Oil and gas well field vegetation recovery quitting monitoring and evaluation method

Abstract

The invention relates to an oil and gas well field vegetation recovery quitting monitoring and evaluation method, which comprises the following steps: carrying out image preprocessing on obtained research area remote sensing images of different time phases to obtain preprocessed remote sensing images; on the basis of pre-established remote sensing interpretation marks of different types of well sites, the preprocessed remote sensing images of different time phases are compared, and the well site where the oil and gas facility exits is determined; calculating vegetation growth indexes of different time phases for a well site where the oil and gas facility exits based on the preprocessed remote sensing image; according to the vegetation growth indexes of different time phases, determining the change condition of the vegetation growth index in the well before and after the oil and gas facility exits; and evaluating the vegetation recovery condition of the well site where the oil and gas facility exits according to the change condition. The remote sensing change detection technology is introduced into oil and gas well exit and ecological restoration monitoring, the large-range oil and gas well field exit and vegetation restoration conditions can be efficiently and accurately monitored, and the blank that the remote sensing technology is used for oil field ecological restoration monitoring is filled.

Description

Technical Field

[0001] The invention relates to a method for monitoring and evaluating vegetation restoration after an oil and gas well site is withdrawn. Background Art

[0002] Ecological protection requires that oil and gas field exploration and development simultaneously address environmental protection. Exiting exploration and development operations requires shutting down and sealing wells, dismantling oil and gas facilities, and carrying out geomorphological and ecological restoration of the surrounding environment. Therefore, monitoring the ecological recovery of oil and gas wells after exit is a crucial component of evaluating oil and gas field ecological protection. In recent years, with the rapid development of remote sensing Earth observation technology, the spectral, spatial, and temporal resolution of satellite remote sensing imagery has significantly improved, enabling comprehensive and real-time monitoring of oil and gas exploration and development activities and the restoration of vegetation at exited well sites. Compared to traditional manual on-site surveys, remote sensing monitoring technology is more economical, scientific, comprehensive, and efficient. Summary of the Invention

[0003] In order to provide a fast, effective, and operational remote sensing-based monitoring and evaluation method for oil and gas well site withdrawal vegetation restoration, which greatly improves the comprehensiveness, timeliness, and accuracy of oil and gas well site withdrawal monitoring, the present invention proposes a monitoring and evaluation method for oil and gas well site withdrawal vegetation restoration. The technical solutions proposed in the present invention are as follows:

[0004] In a first aspect, the present invention provides a method for monitoring and evaluating vegetation restoration after oil and gas well site exit, comprising:

[0005] Perform image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images;

[0006] Based on pre-established remote sensing interpretation marks for different types of well sites, the pre-processed remote sensing images of different time phases are compared to determine the well site where the oil and gas facilities are to be withdrawn;

[0007] Based on the pre-processed remote sensing images, calculating vegetation growth indexes at different time phases for the well site where the oil and gas facilities have been removed;

[0008] Determining changes in the vegetation growth index in the well site before and after the oil and gas facilities are withdrawn based on the vegetation growth index at different time phases;

[0009] Based on the changes, the vegetation recovery status of the well site where the oil and gas facilities have been withdrawn is evaluated.

[0010] In one or some embodiments, performing image preprocessing on the acquired remote sensing images of the study area at different time phases to obtain preprocessed remote sensing images includes:

[0011] Screening remote sensing data including visible light band, near infrared band and panchromatic band with sub-meter spatial resolution, and image cloud cover below a preset cloud cover threshold, to obtain remote sensing images of the study area;

[0012] The remote sensing images of the study area are subjected to orthorectification, image cropping, radiation correction, atmospheric correction, image registration and image fusion processing to obtain preprocessed remote sensing images.

[0013] In one or more embodiments, the remote sensing interpretation markers of different types of well sites are established by:

[0014] The electromagnetic radiation characteristics, geometric features, and spatial relationships with surrounding objects and the environment of different objects in the pre-processed remote sensing images of the research area are comprehensively studied to establish remote sensing interpretation marks for different types of well sites.

[0015] In one or more embodiments, the vegetation growth index is determined by the following formula:

[0016]

[0017] Among them, GRNDVI represents the vegetation growth index, NIR represents the surface reflectance in the near-infrared band, and R represents the surface reflectance in the red light band.

[0018] In one or some embodiments, determining the change in vegetation growth index in the well site before and after the withdrawal of the oil and gas facilities based on the vegetation growth index in different time phases includes:

[0019] Based on the vegetation growth indexes at different time phases, a qualitative classification of vegetation change types and a quantitative evaluation of vegetation growth change degrees are performed on the well sites before and after the oil and gas facilities are withdrawn, to obtain the change status.

[0020] In one or some embodiments, the qualitative classification of vegetation change types is performed in the following manner:

[0021] According to a preset index threshold and the vegetation growth index, pixels in the well site area are divided into vegetation and bare land, and are assigned values ​​of 1 and 0 respectively to obtain an assignment result;

[0022] The assignment results of different time phases were subtracted to obtain three types of changes: vegetation changing to bare land, no change, and bare land changing to vegetation.

[0023] In one or more embodiments, the quantitative evaluation of the degree of change in vegetation growth is performed by:

[0024] The vegetation growth indexes at different phases are subtracted to obtain the subtraction results;

[0025] The degree of change in vegetation growth at the well site is determined based on a preset change threshold and the difference result; wherein the degree of change in vegetation growth includes three levels: worsening growth, no significant change in growth, and improving growth.

[0026] In one or some embodiments, evaluating the vegetation restoration status of the well site where the oil and gas facility has exited based on the change includes:

[0027] Selecting areas in the well site where the oil and gas facilities have been removed where the vegetation change type is from bare land to vegetation as vegetation restoration areas, and selecting areas in the well site where the oil and gas facilities have been removed where the vegetation growth has improved as growth restoration areas;

[0028] Combined with the vector boundaries of the well site, the proportion of the growth recovery area and the vegetation recovery area in the well site where the oil and gas facilities have exited is calculated, and the recovery status of the well site is evaluated as recovered, recovering, or not recovered based on a preset proportion threshold.

[0029] In one or some embodiments, before calculating the ratio of the growth recovery area and the vegetation restoration area in the well site, the method further includes:

[0030] The corresponding pixels of the ternary map where the change results are growth recovery areas and vegetation recovery areas are summed, and the duplicate pixels of the growth recovery areas and vegetation recovery areas are removed.

[0031] In a second aspect, the present invention provides a monitoring and evaluation device for vegetation restoration after oil and gas well site exit, comprising:

[0032] A preprocessing module is used to perform image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images;

[0033] An identification module is used to compare the pre-processed remote sensing images of different phases based on pre-established remote sensing interpretation marks of different types of well sites to determine the well site where the oil and gas facilities have exited;

[0034] A calculation module, configured to calculate vegetation growth indexes at different time phases for the well site where the oil and gas facilities have exited, based on the pre-processed remote sensing images;

[0035] A classification module is used to determine the change of the vegetation growth index in the well site before and after the oil and gas facility is withdrawn according to the vegetation growth index in different time phases;

[0036] An evaluation module is used to evaluate the vegetation restoration status of the well site where the oil and gas facilities have withdrawn based on the changes.

[0037] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the oil and gas well site exit vegetation restoration monitoring and evaluation method as described in the first aspect.

[0038] In a fourth aspect, the present invention provides an electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0039] Memory for storing computer programs;

[0040] The processor is used to implement the oil and gas well site exit vegetation restoration monitoring and evaluation method as described in the first aspect when executing the program stored in the memory.

[0041] Based on the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0042] The method for monitoring and evaluating vegetation restoration after oil and gas well site withdrawal provided by the present invention is based on the characteristics of oil and gas well site patches being small, numerous, and widely distributed. In order to be able to efficiently and accurately carry out large-scale oil and gas well site withdrawal and vegetation restoration monitoring, it fully utilizes the technical advantages of satellite remote sensing in macroscopic observation, fine characterization, and dynamic quantification, combines GIS and GPS technologies, and introduces remote sensing change detection technology into the field of oil and gas well site withdrawal and ecological restoration monitoring. The present invention establishes oil and gas well site remote sensing interpretation marks and introduces quantitative analysis based on vegetation growth index, thereby opening up a new technical approach for remote sensing monitoring and evaluation of vegetation restoration after oil and gas well site withdrawal. Introducing remote sensing change detection technology into oil and gas well site withdrawal and ecological restoration monitoring can efficiently and accurately monitor the withdrawal of oil and gas well sites and vegetation restoration in a large area, solving the problems of high cost, poor timeliness, and limited monitoring range of traditional field inspection methods, and filling the gap in the use of remote sensing technology for oilfield ecological restoration monitoring. Compared with traditional repetitive field inspections, this method has the advantages of a large monitoring range, short revisit cycle, low cost, and the ability to repeat large-scale vegetation restoration monitoring and evaluation. The promotion and application of this method can provide an important evaluation basis for the ecological protection of oil and gas fields, and effectively contribute to the green and sustainable development of oil and gas mines.

[0043] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 Flowchart of the monitoring and evaluation method for vegetation restoration after oil and gas well site exit.

[0047] Figure 2 This is a technical flow chart for remote sensing monitoring of vegetation restoration after oil and gas well site exit.

[0048] Figure 3 These are the qualitative detection results of the change types in the Dabusu Lake experimental area; (a) is the GRNDVI classification map in 2017, (b) is the GRNDVI classification map in 2019, and (c) is the bare land to vegetation conversion result map.

[0049] Figure 4 These are the quantitative evaluation results of the degree of change in the Dabusu Lake experimental area; (a) is the GRNDVI classification in 2017, (b) is the GRNDVI classification in 2019, and (c) is the GRNDVI difference result classification.

[0050] Figure 5 These are the qualitative detection results of change types in the northern area of ​​Liaohe River; (a) is the GRNDVI classification map in 2017, (b) is the GRNDVI classification map in 2020, and (c) is the bare land to vegetation map.

[0051] Figure 6 These are the quantitative evaluation results of the degree of change in the northern area of ​​Liaohe River; (a) is the GRNDVI classification in 2017, (b) is the GRNDVI classification in 2020, and (c) is the GRNDVI difference result classification.

[0052] Figure 7 The qualitative detection results of the change types in the southern part of Liaohe River are shown in Figure 1. (a) is the GRNDVI classification map in 2017, (b) is the GRNDVI classification map in 2020, and (c) is the bare land to vegetation map.

[0053] Figure 8 The quantitative evaluation results of the degree of change in the southern part of Liaohe River are shown in Figure 1. (a) is the GRNDVI classification in 2017, (b) is the GRNDVI classification in 2020, and (c) is the GRNDVI difference classification.

[0054] Figure 9 Remote sensing interpretation signs for different types of well sites.

[0055] Figure 10 This is a structural diagram of the oil and gas well site exit vegetation restoration monitoring and evaluation device.

[0056] Figure 11 A schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0057] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0058] A literature review revealed that remote sensing technology is currently used to monitor vegetation restoration in mining areas, primarily in solid mines such as coal, stone, and metal mines. The indicators used are primarily parameters such as the Normalized Difference Vegetation Index (NDVI) and vegetation coverage. In 2014, Zhiyong Qiao et al. used long-term Landsat data to calculate and monitor vegetation coverage (FVC) and vegetation condition index (VCI) within the Daliuta mining area, evaluating the long-term variation characteristics of vegetation growth and coverage within the study area. In 2016, Zhang Yao et al. used Landsat data from 1987 to 2013 to monitor vegetation coverage and vegetation recovery within the Pingshuo open-pit coal mine in Shanxi Province. Using the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Width Index (NDWI), and the Reach Difference Vegetation Index (RNDVI), they used Landsat data from 1987 to 2013 to monitor vegetation recovery. This has a certain role in promoting the improvement of the indicator system for mining area supervision. In 2018, Pang Dong et al. used Landsat TM / ETM+ / OLI satellite data from 2007 to 2016 to calculate the vegetation coverage index (FVC) and vegetation growth index (VCI) in an iron mine in Xinjiang and its surrounding areas. They evaluated the spatiotemporal variation of vegetation coverage and vegetation growth in the study area and explored the impact of iron ore mining on the surrounding environment. In 2021, Liu Huan, Hu Qingwu et al. used the GEE as a research platform in the Mufushan dolomite mining area of ​​Nanjing. Based on Landsat data from 1991 to 2020, they calculated the vegetation coverage (FVC) in the study area and analyzed its trend using the Sen+Mann-Kendall method. This allowed them to conduct long-term dynamic monitoring of the vegetation restoration effect in the study area.

[0059] Currently, ecological restoration monitoring in oil and gas well site exit areas is mostly carried out through repetitive field inspections. This method is costly and time-consuming, making it unsuitable for large-scale monitoring. Remote sensing technology offers advantages such as a large monitoring range, short revisit cycles, and low cost, making it suitable for repeated large-scale vegetation restoration monitoring and assessment. Due to the small scale, large number, and widespread distribution of oil and gas well sites, their remote sensing image characteristics also vary regionally and by industry. Therefore, it is necessary to establish a set of oil and gas well exit and ecological restoration indicator parameters and remote sensing intelligent monitoring technology processes. In recent years, global Earth observation space technology has continued to develop. The number and types of satellites at home and abroad have increased, and the spatial and temporal resolutions have become increasingly higher. The ability to observe targets has been enhanced, and the details have become more prominent. The ability to accurately observe oil and gas well sites using remote sensing technology has become available.

[0060] Example 1

[0061] The purpose of the present invention is to provide a fast, effective and operational remote sensing-based remote sensing monitoring and evaluation method for oil and gas well site withdrawal vegetation restoration, which greatly improves the comprehensiveness, timeliness and accuracy of oil and gas well site withdrawal monitoring, fully utilizes the advantages of remote sensing technology, and makes up for the shortcomings of traditional methods such as high cost and poor timeliness. The oil and gas well site withdrawal vegetation restoration monitoring and evaluation method provided in the embodiment of the present invention, with reference to Figure 1 and Figure 2 As shown, including:

[0062] S101, performing image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images;

[0063] Image selection should consider four key factors: band combination, spatial resolution, temporal phase, and cloud cover. Remote sensing data should include visible light, near-infrared, and panchromatic bands with sub-meter spatial resolution. Imagery should be taken during periods of high vegetation growth, and cloud cover should be below 8%.

[0064] S102, based on pre-established remote sensing interpretation marks for different types of well sites, comparing the pre-processed remote sensing images at different time phases to determine the well site where the oil and gas facilities are to be withdrawn;

[0065] Oil and gas well sites mainly include production wells and exploration wells. Among them, the exploration well site includes exploration facilities such as exploration well derricks, and the production well site includes various extraction facilities such as pumping units. Remote sensing interpretation marks are established based on the electromagnetic wave radiation characteristics, geometric features, and spatial relationships between the oil and gas well site and the surrounding objects and environment presented in the image. Figure 9 The remote sensing interpretation signs shown are used to compare and analyze images of different phases to determine the well site where the oil and gas facilities have been withdrawn.

[0066] Specifically, for the well sites in use: oil and gas well sites are generally square bare land with light colors and mostly rectangular shapes; there are linear roads connected to them, and they are interconnected with other well sites through roads; there are different types of pumping units in the oil well sites in use. The more common walking beam pumping units have an overall "sickle-shaped" or "long strip" morphology due to differences in imaging angles, and the pixels at the front end of the long strips are blurred; under different lighting conditions, dark shadows in the shape of "straight lines", "broken lines" or "clumps" will appear next to some pumping units.

[0067] For abandoned well sites: the vast majority of abandoned wells are rectangular, with occasional irregular shapes; their tones are mostly light, significantly different from the surrounding background; there are generally no oil and gas facilities inside, and sometimes a small amount of vegetation can be seen.

[0068] Comparing and analyzing images from different phases based on interpretation indicators reveals that if the imagery from the earlier phase contains square bare land (i.e., light-colored and mostly rectangular), connected by linear roads and connected to other well sites via roads, and contains pumping units (i.e., the overall image morphology exhibits a sickle-like or long strip shape), with pixels at the front of the strip blurred, and under varying lighting conditions, dark shadows resembling "straight lines," "broken lines," or "lumps" may appear next to some pumping units. If the wells in the later phase are mostly rectangular, with a few other irregular shapes, and have light colors that are significantly different from the surrounding background, and generally lack oil and gas facilities within, with a small amount of vegetation sometimes visible, this indicates that the well site is a decommissioned oil and gas facility.

[0069] S103, calculating vegetation growth indexes at different time phases for the well site where the oil and gas facilities have been removed based on the pre-processed remote sensing images;

[0070] The vegetation growth monitoring indicator used is the Growth Root Normalized Differential Vegetation Index (GRNDVI). It provides a visual description of vegetation growth and more accurately depicts vegetation growth status. Compared with more common vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the Relative Difference Vegetation Index (RVI), GRNDVI significantly mitigates the effects of soil background on NDVI at low vegetation coverage and the excessively large and rapidly changing RVI values ​​at high vegetation coverage.

[0071] The vegetation growth index is determined by the following formula:

[0072]

[0073] Among them, GRNDVI represents the vegetation growth index, NIR represents the surface reflectance in the near-infrared band, and R represents the surface reflectance in the red light band.

[0074] For the well site from which the oil and gas facilities have been withdrawn, as determined in step S102 above, the above formula is applied to calculate the growth monitoring index GRNDVI of the well site vegetation at different time phases.

[0075] S104, determining changes in the vegetation growth index in the well site before and after the oil and gas facility is withdrawn based on the vegetation growth index at different time phases;

[0076] Based on the changes in GRNDVI at different time phases, GRNDVI change detection was carried out to determine the changes in vegetation growth index in the well site before and after the withdrawal of oil and gas facilities.

[0077] S105. Evaluate the vegetation restoration status of the well site where the oil and gas facilities have been removed based on the changes.

[0078] The present invention relates to the fields of remote sensing image processing and analysis and oil and gas remote sensing technology, and specifically to a method for monitoring and evaluating the ecological restoration of oil and gas mines based on multi-temporal, high-resolution satellite remote sensing. The present invention proposes a remote sensing-based monitoring and evaluation method for vegetation restoration after oil and gas well site withdrawal, which fully utilizes the technical advantages of satellite remote sensing in macroscopic observation, fine characterization, and dynamic quantification. In view of the small, numerous, and widely distributed patches of oil and gas well sites, remote sensing change detection technology is introduced into oil and gas well withdrawal and ecological restoration monitoring. This method can efficiently and accurately monitor the withdrawal of oil and gas well sites and vegetation restoration over a large area, solving the problems of high cost, poor timeliness, and limited monitoring range of traditional field inspection methods, and filling the gap in the application of remote sensing technology to oilfield ecological restoration monitoring.

[0079] In view of the characteristics of oil and gas well sites with small patches, large numbers and wide distribution, in order to carry out large-scale oil and gas well site withdrawal and vegetation restoration monitoring efficiently and accurately, the present invention fully utilizes the technical advantages of satellite remote sensing in macroscopic observation, fine characterization and dynamic quantification, combines GIS and GPS technology, introduces remote sensing change detection technology into the field of oil and gas well withdrawal and ecological restoration monitoring, and proposes a remote sensing monitoring and evaluation method for vegetation restoration of oil and gas well site withdrawal based on remote sensing. The results show that this method is effective in monitoring and counting the withdrawal of oil and gas facilities and the vegetation restoration of related well sites. Compared with traditional repetitive field inspections, it has the advantages of large monitoring range, short revisit cycle, low cost, and repeatable large-area vegetation restoration monitoring and evaluation. The promotion and application of this method can provide an important evaluation basis for the ecological protection of oil and gas fields, and effectively contribute to the green and sustainable development of oil and gas mines.

[0080] In an optional embodiment, the image preprocessing of the remote sensing images of the study area acquired at different time phases described in step S101 to obtain preprocessed remote sensing images includes:

[0081] S1011. Filter remote sensing data including visible light bands, near-infrared bands, and panchromatic bands with sub-meter spatial resolution, and image cloud cover below a preset cloud cover threshold, to obtain a remote sensing image of the study area;

[0082] Image selection should consider four key factors: band combination, spatial resolution, temporal phase, and cloud cover. Remote sensing data should include visible light, near-infrared, and panchromatic bands with sub-meter spatial resolution. Imagery should be taken during periods of high vegetation growth, and cloud cover should be below 8%.

[0083] S1012. Perform orthorectification, image cropping, radiation correction, atmospheric correction, image registration, and image fusion processing on the remote sensing image of the study area to obtain a pre-processed remote sensing image.

[0084] Orthorectification corrects geometric distortion caused by terrain, satellite attitude, and sensor geometry to produce images with accurate geographic location and uniform scale. This correction is accomplished using the image's included PRC file and the DEM data included with ENVI software, using the "PRC Orthorectification Workflow" tool in ENVI. Radiometric correction applies a gain and offset to the DN values ​​recorded in the image, ultimately converting them into apparent reflectance. This is accomplished using the "Apply Gain and Offset" tool in ENVI software, utilizing the gain and offset coefficients of different sensors. Atmospheric correction converts the radiance (or apparent reflectance) of the top atmosphere into the radiance (or surface reflectance) of sunlight reflected from the surface, eliminating the effects of atmospheric absorption and scattering on radiation transmission. This is accomplished using the "FLAASH Atmospheric Correction" tool in ENVI software. Geometric registration aligns the geographic coordinates of different images, ensuring that they correspond exactly to each other for the same region, facilitating subsequent image fusion and change detection. This is accomplished by manually selecting a number of pixels with the same name and using the "Georeferencing" tool in arcMAP software. The purpose of image fusion is to fuse panchromatic images and multispectral images to obtain multispectral images with higher spatial resolution. The specific method is to use the "Principal Component Change Image Fusion" tool of ENVI software to fuse the registered panchromatic images and multispectral images.

[0085] In an optional embodiment, the remote sensing interpretation marks of the different types of well sites are established in the following manner:

[0086] The electromagnetic radiation characteristics, geometric features, and spatial relationships with surrounding objects and the environment of different objects in the pre-processed remote sensing images of the research area are comprehensively studied to establish remote sensing interpretation marks for different types of well sites.

[0087] Remote sensing interpretation marks are established based on the electromagnetic radiation characteristics, geometric features, and spatial relationships between the oil and gas well site and the surrounding objects and environment presented by the fused images. Figure 9 The remote sensing interpretation signs shown are used to compare and analyze images of different phases to determine the well site where the oil and gas facilities have been withdrawn.

[0088] In an optional embodiment, the step S104 described above of determining the change in vegetation growth index in the well site before and after the withdrawal of the oil and gas facilities based on the vegetation growth index in different time phases includes:

[0089] Based on the vegetation growth indexes at different time phases, a qualitative classification of vegetation change types and a quantitative evaluation of vegetation growth change degrees are performed on the well sites before and after the oil and gas facilities are withdrawn, to obtain the change status.

[0090] Specifically, GRNDVI change detection is conducted based on the changes in the vegetation growth index at different time phases. Change detection is divided into two aspects: qualitative classification of change types and quantitative evaluation of the degree of change. By comparing the vegetation growth index at the well site before and after the oil and gas facility decommissioning, the type of vegetation change and the degree of vegetation growth change at the well site are determined.

[0091] In an optional embodiment, the qualitative classification of vegetation change types is performed in the following manner:

[0092] S1041, dividing pixels in the well site area into vegetation and bare land according to a preset index threshold and the vegetation growth index, assigning values ​​of 1 and 0 respectively, to obtain an assignment result;

[0093] First, a threshold (the preset index threshold) was set for the GRNDVI of the two temporal phases. Based on the threshold segmentation results, pixels in the wellsite area below the preset index threshold were classified as bare ground, while pixels greater than or equal to the preset index threshold were classified as vegetation. Pixels identified as vegetation were assigned a value of 1, while pixels identified as bare ground were assigned a value of 0. These preset index thresholds were determined through field surveys and a comprehensive analysis of the GRNDVI values ​​at the corresponding locations.

[0094] S1042. Differences are calculated for the assignment results at different time phases to obtain three types of changes: vegetation changing to bare land, no change, and bare land changing to vegetation.

[0095] The difference between the two temporal classification result maps was calculated to detect three types of changes: vegetation to bare land, no change, and bare land to vegetation, and they were assigned values ​​of -1, 0, and 1 respectively (e.g. Figure 3 、 5 , 7), and obtain the GRNDVI change type three-value map corresponding to the detection results. The bare land->vegetation type area, that is, the pixel with a pixel value of 1, is selected as the vegetation restoration area.

[0096] In an optional embodiment, the quantitative evaluation of the degree of change in vegetation growth is performed in the following manner:

[0097] S1043. Subtract the vegetation growth indexes at different time phases to obtain a difference result; and determine the degree of change in vegetation growth at the well site based on a preset change threshold and the difference result.

[0098] For the remote sensing images after preprocessing, the difference of the GRNDVI index between the two time phases is first calculated to obtain the difference result. The pixels with a difference result greater than or equal to the preset change threshold are evaluated as having improved growth and are assigned a value of 1. The pixels between the threshold and 0 are evaluated as having unchanged growth and are assigned a value of 0. The pixels with a difference result less than 0 are evaluated as having deteriorated growth and are assigned a value of -1 (e.g. Figure 4 、 6 , 8), and obtain the GRNDVI change degree three-value map corresponding to the test results. The area with a good growth level, that is, the pixel with a pixel value of 1, is selected as the growth recovery area.

[0099] The above-mentioned preset change threshold was obtained by selecting 30 sample points that were evenly distributed in the study area and covered different types, covering three types of changes. Through field surveys and historical image comparisons, based on the sorting and comparison of the GRNDVI change values ​​of each sample point, the optimal threshold that can completely distinguish the change types of the 30 sample points was selected to obtain the above-mentioned preset change threshold.

[0100] In an optional embodiment, the step S105 of evaluating the vegetation restoration status of the well site where the oil and gas facility has exited based on the change status includes:

[0101] S1051. Select the area in the well site where the oil and gas facility has exited and the vegetation change type is bare land -> vegetation type as the vegetation restoration area, and select the area in the well site where the oil and gas facility has exited and the vegetation growth change degree is improved as the growth recovery area; combine the vector boundary of the well site, calculate the ratio of the growth recovery area and the vegetation restoration area in the well site where the oil and gas facility has exited, and evaluate the recovery status of the well site as recovered, recovering, or not recovered based on the preset ratio threshold.

[0102] Based on the well site's vector boundaries, the proportions of "growth recovery areas" and "vegetation recovery areas" within the well site are calculated. A threshold is then set for these proportions to obtain the preset ratio thresholds. Well site recovery is then assessed as "recovered," "recovering," or "not recovered." For example, if the preset ratio thresholds are set to 0.5 and 0.8, well sites with a ratio exceeding 80% (inclusive) are considered "recovered," well sites with a ratio between 50% (inclusive) and 80% are considered "recovering," and well sites with a ratio less than 50% are considered "not recovered."

[0103] In an optional embodiment, before calculating the ratio of the growth recovery area and the vegetation recovery area in the well site, the method further includes:

[0104] The corresponding pixels of the ternary map where the change results are growth recovery areas and vegetation recovery areas are summed, and the duplicate pixels of the growth recovery areas and vegetation recovery areas are removed.

[0105] There will be overlap between the "growth recovery area" and the "vegetation recovery area." To count these pixels, sum the corresponding pixels in the GRNDVI change type ternary map and the GRNDVI change degree ternary map in S1042 and S1043. Pixels with a sum of 2 are overlapping pixels and should be removed when calculating the proportion. These pixels are removed from the growth recovery area or the vegetation recovery area, and then the proportion of these two types of areas in the well site is calculated.

[0106] Example 2

[0107] In order to provide a clearer explanation of the remote sensing-based oil and gas well site exit vegetation restoration monitoring and evaluation method provided in an embodiment of the present invention and to verify the accuracy of the method, the oil and gas well site exit vegetation restoration monitoring and evaluation method was applied to the Dabusu Lake area in Jilin and the Liaohekou area in Liaoning to obtain the corresponding vegetation restoration conditions.

[0108] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0109] Reference Figure 2 As shown, the present invention proposes a remote sensing monitoring and evaluation method for vegetation recovery after oil and gas well site withdrawal, comprising the following steps: 1) optimizing remote sensing data and performing corresponding preprocessing on it; 2) establishing remote sensing interpretation marks for oil field stations and performing image interpretation to identify well sites where oil and gas facilities have been withdrawn; 3) constructing and calculating the vegetation growth index GRNDVI at different phases; 4) analyzing the changes in GRNDVI in the well site before and after the withdrawal of oil and gas facilities; and 5) evaluating the vegetation recovery of the well site based on the change detection results.

[0110] Regarding step 1): the experimental areas selected in the present invention are the Dabusu Lake area in Jilin and the Liaohekou area in Liaoning, the latter of which is divided into two working areas, the south area and the north area.

[0111] About step 1): The present invention uses the GF-2 images of the Dabusu Lake area in Jilin Province on August 25, 2017 and September 4, 2019, and the Liaohekou area in Liaoning Province on August 30, 2017, August 14, 2020 (North District), and July 14, 2022 (South District), including four multispectral bands of red, green, blue, and near-infrared and one panchromatic band, wherein the spatial resolution of the multispectral band is 4m, and the spatial resolution of the panchromatic band is 1 meter. Since 1A-level data is used, it needs to be preprocessed to meet the requirements of remote sensing interpretation and quantitative analysis. The image preprocessing process mainly includes: orthorectification, radiation correction, atmospheric correction, geometric alignment and image fusion. For the preprocessed GF-2 image, the GF-2 image is cropped according to the study area vector, that is, the scope of the study area, to obtain the image corresponding to the study area.

[0112] Regarding step 2): The oil and gas facilities in the well site are mainly pumping units, oil storage tanks, etc. The remote sensing interpretation signs of different types of well sites are summarized by comprehensively studying the electromagnetic radiation characteristics, geometric features, and spatial relationships with surrounding objects and the environment of different land features in the fused image. The specific interpretation signs are as follows: Figure 9 By comparing and analyzing images of different phases based on the interpreted symbols, the well sites where oil and gas facilities have been decommissioned are identified.

[0113] For the well sites in use: oil and gas well sites are generally square bare land with light colors and mostly rectangular shapes; there are linear roads connecting them, and they are interconnected with other well sites through roads; there are different types of pumping units in the oil well sites in use. The more common walking beam pumping units have an overall "sickle-shaped" or "long strip" morphology due to differences in imaging angles, and the pixels at the front end of the long strips are blurred; under different lighting conditions, dark shadows in the shape of "straight lines", "broken lines" or "clumps" will appear next to some pumping units.

[0114] For abandoned well sites: the vast majority of abandoned wells are rectangular, with occasional irregular shapes; their tones are mostly light, significantly different from the surrounding background; there are generally no oil and gas facilities inside, and sometimes a small amount of vegetation can be seen.

[0115] Comparing and analyzing images from different phases based on interpretation signs reveals that if the image from the previous phase contains square bare land (i.e., light-colored and mostly rectangular in shape), connected by a linear road and connected to other well sites via roads, and if there are pumping units in the image (i.e., the image has an overall "sickle-shaped" or "long strip" shape, with blurred pixels at the front end of the strip), and dark shadows like "straight lines," "broken lines," or "lumps" appear next to some pumping units under different lighting conditions, then the well site in the image from the previous phase is in use.

[0116] If the wells in the later phase images are mostly rectangular in shape, with a small number of other irregular shapes; their tones are light, significantly different from the surrounding background; there are generally no oil and gas facilities inside, and sometimes a small amount of vegetation can be seen, it means that the well site in the later phase images is the well site where oil and gas facilities have withdrawn.

[0117] Regarding step 3): Based on the pre-processed GF-2 multispectral image, for the oil and gas facility exit well site determined in step 2, calculate the GRNDVI according to the following formula:

[0118]

[0119] NIR refers to the surface reflectance of the near-infrared band, which is the band 4 band of the GF-2 image; R refers to the surface reflectance of the red band, which is the band 3 band of the GF-2 image.

[0120] Regarding step 4): Change detection is divided into two main aspects: qualitative classification of change types and quantitative evaluation of the degree of change.

[0121] For qualitative classification detection of change types. Thresholds are set for the GRNDVI of the two phases respectively. The GRNDVI threshold of the remote sensing images selected for the Dabusu Lake area and the northern area of ​​Liaohe River is set to 1.40, and that for the southern area of ​​Liaohe River should be set to 1.60. Bare land is below the threshold, and vegetation is greater than or equal to the threshold. According to the threshold segmentation results, pixels in the well site area greater than the threshold are divided into "vegetation", and pixels less than the threshold are divided into "bare land", and are assigned values ​​of 1 and 0 respectively. The pre-processed GF-2 multispectral images of the latter phase and the former phase are assigned values ​​to obtain the binary image of the latter phase and the binary image of the former phase respectively. The difference between the binary images of the two phases is taken to detect three types of changes: vegetation to bare land, no change, and bare land->vegetation, and are assigned values ​​of -1, 0, and 1 respectively (such as Figure 3 、 5 , 7), and obtain the GRNDVI change type three-value map corresponding to the detection results. The bare land->vegetation type area, that is, the pixel with a pixel value of 1, is selected as the vegetation restoration area.

[0122] For the Dabusu Lake experimental area, the threshold should be set to 1.40. The results are as follows Figure 3 As shown; for the northern area of ​​Liaohekou Experimental Area, the threshold should also be set to 1.40, and the results are as follows Figure 5 As shown; for the southern area of ​​Liaohekou Experimental Area, the threshold should be set to 1.60, and the results are as follows Figure 7 shown.

[0123] Regarding step 4): quantitative evaluation and analysis of the degree of change. First, the difference of the GRNDVI index of the two phases is calculated to obtain the difference result, and then a threshold is set for the difference result. After experiments, for the Dabusu Lake area and the northern area of ​​Liaohekou, the threshold should be set to 0.20; for the southern area of ​​Liaohekou, the threshold should be set to 0.30. Pixels with a difference result greater than or equal to the threshold are evaluated as "growth improved" and assigned a value of 1, pixels between the threshold and 0 are evaluated as "growth unchanged" and assigned a value of 0, and pixels less than 0 are evaluated as "growth worsened" and assigned a value of -1 (such as Figure 4 、 6 , 8), and obtain the GRNDVI change degree three-value map corresponding to the test results. The "growth improves" level area, that is, the pixel value of 1, is selected as the "growth recovery area."

[0124] For the Dabusu Lake experimental area, the threshold should be set to 0.2. The results are as follows Figure 4 As shown; for the northern area of ​​Liaohekou Experimental Area, the threshold should also be set to 0.20, and the results are as follows Figure 6 As shown; for the southern area of ​​Liaohekou Experimental Area, the threshold should be set to 0.30, and the results are as follows Figure 8 shown.

[0125] Regarding step 5): Based on the vector boundary of the identified well site, count the "vegetation recovery zone" and "growth recovery zone" within the well site, calculate the ratio of the combined area of ​​the two areas to the total area of ​​the well site, and set a threshold for this ratio to further evaluate the vegetation recovery status of the well site.

[0126] For the Dabusu Lake Experimental Area, this threshold should be set at 0.8, meaning that well sites with a percentage exceeding 80% (inclusive) are considered "recovered," and well sites with a percentage less than 80% are considered "recovering." There are no "unrecovered" well sites in the Dabusu Lake Experimental Area. The statistical analysis results for the Dabusu Lake Experimental Area are shown in Table 1. Table 1 shows the oil and gas facility decommissioning and restoration evaluation table for the Dabusu Lake Experimental Area.

[0127]

[0128] Table 1

[0129] For the Liaohekou Experimental Area, the thresholds should be set at 0.5 and 0.8, meaning that well sites with a percentage exceeding 80% (inclusive) are considered "recovered," well sites with a percentage between 50% (inclusive) and 80% are considered "recovering," and well sites with a percentage less than 50% are considered "unrecovered." The statistical analysis results for the Liaohekou Experimental Area are shown in Table 2. Table 2 is an evaluation table for the decommissioning and restoration of oil and gas facilities in the Liaohekou Experimental Area.

[0130] Regarding step 5): There will be overlap between the "growth recovery area" and the "vegetation recovery area". Sum the corresponding pixels in the GRNDVI change type ternary map and the GRNDVI change degree ternary map in step 4. Pixels with a sum of 2 are overlapping pixels. Remove the overlapping pixels when calculating the percentage.

[0131]

[0132] Table 2

[0133] Example 3

[0134] The embodiment of the present invention provides a monitoring and evaluation device for vegetation restoration after oil and gas well site exit, referring to Figure 10 As shown, including:

[0135] A preprocessing module 201 is used to perform image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images;

[0136] Identification module 202, for comparing the pre-processed remote sensing images of different time phases based on pre-established remote sensing interpretation marks of different types of well sites, to determine the well site where the oil and gas facilities have exited;

[0137] A calculation module 203 is configured to calculate vegetation growth indices at different time phases for the well site where the oil and gas facilities have exited based on the pre-processed remote sensing images;

[0138] The classification module 204 is configured to determine the change in the vegetation growth index in the well site before and after the oil and gas facility is withdrawn based on the vegetation growth index in different time phases;

[0139] The evaluation module 205 is used to evaluate the vegetation restoration status of the well site where the oil and gas facilities have been removed based on the changes.

[0140] The oil and gas well site exit vegetation restoration monitoring and evaluation device provided in the embodiment of the present invention has an implementation principle and technical effects similar to any of the aforementioned method embodiments, and will not be repeated here.

[0141] Example 4

[0142] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for monitoring and evaluating vegetation restoration after oil and gas well site exit is implemented as described in the aforementioned method embodiment.

[0143] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments, or may exist independently without being incorporated into the device / apparatus. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0144] According to an embodiment of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0145] Example 5

[0146] An embodiment of the present invention provides an electronic device, referring to Figure 11 As shown, it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114.

[0147] Memory 113, for storing computer programs;

[0148] The processor 111 is configured to execute the program stored in the memory 113 to implement the oil and gas well site exit vegetation restoration monitoring and evaluation method as described in the aforementioned method embodiment.

[0149] The implementation principle and technical effects of the electronic device provided by the embodiment of the present invention are similar to those of any of the aforementioned method embodiments and will not be repeated here.

[0150] The memory 113 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. The memory 113 has storage space for program code for executing any of the method steps described above. For example, the storage space for program code can include individual program codes for implementing each of the steps in the method described above. These program codes can be read from or written to one or more computer program products. These computer program products include program code carriers such as a hard disk, a compact disc (CD), a memory card, or a floppy disk. Such computer program products are typically portable or fixed storage units. The storage unit can have storage segments or storage space arranged similarly to the memory 113 in the electronic device described above. The program code can be compressed, for example, in a suitable form. Typically, the storage unit includes a program for executing the method steps according to an embodiment of the present invention, i.e., code that can be read by, for example, the processor 111, and when executed by the electronic device, causes the electronic device to execute the various steps in the method described above.

[0151] In the present invention, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. The orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0152] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention is not limited to any single aspect, nor to any single embodiment, nor to any combination and / or permutation of these aspects and / or embodiments. Each aspect and / or embodiment of the present invention can be used alone or in combination with one or more other aspects and / or other embodiments.

[0153] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for monitoring and evaluating vegetation restoration after oil and gas well site exit, characterized in that: include: Perform image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images; Based on pre-established remote sensing interpretation marks for different types of well sites, the pre-processed remote sensing images of different time phases are compared to determine the well site where the oil and gas facilities are to be withdrawn; Based on the pre-processed remote sensing images, calculating vegetation growth indexes at different time phases for the well site where the oil and gas facilities have been removed; Determining changes in the vegetation growth index in the well site before and after the oil and gas facilities are withdrawn based on the vegetation growth index at different time phases; Based on the changes, the vegetation recovery status of the well site where the oil and gas facilities have been withdrawn is evaluated.

2. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 1 is characterized in that: The image preprocessing is performed on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images, including: Screening remote sensing data including visible light band, near infrared band and panchromatic band with sub-meter spatial resolution, and image cloud cover below a preset cloud cover threshold, to obtain remote sensing images of the study area; The remote sensing images of the study area are subjected to orthorectification, image cropping, radiation correction, atmospheric correction, image registration and image fusion processing to obtain preprocessed remote sensing images.

3. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 1 is characterized in that: The remote sensing interpretation marks of different types of well sites are established in the following way: The electromagnetic radiation characteristics, geometric features, and spatial relationships with surrounding objects and the environment of different objects in the pre-processed remote sensing images of the research area are comprehensively studied to establish remote sensing interpretation marks for different types of well sites.

4. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 1 is characterized in that: The vegetation growth index is determined by the following formula: Among them, GRNDVI represents the vegetation growth index, NIR represents the surface reflectance in the near-infrared band, and R represents the surface reflectance in the red light band.

5. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 1 is characterized in that: Determining the change in vegetation growth index in the well site before and after the withdrawal of the oil and gas facilities based on the vegetation growth index in different time phases includes: Based on the vegetation growth indexes at different time phases, a qualitative classification of vegetation change types and a quantitative evaluation of vegetation growth change degrees are performed on the well sites before and after the oil and gas facilities are withdrawn, to obtain the change status.

6. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 5 is characterized in that: A qualitative classification of vegetation change types was performed in the following way: According to a preset index threshold and the vegetation growth index, pixels in the well site area are divided into vegetation and bare land, and are assigned values ​​of 1 and 0 respectively to obtain an assignment result; The assignment results of different time phases were subtracted to obtain three types of changes: vegetation changing to bare land, no change, and bare land changing to vegetation.

7. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 5 is characterized in that: The quantitative evaluation of the degree of change in vegetation growth was carried out by the following methods: The vegetation growth indexes at different phases are subtracted to obtain the subtraction results; The degree of change in vegetation growth at the well site is determined based on a preset change threshold and the difference result; wherein the degree of change in vegetation growth includes three levels: worsening growth, no significant change in growth, and improving growth.

8. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 5 is characterized in that: The evaluation of vegetation restoration at the well site where the oil and gas facilities have been withdrawn based on the changes includes: Selecting areas in the well site where the oil and gas facilities have been removed where the vegetation change type is from bare land to vegetation as vegetation restoration areas, and selecting areas in the well site where the oil and gas facilities have been removed where the vegetation growth has improved as growth restoration areas; Combined with the vector boundaries of the well site, the proportion of the growth recovery area and the vegetation recovery area in the well site where the oil and gas facilities have exited is calculated, and the recovery status of the well site is evaluated as recovered, recovering, or not recovered based on a preset proportion threshold.

9. The method for monitoring and evaluating vegetation restoration after oil and gas well site exit according to claim 8 is characterized in that: Before calculating the ratio of the growth recovery area and the vegetation recovery area in the well site, the method further includes: The corresponding pixels of the ternary map where the change results are growth recovery areas and vegetation recovery areas are summed, and the duplicate pixels of the growth recovery areas and vegetation recovery areas are removed.

10. A monitoring and evaluation device for vegetation restoration after oil and gas well site exit, characterized in that: include: A preprocessing module is used to perform image preprocessing on the remote sensing images of the study area acquired at different time phases to obtain preprocessed remote sensing images; An identification module is used to compare the pre-processed remote sensing images of different phases based on pre-established remote sensing interpretation marks of different types of well sites to determine the well site where the oil and gas facilities have exited; A calculation module, configured to calculate vegetation growth indexes at different time phases for the well site where the oil and gas facilities have exited, based on the pre-processed remote sensing images; A classification module is used to determine the change of the vegetation growth index in the well site before and after the oil and gas facilities are withdrawn according to the vegetation growth index in different time phases; An evaluation module is used to evaluate the vegetation restoration status of the well site where the oil and gas facilities have withdrawn based on the changes.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for monitoring and evaluating vegetation restoration after oil and gas well site exit is implemented as described in any one of claims 1 to 9.

12. An electronic device, characterized in that: The processor, the communication interface, the memory and the communication bus are connected to each other via the communication bus. Memory for storing computer programs; The processor is configured to implement the oil and gas well site exit vegetation restoration monitoring and evaluation method as described in any one of claims 1 to 9 when executing the program stored in the memory.

Images