Method for determining a gas leakage area, electronic device and program product
By collecting and analyzing time-domain seismic data of seabed gas leakage areas, the root mean square amplitude and coherence value of the target point are determined, solving the problems of low accuracy and efficiency in existing technologies, and realizing efficient and low-cost leakage point identification.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU MARINE GEOLOGICAL SURVEY
- Filing Date
- 2026-05-07
- Publication Date
- 2026-07-14
Smart Images
Figure CN122386375A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of oil and gas hydrate exploration technology, and in particular to a method, electronic equipment and program product for determining gas leakage areas. Background Technology
[0002] Long-term leakage of gas from the seabed can have significant impacts on the environment and human activities. For example, large-scale release of methane from the seabed may exacerbate global warming. At the same time, seabed methane leakage is an important indicator in the exploration of natural gas hydrate resources.
[0003] In related technologies, the location of seabed gas leaks is mainly determined by identifying acoustic anomalies in the collected data. However, on the one hand, this requires technicians to process and analyze each acoustic anomaly individually, increasing their workload and labor costs. On the other hand, sonar and water body detection technologies can only identify relatively active leaks that are currently leaking gas. Therefore, these technologies still struggle to identify some weak or intermittent seabed leaks, affecting the accuracy and efficiency of seabed leak identification. Summary of the Invention
[0004] This invention provides a method, electronic device, and program product for determining gas leakage areas, in order to solve the technical problems of low efficiency and insufficient accuracy in identifying seabed gas leakage points in related technologies.
[0005] According to one aspect of the present invention, a method for determining a gas leakage area is provided, the method comprising: Multiple target observation areas are determined from the target area, and time-domain seismic data of multiple data sampling points in each target observation area are collected; For a single data sampling point, the average root mean square amplitude value of the target point in the direction of the target main survey line is determined based on the time-domain seismic data of the data sampling point, and the coherence value and total amplitude value of the target point are determined, wherein the target point includes the target main survey line and the target connecting survey line; Based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points, the gas leakage identification result for each target observation area is determined.
[0006] According to another aspect of the present invention, an apparatus for determining a gas leakage area is provided, the apparatus comprising: The seismic data acquisition module is used to determine multiple target observation areas from the target area and acquire time-domain seismic data from multiple data sampling points in each target observation area; The seismic data processing module is used to determine, for a single data sampling point, the average root mean square amplitude value of the target point in the direction of the target main survey line based on the time-domain seismic data of the data sampling point, and to determine the coherence value and total amplitude value of the target point, wherein the target point includes the target main survey line and the target connecting survey line; The gas leakage determination module is used to determine the gas leakage identification result of each of the target observation areas based on the average root mean square amplitude value, the coherence value and the total amplitude value of multiple target points.
[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: One or more processors; and a memory communicatively connected to at least one of the processors; wherein the memory stores a computer program executable by at least one of the processors, which, when executed by one or more of the processors, causes one or more of the processors to implement a method for determining a gas leakage area as described in any one of claims 1-8.
[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement a method for determining a gas leakage area as described in any one of claims 1-8.
[0009] According to another aspect of the present invention, embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements a method for determining a gas leakage area as described in any one of claims 1-8.
[0010] The technical solution of this invention firstly identifies multiple target observation areas from the target region and collects time-domain seismic data from multiple data sampling points in each target observation area. By collecting seismic data at different depths in multiple observation areas, multi-level data interpretation and analysis are performed based on a relatively small amount of data, ensuring the comprehensive reliability of the analysis and interpretation of the observation area. Secondly, for a single data sampling point, the average root mean square amplitude value of the target point corresponding to the data sampling point in the direction of the target main survey line is determined based on the time-domain seismic data of the data sampling point. Furthermore, the coherence value and total amplitude value of the target point are determined, where the target point includes the target main survey line and the target connecting survey line. Attribute information is extracted from the time-domain seismic data, thereby performing multi-dimensional joint analysis of the observation area based on the target attribute information. This effectively reduces the amount of data processing and improves the reliability and accuracy of the data interpretation of the observation area. Finally, based on the average root mean square amplitude, coherence value, and total amplitude value of multiple target points, the gas leak identification result for each target observation area is determined. Through the fusion analysis of multi-dimensional attribute information, the accuracy, sensitivity, and spatial resolution capability of identifying gas leak points in the observation area are effectively improved. Therefore, in summary, this technical solution can perform batch and rapid detection and analysis of target points in the observation area based on a relatively small amount of seismic data, achieving efficient, low-cost, repeatable, accurate, and reliable gas leak point identification and detection.
[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description
[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0013] Figure 1 This is a flowchart of a method for determining a gas leakage area according to Embodiment 1 of the present invention; Figure 2A This is a flowchart of a method for determining a gas leakage area according to Embodiment 2 of the present invention; Figure 2B This is a schematic diagram illustrating the determination of the root mean square amplitude threshold in a method for determining a gas leakage area according to Embodiment 2 of the present invention. Figure 2CThis is a schematic diagram illustrating the determination of the coherence threshold and the total amplitude threshold in a method for determining a gas leakage area according to Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of a device for determining a gas leakage area according to Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the method for determining a gas leakage area provided in Embodiment 4 of the present invention. Detailed Implementation
[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0015] It should be noted that the terms "first preset quantity," "second preset quantity," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0016] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0017] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0018] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.
[0019] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.
[0020] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.
[0021] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.
[0022] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.
[0023] Example 1 Figure 1 This is a flowchart illustrating a method for determining a gas leak area according to Embodiment 1 of the present invention. This embodiment is applicable to scenarios involving the detection of gas leak points on the seabed. The method can be executed by a device for determining gas leak areas. This device can be implemented in hardware and / or software, optionally through electronic devices such as mobile terminals, PCs, or servers. Figure 1 As shown, the method may specifically include: S110. Determine multiple target observation areas from the target area, and collect time-domain seismic data from multiple data sampling points in each target observation area.
[0024] In this context, the target area can be understood as a large seabed area for gas leak detection; for example, the target area may include the sea area of a certain region. The target observation area can be understood as a small, localized area delineated from the target area. Data sampling points can be understood as data acquisition points for acquiring seismic data. Time-domain seismic data can be understood as seismic data acquired from relatively shallow strata; for example, time-domain seismic data may be seismic data from strata between 0 and 100 milliseconds (ms).
[0025] Specifically, attribute analysis can be performed on the target area to identify multiple representative geological target observation areas. For a single target observation area, multiple data sampling points can be determined by deploying a regular grid. By setting seismic sources and receivers at the data sampling points, time-domain seismic data within a preset time range can be collected. By adopting the above method, seismic data within the target time range can be collected in a regular and repeatable manner, thereby improving the accuracy of subsequent analysis of gas leakage points.
[0026] Furthermore, this technical solution can also be applied in areas where seismic data acquisition has already been completed. By identifying target observation areas within target areas that already possess seismic data, and acquiring seismic data within each target observation area, data analysis and processing can be performed directly on the seismic data in the target observation areas without the need for further dedicated seismic data acquisition operations. This enables more efficient and convenient gas leak identification and detection.
[0027] S120. For a single data sampling point, determine the average root mean square amplitude value of the target point in the direction of the target main survey line based on the time-domain seismic data of the data sampling point, and determine the coherence value and total amplitude value of the target point, wherein the target point includes the target main survey line and the target connecting survey line.
[0028] In this context, the target point can be understood as a specific underground coordinate location determined jointly by the target master survey line and the target connecting survey line in the 3D data volume. The target master survey line can be understood as an index along the main direction of seismic acquisition. The target connecting survey line is an index perpendicular to the target master survey line. The average root mean square amplitude can be understood as the average energy intensity of the seismic wave at the target point. The coherence value can be understood as the amount of data used to assess the similarity between geological structures near the target point, which can be calculated based on the waveform similarity between adjacent seismic traces. The total amplitude value can be understood as the sum of the absolute amplitude values corresponding to multiple sampling points within a short time window, centered on the target point and determined along the time axis or stratigraphic level. It should be further noted that the root mean square amplitude value, coherence value, and total amplitude value are all attribute data obtained from the analysis of seismic data. They can be obtained using any seismic data interpretation software by setting certain analytical parameters; this technical solution does not impose any limitations on this.
[0029] Specifically, a three-dimensional data volume is determined based on the time-domain seismic data of the sampling points. The target location is then determined based on this three-dimensional data volume, and the average root-mean-square amplitude of the target location along the main seismic line is calculated using the data within the three-dimensional data volume. Furthermore, coherence analysis can be performed on multiple seismic channels around the target location using the time-domain seismic data to calculate the coherence value of the target location. Additionally, amplitude data from multiple sampling points temporally adjacent to the target location can be determined based on the time-domain seismic data, and the total amplitude value is calculated based on the absolute values of the amplitudes from these multiple sampling points. By analyzing the time-domain seismic data, quantitative indicators at the target location can be accurately obtained, thereby improving the spatial resolution capability of gas leakage points and enhancing the reliability of seafloor stratigraphic data analysis.
[0030] Furthermore, the methods for determining the coherence value and total amplitude value of the target point can also include other implementation methods. This technical solution does not limit these methods, and the coherence value and total amplitude value of the target point can be calculated by any other method.
[0031] In one embodiment, determining the average root mean square amplitude value of the target point in the direction of the target main seismic line based on the time-domain seismic data of the data sampling point includes: generating a three-dimensional data volume based on the time-domain seismic data, the three-dimensional data volume including multiple main seismic lines and multiple connecting seismic lines, the main seismic lines and the connecting seismic lines being perpendicular to each other; determining the target point based on the three-dimensional data volume; obtaining the root mean square amplitude values of the target point on multiple reference connecting seismic lines in the direction of the target connecting seismic line; and determining the average root mean square amplitude value of the target point in the direction of the target main seismic line based on the root mean square amplitude values of the multiple reference connecting seismic lines.
[0032] The three-dimensional data volume can be understood as a regular three-dimensional grid data formed by arranging the seismic amplitudes at each point in three-dimensional space, or a data cube formed by arranging multiple seismic traces according to spatial coordinates. Reference connecting lines can be understood as other connecting lines adjacent to or within a certain range of the original connecting line. The root mean square amplitude value can be understood as the amplitude data obtained by squaring the amplitude values over a time window, taking the average, and then taking the square root.
[0033] Specifically, time-domain seismic data can be arranged according to preset three-dimensional spatial rules to generate a three-dimensional data volume. This three-dimensional data volume can include multiple main seismic lines and connecting seismic lines, which are perpendicular to each other. A target point is determined from the three-dimensional data volume based on the main seismic lines and connecting seismic lines, and the root mean square (RMS) amplitude values of multiple reference connecting seismic lines adjacent to the target point along the target connecting seismic line direction are determined. Therefore, the average RMS amplitude value of the target point along the target main seismic line direction is determined based on the RMS amplitude values corresponding to the multiple reference connecting seismic lines. This technical solution extracts the RMS amplitude values of multiple connecting seismic lines adjacent to the target point, thereby improving the stability of the calculation of the average RMS amplitude value of the target point based on the amplitude data of multiple connecting seismic lines, and better reflecting the gas leakage situation at the location of the main seismic line.
[0034] In another embodiment, determining the average root mean square amplitude value of the target point along the target main survey line direction based on the root mean square amplitude values of the plurality of reference connection survey lines includes: ; in, This represents the average root mean square amplitude of the target point along the main survey line. For the first The root mean square amplitude value of the reference connection line. This represents the total number of reference connection survey lines used to calculate the average root mean square amplitude. The difference in the number of communication survey lines between the target communication survey line and the furthest reference communication survey line. This represents the number of connection survey lines corresponding to the target connection survey line at the target location.
[0035] S130. Based on the average root mean square amplitude value, the coherence value, and the total amplitude value of the multiple target points, determine the gas leakage identification result for each target observation area.
[0036] The gas leak identification result can be understood as a determination of whether a gas leak exists in the target observation area. It can include no leak or a leak. It can also include at least one of the following: active leak, dormant leak, and potential leak. An active leak can be understood as a gas leak that is currently occurring; a dormant leak can be understood as a gas leak that has occurred in the past but has not occurred at present; a potential leak can be understood as no signs of leakage at present, but there is a significant risk of leakage.
[0037] Specifically, the average root mean square amplitude, coherence value, and total amplitude value of multiple target points in each target observation area can be compared and analyzed with preset threshold data to determine the gas leakage status of that target observation area. Furthermore, this method can be used to analyze and process each observation area to determine the gas leakage status of each target observation area. This technical solution, through comprehensive analysis integrating multi-dimensional attribute information, can improve the detection and identification capabilities of hidden leaks, achieve early risk warnings, reduce the false positive rate of gas leakage, and enhance the reliability of the final judgment results.
[0038] Furthermore, if leakage exists in the target observation area, the leakage activity of the target observation area can be determined based on the average root mean square amplitude value, the coherence value, and the total amplitude value of the target point, so as to determine the specific situation of gas leakage.
[0039] In some embodiments, before determining the gas leakage identification result of each target observation area based on the average root mean square amplitude value, the coherence value, and the total amplitude value of the plurality of target points, the method further includes: normalizing the average root mean square amplitude value, the coherence value, and the total amplitude value of the plurality of target points.
[0040] Specifically, before detecting and identifying gas leaks in the target observation area, the average root mean square amplitude, coherence value, and total amplitude value corresponding to multiple target points can be normalized. This normalizes parameters of different magnitudes into quantitative data of the same magnitude, which facilitates data matching and comparison and effectively improves the efficiency of data processing.
[0041] The technical solution of this invention firstly identifies multiple target observation areas from the target region and collects time-domain seismic data from multiple data sampling points in each target observation area. By collecting seismic data at different depths in multiple observation areas, multi-level data interpretation and analysis are performed based on a relatively small amount of data, ensuring the comprehensive reliability of the analysis and interpretation of the observation area. Secondly, for a single data sampling point, the average root mean square amplitude value of the target point corresponding to the data sampling point in the direction of the target main survey line is determined based on the time-domain seismic data of the data sampling point. Furthermore, the coherence value and total amplitude value of the target point are determined, where the target point includes the target main survey line and the target connecting survey line. Attribute information is extracted from the time-domain seismic data, thereby performing multi-dimensional joint analysis of the observation area based on the target attribute information. This effectively reduces the amount of data processing and improves the reliability and accuracy of the data interpretation of the observation area. Finally, based on the average root mean square amplitude, coherence value, and total amplitude value of multiple target points, the gas leak identification result for each target observation area is determined. Through the fusion analysis of multi-dimensional attribute information, the accuracy, sensitivity, and spatial resolution capability of identifying gas leak points in the observation area are effectively improved. Therefore, in summary, this technical solution can perform batch and rapid detection and analysis of target points in the observation area based on a relatively small amount of seismic data, achieving efficient, low-cost, repeatable, accurate, and reliable gas leak point identification and detection.
[0042] Example 2 Figure 2A This is a flowchart of a method for determining a gas leakage area according to Embodiment 2 of the present invention. This embodiment is a refinement of the technical solution of "determining the gas leakage identification result of each target observation area based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points" based on the above embodiments. Specific implementation details can be found in the description of this embodiment. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here. Figure 2A As shown, the method may specifically include: S210. Identify multiple target observation areas from the target area, and collect time-domain seismic data from multiple data sampling points in each target observation area.
[0043] S220. For a single data sampling point, determine the average root mean square amplitude value of the target point in the direction of the target main survey line based on the time-domain seismic data of the data sampling point, and determine the coherence value and total amplitude value of the target point, wherein the target point includes the target main survey line and the target connecting survey line.
[0044] S230. If the average root mean square amplitude value of multiple target points satisfies the first condition, the target observation area is determined as a candidate area.
[0045] The first condition can be understood as the quantity or proportion that multiple average root mean square amplitude values need to satisfy with respect to a preset root mean square amplitude threshold. For example, the first condition could be that a certain number of target points are all greater than the root mean square amplitude threshold. The candidate region can be understood as the observation region that satisfies the first condition.
[0046] Specifically, the average root mean square amplitude values of multiple target points can be compared with the root mean square amplitude threshold in the first condition, and the number of target points with average root mean square amplitude values greater than the threshold can be determined. Thus, when the quantity or proportion conditions set in the first condition are met, the target observation area is determined as a candidate area. In this way, each candidate area can be determined more flexibly and conveniently, and the efficiency of candidate area determination is improved based on the relatively simple and clear threshold comparison.
[0047] In some implementations, determining the target observation area as a candidate area when the average root mean square amplitude values of multiple target points meet a first condition includes: determining the target observation area as a candidate area when the average root mean square amplitude values of a first preset number of target points are greater than a root mean square amplitude threshold; or, determining the target observation area as a candidate area when the average root mean square amplitude values of a first preset proportion of target points are greater than a root mean square amplitude threshold.
[0048] The first preset quantity can be understood as the number of target points that meet the root mean square amplitude threshold when the observation area is determined as a candidate area. The first preset proportion can be understood as the proportion of target points that meet the root mean square amplitude threshold to the total number of target points when the observation area is determined as a candidate area.
[0049] Specifically, the average root mean square (RMS) amplitude values of multiple target points can be compared with an RMS amplitude threshold. If the average RMS amplitude value of a first preset number of target points is greater than the RMS amplitude threshold, the target observation area is identified as a candidate area. If the average RMS amplitude value of a first preset proportion of target points is greater than the RMS amplitude threshold, the target observation area is also identified as a candidate area. This allows for low-cost, high-efficiency, and scalable leakage area screening based on average RMS amplitude, effectively improving the efficiency of gas leakage detection in the observation area.
[0050] S240. If the coherence value and the total amplitude value of multiple target points in the candidate region satisfy the second condition, it is determined that there is gas leakage in the candidate region.
[0051] The second condition can be understood as the quantity or proportion condition that needs to be satisfied between the coherence value, total amplitude value and corresponding threshold of multiple target points in the candidate region.
[0052] Specifically, the coherence values and total amplitude values of multiple target points in the candidate region can be compared with their corresponding thresholds to identify multiple target points that meet the threshold conditions. When the number or proportion of these multiple target points among all target points in the candidate region reaches a set condition, gas leakage is determined to exist in the candidate region. By employing a fusion comparative analysis of coherence values and total amplitude values, multiple detection verifications of seabed leakage areas can be performed, effectively improving the reliability and geological interpretability of gas leakage detection results.
[0053] In some implementations, determining that a gas leak exists in a candidate region when the coherence value and the total amplitude value of multiple target points in the candidate region meet a second condition includes: identifying target points in the candidate region whose coherence value is greater than a coherence threshold and whose total amplitude value is greater than a total amplitude threshold as target identification points; determining that a gas leak exists in a candidate region when the number of target identification points reaches a second preset number; or determining that a gas leak exists in a candidate region when the proportion of target identification points to all target points reaches a second preset proportion.
[0054] Here, the target identification point can be understood as the target point in the candidate region that simultaneously meets the coherence threshold and the predicted total amplitude. The second preset quantity can be understood as the quantity condition that needs to be met when the observation area is determined to have a gas leak. The second preset ratio can be understood as the proportion of the target identification point to the total number of target points when the observation area is determined to have a gas leak.
[0055] Specifically, the coherence values of multiple target points in the candidate region can be compared with a coherence threshold, and the total amplitude value can be compared with a total amplitude threshold. Target points that simultaneously exceed both the coherence threshold and the total amplitude threshold are then identified as target identification points. Furthermore, a gas leak can be determined to exist in the candidate region if the number of target identification points reaches a second preset number, or if the proportion of target identification points to all target points reaches a second preset proportion. By employing a fusion comparison analysis of coherence values and total amplitude values, multiple detection and verification of seabed leak areas can be performed, effectively improving the reliability and geological interpretability of gas leak detection results.
[0056] In some implementations, the method further includes at least one of the following: obtaining reference average root mean square amplitude values for a plurality of reference points in the target area where gas leaks are known to exist, and determining the lowest reference average root mean square amplitude value among the plurality of reference points as a root mean square amplitude threshold; obtaining reference coherence values for a plurality of reference points in the target area where gas leaks are known to exist, and determining the lowest reference coherence value among the plurality of reference points as a coherence threshold; obtaining reference total amplitude values for a plurality of reference points in the target area where gas leaks are known to exist, and determining the lowest reference total amplitude value among the plurality of reference points as a total amplitude value threshold.
[0057] Specifically, multiple known first reference points without gas leaks and second reference points with gas leaks can be obtained from the target area. Multiple reference average root-mean-square (RMMS) amplitude values for the first and second reference points are acquired, and these are compared with the reference average RMS amplitude values corresponding to the first and second reference points without gas leaks. The lowest value among the reference average RMS amplitude values for the second reference point with gas leaks is taken as the lowest reference average RMS amplitude value and determined as the RMS amplitude threshold. Similarly, multiple reference coherence values for the first and second reference points can be acquired, and these values are compared with the reference coherence values corresponding to the first and second reference points without gas leaks. The relatively lower reference coherence value among the reference coherence values for the second reference point with gas leaks is taken as the lowest reference coherence value and determined as the coherence threshold. Furthermore, the reference total amplitude values of the first and second reference points are obtained, and the reference total amplitude values corresponding to the first reference point without gas leakage and the second reference point with gas leakage are compared. The lowest reference total amplitude value among all reference total amplitude values at the second reference point with gas leakage is then used as the minimum reference total amplitude value and determined as the total amplitude threshold. By comparing and analyzing the extracted attribute data of the gas leakage area with that of the non-gas leakage area, and using the relatively lower attribute data in the gas leakage area as the corresponding threshold data, the convenience and reliability of threshold determination are ensured, and the accuracy of the screening threshold is guaranteed.
[0058] Furthermore, the method of determining the root mean square amplitude threshold, coherence threshold, and total amplitude threshold based on multiple known first reference points where there is no gas leakage and second reference points where there is gas leakage can also be as follows: Figure 2B and Figure 2C As shown, specifically, in Figure 2BThe data includes reference average root-mean-square amplitude values for multiple stations without gas leaks (first reference points) and reference average root-mean-square amplitude values for stations with gas leaks (second reference points). By comparing the multiple reference average root-mean-square amplitude values included at the multiple second reference points with gas leaks, the lowest value of 0.33 among the multiple reference average root-mean-square amplitude values at the second reference points can be taken as the lowest reference average root-mean-square amplitude value and used as the root-mean-square amplitude threshold. Furthermore, in... Figure 2C The data includes reference coherence values and total amplitude values corresponding to multiple first reference points where there is no gas leakage, and reference coherence values and total amplitude values corresponding to second reference points where there is gas leakage. By comparing the multiple reference coherence values and total amplitude values at the second reference points where there is gas leakage, 0.22 is selected as the lowest reference coherence value and used as the coherence threshold; similarly, 0.34 is selected as the lowest reference total amplitude value and used as the total amplitude threshold. By comparing the data from reference points with and without gas leakage, relatively reliable threshold data can be established, effectively improving the accuracy of identifying and detecting gas leakage in the target area.
[0059] Furthermore, in this technical solution, the target threshold data can be determined based on the reference average root-mean-square amplitude value, reference coherence value, and reference total amplitude value of multiple second reference points where gas leakage exists. For example, it is feasible to calculate the average reference average root-mean-square amplitude value based on a relatively small number of preset reference average root-mean-square amplitude values, and use this as the root-mean-square amplitude threshold. Alternatively, one of the multiple reference average root-mean-square amplitude values can be directly selected as the root-mean-square amplitude threshold. Determining the root-mean-square amplitude threshold through reasonable methods is acceptable, and this technical solution does not impose further limitations on this. Simultaneously, the methods for determining the coherence threshold and the total amplitude value threshold can be similar to or the same as the method for determining the root-mean-square amplitude threshold, and this technical solution does not impose specific limitations on this either. This technical solution can determine the target observation area as a candidate area when the average root-mean-square amplitude values of multiple target points meet a first condition; and determine that gas leakage exists in the candidate area when the coherence value and the total amplitude value of multiple target points in the candidate area meet a second condition. Therefore, this technical solution effectively improves the accuracy and reliability of gas leakage area detection by matching and analyzing different attribute data with preset conditions, thereby realizing the batch and efficient identification and detection of seabed leakage points.
[0060] Example 3 Figure 3This is a schematic diagram of a device for determining a gas leakage area according to Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a seismic data acquisition module 301, a seismic data processing module 302, and a gas leakage determination module 303.
[0061] The seismic data acquisition module 301 is used to determine multiple target observation areas from the target area and acquire time-domain seismic data from multiple data sampling points in each target observation area; the seismic data processing module 302 is used to determine, for a single data sampling point, the average root mean square amplitude value of the target point in the direction of the target main survey line based on the time-domain seismic data of the data sampling point, and to determine the coherence value and total amplitude value of the target point, wherein the target point includes the target main survey line and the target connecting survey line; the gas leakage determination module 303 is used to determine the gas leakage identification result of each target observation area based on the average root mean square amplitude value, the coherence value and the total amplitude value of the multiple target points.
[0062] The technical solution of this invention involves the following steps: First, the seismic data acquisition module 301 identifies multiple target observation areas from the target region and acquires time-domain seismic data from multiple data sampling points in each target observation area. By acquiring seismic data at different depths in multiple observation areas, multi-level data interpretation and analysis are performed based on a relatively small amount of data, ensuring the comprehensive reliability of the analysis and interpretation of the observation area. Second, for a single data sampling point, the seismic data processing module 302 determines the average root mean square amplitude value of the target point in the direction of the target main survey line based on the time-domain seismic data of the data sampling point, and determines the coherence value and total amplitude value of the target point. The target point includes the target main survey line and the target connecting survey line. Attribute information is extracted based on the time-domain seismic data, thereby performing multi-dimensional joint analysis of the observation area based on the target attribute information, effectively reducing the amount of data processing and improving the reliability and accuracy of the data interpretation of the observation area. Finally, the gas leak determination module 303 determines the gas leak identification result for each target observation area based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points. Through the fusion analysis of multi-dimensional attribute information, the accuracy, sensitivity, and spatial resolution capability of identifying gas leak points in the observation area are effectively improved. Therefore, in summary, this technical solution can perform batch and rapid detection and analysis of target points in the observation area based on a relatively small amount of seismic data, achieving efficient, low-cost, repeatable, accurate, and reliable gas leak point identification and detection.
[0063] Based on the above-mentioned optional technical solutions, the gas leakage determination module 303 may optionally include: a first matching module and a second matching module. The first matching module is used to determine the target observation area as a candidate area when the average root mean square amplitude values of multiple target points meet a first condition; the second matching module is used to determine that gas leakage exists in the candidate area when the coherence value and the total amplitude value of multiple target points in the candidate area meet a second condition.
[0064] Based on the above-mentioned optional technical solutions, the first matching module may optionally include: a first candidate region determining unit and a second candidate region determining unit. The first candidate region determining unit is used to determine the target observation region as a candidate region when the average root mean square amplitude value of a first preset number of target points is greater than a root mean square amplitude threshold; the second candidate region determining unit is used to determine the target observation region as a candidate region when the average root mean square amplitude value of a first preset proportion of target points is greater than a root mean square amplitude threshold.
[0065] Based on the above-mentioned optional technical solutions, the second matching module may optionally include: a target identification point determination unit and a gas leakage area determination unit. The target identification point determination unit is used to determine the target points in the candidate region whose coherence values are greater than a coherence threshold and whose total amplitude values are greater than a total amplitude threshold as target identification points. The gas leakage area determination unit is used to determine that a gas leakage exists in the candidate region when the number of target identification points reaches a second preset number, or when the proportion of target identification points to all target points reaches a second preset proportion.
[0066] Based on the above-mentioned optional technical solutions, the seismic data processing module 302 may optionally include: a data volume generation unit, a root mean square amplitude determination unit, and an average root mean square amplitude determination unit. The data volume generation unit is used to generate a three-dimensional data volume based on the time-domain seismic data. The three-dimensional data volume includes multiple main survey lines and multiple connecting survey lines, with the main survey lines and connecting survey lines perpendicular to each other. The root mean square amplitude determination unit is used to determine the target point location based on the three-dimensional data volume and obtain the root mean square amplitude values of multiple reference connecting survey lines along the target connecting survey line direction. The average root mean square amplitude determination unit is used to determine the average root mean square amplitude value of the target point along the target main survey line direction based on the root mean square amplitude values of the multiple reference connecting survey lines.
[0067] Based on the above-mentioned optional technical solutions, the device for determining a gas leakage area may optionally include: ; in, This represents the average root mean square amplitude of the target point along the main survey line. For the first The root mean square amplitude value of the reference connection line. This represents the total number of reference connection survey lines used to calculate the average root mean square amplitude. The difference in the number of communication survey lines between the target communication survey line and the furthest reference communication survey line. This represents the number of connection survey lines corresponding to the target connection survey line at the target location.
[0068] Based on the above-mentioned optional technical solutions, the device for determining gas leakage areas may optionally include a normalization processing module. The normalization processing module is used to normalize the average root mean square amplitude value, coherence value, and total amplitude value of the multiple target points.
[0069] Based on the above-mentioned optional technical solutions, the device for determining a gas leakage area may optionally include: a root mean square amplitude threshold determination module, a coherence threshold determination module, and a total amplitude threshold determination module. Specifically, the root mean square amplitude threshold determination module is used to obtain the reference average root mean square amplitude values of multiple reference points in the target area where gas leakage is known, and to determine the lowest reference average root mean square amplitude value among the multiple reference points as the root mean square amplitude threshold; the coherence threshold determination module is used to obtain the reference coherence values of multiple reference points in the target area where gas leakage is known, and to determine the lowest reference coherence value among the multiple reference points as the coherence threshold; the total amplitude threshold determination module is used to obtain the reference total amplitude values of multiple reference points in the target area where gas leakage is known, and to determine the lowest reference total amplitude value among the multiple reference points as the total amplitude threshold.
[0070] The device for determining a gas leakage area provided in the embodiments of the present invention can execute the method for determining a gas leakage area provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.
[0071] Example 4 Figure 4A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.
[0072] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0073] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0074] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a method for determining a gas leak area.
[0075] In some embodiments, a method for determining a gas leak area may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for determining a gas leak area described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform a method for determining a gas leak area by any other suitable means (e.g., by means of firmware).
[0076] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0077] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0078] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0079] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0080] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.
[0081] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.
[0082] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.
[0083] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.
[0084] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.
Claims
1. A method for determining a gas leakage area, characterized in that, include: Multiple target observation areas are determined from the target area, and time-domain seismic data of multiple data sampling points in each target observation area are collected; For a single data sampling point, the average root mean square amplitude value of the target point in the direction of the target main survey line is determined based on the time-domain seismic data of the data sampling point, and the coherence value and total amplitude value of the target point are determined, wherein the target point includes the target main survey line and the target connecting survey line; Based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points, the gas leakage identification result for each target observation area is determined.
2. The method for determining a gas leakage area according to claim 1, characterized in that, The gas leak identification result includes gas leaks. The determination of the gas leak identification result for each target observation area based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points includes: If the average root mean square amplitude values of multiple target points meet the first condition, the target observation area is determined as a candidate area. If the coherence value and total amplitude value of multiple target points in the candidate region satisfy the second condition, it is determined that there is gas leakage in the candidate region.
3. The method for determining a gas leakage area according to claim 2, characterized in that, The step of determining the target observation area as a candidate area when the average root mean square amplitude values of multiple target points meet a first condition includes: If the average root mean square amplitude of the target points is greater than the root mean square amplitude threshold, the target observation area is determined as a candidate area; or, If the average root mean square amplitude of the target points is greater than the root mean square amplitude threshold, the target observation area is determined as a candidate area.
4. The method for determining a gas leakage area according to claim 2, characterized in that, When the coherence value and total amplitude value of multiple target points in the candidate region satisfy the second condition, it is determined that there is gas leakage in the candidate region, including: Among the multiple target points in the candidate region, the target points whose coherence value is greater than the coherence threshold and whose total amplitude value is greater than the total amplitude threshold are identified as target identification points; If the number of target identification points reaches a second preset number, it is determined that there is gas leakage in the candidate area; or, if the proportion of target identification points to all target points reaches a second preset proportion, it is determined that there is gas leakage in the candidate area.
5. The method for determining a gas leakage area according to claim 1, characterized in that, The step of determining the average root mean square amplitude value of the target point corresponding to the data sampling point along the target main survey line direction based on the time-domain seismic data of the data sampling point includes: A three-dimensional data volume is generated based on the time-domain seismic data. The three-dimensional data volume includes multiple main survey lines and multiple connecting survey lines, and the main survey lines and the connecting survey lines are perpendicular to each other. The target point is determined based on the three-dimensional data volume, and the root mean square amplitude value of the target point on multiple reference connection survey lines in the direction of the target connection survey line is obtained. The average root mean square amplitude value of the target point in the direction of the target main survey line is determined based on the root mean square amplitude values of multiple reference connection survey lines.
6. The method for determining a gas leakage area according to claim 5, characterized in that, Determining the average root mean square amplitude value of the target point along the target main survey line direction based on the root mean square amplitude values of multiple reference connection survey lines includes: ； in, This represents the average root mean square amplitude of the target point along the main survey line. For the first The root mean square amplitude value of the reference connection line. This represents the total number of reference connection survey lines used to calculate the average root mean square amplitude. The difference in the number of communication survey lines between the target communication survey line and the furthest reference communication survey line. This represents the number of connection survey lines corresponding to the target connection survey line at the target location.
7. The method for determining a gas leakage area according to claim 1, characterized in that, Before determining the gas leakage identification result for each target observation area based on the average root mean square amplitude value, the coherence value, and the total amplitude value of multiple target points, the method further includes: The average root mean square amplitude, coherence value, and total amplitude value of the multiple target points are normalized.
8. The method for determining a gas leakage area according to claim 2, characterized in that, It also includes at least one of the following: Obtain the reference average root mean square amplitude values of multiple reference points in the target area where gas leakage is known to exist, and determine the lowest reference average root mean square amplitude value among the multiple reference points as the root mean square amplitude threshold. Obtain reference coherence values for multiple reference points in the target area where gas leakage is known to exist, and determine the lowest reference coherence value among the multiple reference points as the coherence threshold; Obtain the reference total amplitude value of multiple reference points in the target area where gas leakage is known, and determine the lowest reference total amplitude value among the multiple reference points as the total amplitude value threshold.
9. An electronic device, characterized in that, The electronic device includes: One or more processors; a storage device for storing one or more programs, which, when executed by one or more of the programs, cause one or more of the processors to implement the method for determining a gas leakage area as described in any one of claims 1-8.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for determining gas leakage areas as described in any one of claims 1-8.