidence level corresponding to the grid; determining a target grid based on the relationship between each grid confidence density and a density threshold; performing a secondary verification on the target region defined by the target grid; and determining the location of the methane emission source based on the verification results.

[0151] Multiple mobile surveys along various routes within the study area yield multiple methane concentration sequence data points. Each methane concentration sequence data point contains multiple methane concentration data points. A single methane concentration data point may include: the methane concentration value, the time the methane concentration value was collected, and the geographic coordinates. Therefore, based on the methane concentration sequence data, the first number of mobile surveys within the grid-defined area can be determined.

[0152] For example, a first quantity threshold can be preset, such as [100, 300]. The first quantity threshold can characterize the minimum number of methane concentration values ​​collected by mobile surveys of a single grid. Methane concentration sequence data with at least some geographic coordinates falling within the geographic coordinate range defined by the second target grid are identified as candidate methane concentration sequence data; and a first number of geographic coordinates falling within this geographic coordinate range is determined for each candidate methane concentration sequence data. Candidate methane concentration sequence data with a first number not less than the first quantity threshold are identified as target methane concentration sequence data. The number of target methane concentration sequence data is used as the first number of surveys corresponding to the second target grid. The second target grid can be a grid whose grid confidence density is to be determined.

[0153] For example, candidate methane concentration data are identified from each methane concentration sequence data whose geographic coordinates fall within the geographic coordinate range defined by a second target grid. Based on the time in each candidate methane concentration data, the candidate methane concentration data are clustered to obtain multiple categories. The number of categories is used as the first number of walks corresponding to the second target grid.

[0154] In this embodiment of the disclosure, the ratio of grid confidence to the number of first navigation runs can be used as the grid confidence density. This can eliminate errors caused by different navigation runs on different routes.

[0155] In this embodiment, multiple different density thresholds can be set. Grids with a grid confidence density greater than the highest density threshold value are identified as the first target grid. In one example, at least three density threshold intervals can be determined based on multiple target thresholds, each interval corresponding to a color, thereby generating a grid heatmap of the study area. Based on the color, the first target grid is identified from the grid heatmap. The first target grid has a higher probability of containing a methane emission source compared to other grids. Secondary verification can be performed in the real-world region corresponding to the first target grid; for ease of description, this region is named the defined target area range of the first target grid. The secondary verification includes at least: determining whether the target area range contains drainage network nodes and detecting the composition of the gas emitted from the drainage network nodes. If the verification result indicates that the composition of the gas emitted from the drainage network nodes in the grid matches the composition of the methane plume corresponding to that grid, then the drainage network nodes in that grid can be identified as the methane emission source of the methane plume corresponding to that grid. The methane plume corresponding to the grid can be the methane plume falling into the grid at the first location.

[0156] In this embodiment, the first target grid is determined based on the grid confidence density, and secondary verification is performed to improve the accuracy and reliability of methane plume source tracing. Furthermore, compared to direct on-site investigation-based source tracing, it saves significant time and improves tracing efficiency.

[0157] Figure 2 This is a schematic diagram of the methane emission source determination device provided in an embodiment of this disclosure. Figure 2 As shown, the device 20 includes:

[0158] The first position determination unit 21 is used to perform multiple mobile surveys on multiple lines within the study area to determine multiple methane plumes and the first position of the methane plumes.

[0159] Emission characteristic score determination unit 22 is used to determine the emission characteristic score of each methane plume;

[0160] Geochemical feature scoring determination unit 23 is used to determine the geochemical feature score of the methane plume based on the concentration of at least one indicator detected at the methane plume.

[0161] The geographic feature scoring determination unit 24 is used to determine the geographic feature score of the methane plume based on the first distance and the standard distance between the methane plume and the nearest drainage network node.

[0162] The plume confidence determination unit 25 is used to determine the plume confidence of each methane plume based on the escaping characteristic score, the geochemical characteristic score, and the geographical characteristic score.

[0163] The grid confidence determination unit 26 is used to divide the regional range data corresponding to the study area into grids to obtain multiple grids, and determine the grid confidence corresponding to each grid based on the first location and the plume confidence.

[0164] The methane emission source location determination unit 27 is used to determine the location of the methane emission source based on the grid confidence level.

[0165] In one possible implementation, the methane plume includes: a continuous methane plume and a non-continuous methane plume, and the first position determination unit 21 is further configured to:

[0166] Through the mobile survey, multiple methane concentration sequence data can be obtained. The methane concentration sequence data includes multiple methane concentration values ​​and the geographic coordinates of each methane concentration value.

[0167] Based on the methane concentration sequence data, the methane plume and its original location were identified.

[0168] Based on the original positions, the first positions of the continuous plumes and the first positions of the non-continuous plumes on each of the lines are determined.

[0169] In one possible implementation, the first position determining unit 21 is further configured to:

[0170] Based on the original positions corresponding to each of the lines, the methane plumes detected on each of the lines are clustered to obtain persistent methane plume clusters and / or non-persistent methane plume clusters.

[0171] Align the positions of the methane plumes in the continuous methane plume clusters on the same line to obtain the first position of each methane plume in the continuous methane plume cluster.

[0172] The original position of the methane plume in the non-persistent methane plume cluster is taken as its first position.

[0173] In one possible implementation, the evaporation characteristic scoring and determining unit 22 is further configured to:

[0174] Clustering of methane plumes detected on the same line yields at least one methane plume cluster.

[0175] Based on the number of navigation trips on the route and the number of methane plumes in each methane plume cluster corresponding to the route, the emission characteristic score of each methane plume in each methane plume cluster corresponding to the route is determined.

[0176] In one possible implementation, the geomorphic feature scoring determination unit 23 is further configured to:

[0177] Based on the concentration of the at least one indicator, at least one indicator index is determined;

[0178] Based on the relationship between the at least one indicator and a preset threshold range, a first score corresponding to the at least one indicator is determined;

[0179] The geochemical characteristic score of the methane plume is obtained by weighting each of the first scores corresponding to the methane plume.

[0180] In one possible implementation, the geographic feature scoring and determination unit 24 is further configured to:

[0181] Based on the first position of the methane plume and the second positions of each of the drainage network nodes, the first distance between the methane plume and the nearest drainage network node is determined.

[0182] The geographic feature score is determined based on the first distance and the standard distance.

[0183] In one possible implementation, the plume confidence determination unit 25 is further configured to:

[0184] Based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score, the initial plume confidence level of the methane plume is determined;

[0185] If the geochemical feature score and the geographic feature score satisfy the first condition, or if the escaping feature score and the geochemical feature score satisfy the second condition, a conflict factor is obtained.

[0186] The initial plume confidence level is adjusted using the conflict factor to obtain the plume confidence level.

[0187] In one possible implementation, the grid confidence determination unit 26 is further configured to:

[0188] Based on the first location, determine the methane plume corresponding to the grid and the plume confidence level corresponding to the grid;

[0189] The grid confidence level is determined based on the plume confidence level corresponding to the grid.

[0190] In one possible implementation, the methane escaping source location determination unit 27 is further configured to:

[0191] Determine the first number of walks within the area defined by the grid;

[0192] The grid confidence density is determined based on the first number of navigation trips and the grid confidence corresponding to the grid.

[0193] Based on the relationship between the confidence density and the density threshold of each grid, the first target grid is determined;

[0194] A second verification is performed on the target area defined by the first target grid, and the location of the methane emission source is determined based on the verification results.

[0195] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0196] This disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0197] This disclosure also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0198] This disclosure also provides a computer program product, including a computer program or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program, when executed by a processor, implements the steps of the above method.

[0199] Figure 3 This is a schematic diagram of an electronic device for determining a methane emission source, provided as an embodiment of this disclosure. For example, device 1900 can be provided as a server or terminal device. (Refer to...) Figure 3 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0200] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output interface 1958 (I / O interface). Device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM macOS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0201] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0202] Computer-readable storage media can be tangible devices capable of holding and storing programs / instructions used by instruction execution devices. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0203] The computer program (or computer-readable program instructions) described herein can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage medium in the respective computing / processing device.

[0204] The computer program (or computer program instructions) used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions to implement various aspects of this disclosure.

[0205] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0206] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0207] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0208] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0209] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining a methane emission source, characterized in that, include: Multiple mobile surveys were conducted along multiple lines within the study area to determine multiple methane plumes and their first locations. Determine the emission characteristic score for each of the methane plumes; A geochemical characterization score of the methane plume is determined based on the concentration of at least one indicator detected at the methane plume. The geographical feature score of the methane plume is determined based on the first distance and the standard distance between the methane plume and the nearest drainage network node. Based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score, the plume confidence level of each methane plume is determined; The regional data corresponding to the study area is divided into grids to obtain multiple grids. Based on the first location and the plume confidence, the grid confidence corresponding to each grid is determined. Based on the grid confidence level, the location of the methane emission source is determined.

2. The method according to claim 1, characterized in that, The methane plume includes: continuous methane plume and non-continuous methane plume. The step of performing multiple mobile surveys along multiple lines within the study area to determine multiple methane plumes and their initial locations includes: Through the mobile survey, multiple methane concentration sequence data can be obtained. The methane concentration sequence data includes multiple methane concentration values ​​and the geographic coordinates of each methane concentration value. Based on the methane concentration sequence data, the methane plume and its original location were identified. Based on the original positions, the first positions of the continuous plumes and the first positions of the non-continuous plumes on each of the lines are determined.

3. The method according to claim 2, characterized in that, The step of determining the first position of the continuous plume and the first position of the non-continuous plume on each of the aforementioned lines based on the original position includes: Based on the original positions corresponding to each of the lines, the methane plumes detected on each of the lines are clustered to obtain persistent methane plume clusters and / or non-persistent methane plume clusters. Align the positions of the methane plumes in the continuous methane plume clusters on the same line to obtain the first position of each methane plume in the continuous methane plume cluster. The original position of the methane plume in the non-persistent methane plume cluster is taken as its first position.

4. The method according to claim 1, characterized in that, The determination of the emission characteristic score for each of the methane plumes includes: Clustering of methane plumes detected on the same line yields at least one methane plume cluster. Based on the number of navigation trips on the route and the number of methane plumes in each methane plume cluster corresponding to the route, the emission characteristic score of each methane plume in each methane plume cluster corresponding to the route is determined.

5. The method according to claim 1, characterized in that, The determination of the geochemical characterization score of the methane plume based on the concentration of at least one indicator detected at the methane plume includes: Based on the concentration of the at least one indicator, at least one indicator index is determined; Based on the relationship between the at least one indicator and a preset threshold range, a first score corresponding to the at least one indicator is determined; The geochemical characteristic score of the methane plume is obtained by weighting each of the first scores corresponding to the methane plume.

6. The method according to claim 1, characterized in that, The determination of the geographical feature score of the methane plume based on the first distance and standard distance between the methane plume and the nearest drainage network node includes: Based on the first position of the methane plume and the second positions of each of the drainage network nodes, the first distance between the methane plume and the nearest drainage network node is determined. The geographic feature score is determined based on the first distance and the standard distance.

7. The method according to claim 1, characterized in that, The determination of the plume confidence level for each methane plume based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score includes: Based on the emission characteristic score, the geochemical characteristic score, and the geographical characteristic score, the initial plume confidence level of the methane plume is determined; If the geochemical feature score and the geographic feature score satisfy the first condition, or if the escaping feature score and the geochemical feature score satisfy the second condition, a conflict factor is obtained. The initial plume confidence level is adjusted using the conflict factor to obtain the plume confidence level.

8. The method according to claim 1, characterized in that, The step of dividing the regional data corresponding to the study area into multiple grids, and determining the grid confidence level corresponding to each grid based on the first location and the plume confidence level, includes: Based on the first location, determine the methane plume corresponding to the grid and the plume confidence level corresponding to the grid; The grid confidence level is determined based on the plume confidence level corresponding to the grid.

9. The method according to claim 1, characterized in that, Determining the location of the methane emission source based on the grid confidence level includes: Determine the first number of walks within the area defined by the grid; The grid confidence density is determined based on the first number of navigation trips and the grid confidence corresponding to the grid. Based on the relationship between the confidence density and the density threshold of each grid, the first target grid is determined; A second verification is performed on the target area defined by the first target grid, and the location of the methane emission source is determined based on the verification results.

10. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

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