Method and device for determining exploration right reduction block, electronic equipment and computer program product

Abstract

The application discloses a method and device for determining a block of exploration right reduction, electronic equipment and computer program product. The method comprises: discretizing a block of exploration right to be reduced into a two-dimensional grid matrix, wherein the two-dimensional grid matrix comprises a plurality of grids with the same area; determining a reservation priority of each grid according to geological potential and surface resistance, wherein the geological potential is used to quantify the exploration value of the grid and is positively correlated with the reservation priority, and the surface resistance is used to quantify the ground exploration resistance of the grid and is negatively correlated with the reservation priority; selecting a plurality of candidate grids meeting a target reduction area in the plurality of grids in ascending order of the reservation priority; and performing morphological processing on the plurality of candidate grids to obtain the block of exploration right reduction, wherein the morphological processing is at least used to eliminate holes in a connected domain formed by the plurality of candidate grids. The application solves the technical problem of lack of scientific and quantitative standard in a traditional exploration right reduction scheme.

Description

Technical Field

[0001] This application relates to the field of geographic information analysis, and more specifically, to a method, apparatus, electronic device, and computer program product for determining exploration rights reduction blocks. Background Technology

[0002] The oil and gas exploration rights are subject to a "hard withdrawal" constraint mechanism. Its core requirement is that a certain proportion of the exploration area must be withdrawn after each exploration cycle expires. After determining the withdrawal area quota, accurately delineating the withdrawal boundaries within the block is a core technical requirement for mineral rights evaluation and management. Its core constraints include: first, a hard area constraint, meaning the withdrawal area must fully match the withdrawal requirements, neither exceeding nor falling short; second, an optimal asset constraint, requiring the preservation of high-potential, high-value exploration assets to the greatest extent possible, prioritizing the withdrawal of inferior blocks; and third, ensuring the integrity of the withdrawn blocks as much as possible, as fragmentation hinders subsequent exploration rights transfers and large-scale exploration and mining.

[0003] However, the traditional process of reducing exploration rights relies on experience-based judgments, lacks scientific quantitative standards, and results in irregular shapes of the reduced blocks.

[0004] There is currently no effective solution to the problem that traditional exploration rights reduction schemes lack scientific and quantitative standards. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and computer program product for determining exploration rights reduction blocks, in order to at least solve the technical problem that traditional exploration rights reduction schemes lack scientific quantitative standards.

[0006] According to one aspect of the embodiments of this application, a method for determining exploration right reduction blocks is provided, comprising: discretizing the exploration right block to be reduced into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes: multiple grids with the same area; determining the retention priority of each grid based on geological potential and surface resistance, wherein the geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority, and the surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority; selecting multiple candidate grids that meet the target reduction area in ascending order of the retention priority from the multiple grids; performing morphological processing on the multiple candidate grids to obtain the exploration right reduction block, wherein the morphological processing is at least used to eliminate holes in the connected domain formed by the multiple candidate grids.

[0007] Optionally, determining the retention priority of each grid based on geological potential and surface resistance includes: obtaining a geological potential score for each grid; obtaining a surface resistance score for each grid; adjusting the relative weight between the geological potential score and the surface resistance score of the same grid using a pre-set balance coefficient; and determining the retention priority based on the ratio of the adjusted geological potential score to the adjusted surface resistance score.

[0008] Optionally, obtaining the geological potential score for each grid includes: obtaining geological index scores for each grid based on multiple geological evaluation indicators, wherein each geological evaluation indicator is a single dimension for evaluating the geological potential; weighting and summing the multiple geological index scores according to the geological weights pre-set for each geological evaluation indicator to obtain a comprehensive geological score for each grid; and adding a confidence penalty factor to the comprehensive geological score of the grid based on the Euclidean distance between the grid and the nearest exploration well to obtain the geological potential score, wherein the confidence penalty factor is negatively correlated with the Euclidean distance, and the geological potential score is positively correlated with the confidence penalty factor.

[0009] Optionally, obtaining the surface resistance score for each grid includes: obtaining a surface resistance score for each grid based on multiple surface resistance indicators, wherein each surface resistance indicator is a single dimension for evaluating surface resistance; weighting and summing the multiple surface resistance scores according to the surface weights pre-set for each surface resistance indicator to obtain a comprehensive surface resistance score for each grid; adding a veto factor to the comprehensive surface resistance score of the grid based on the positional relationship between the grid and a pre-set prohibited exploration block to obtain the surface resistance score, wherein the veto factor is at its maximum value when the grid's position coincides with the prohibited exploration block, and the veto factor is positive when the grid's position does not coincide with the prohibited exploration block, and the surface resistance score is positively correlated with the veto factor.

[0010] Optionally, selecting multiple candidate grids that meet the target reduction area in ascending order of retention priority from the multiple grids includes: selecting a preset number of initial grids in ascending order of retention priority from the multiple grids to obtain a candidate set; selecting seed grids in ascending order of retention priority from the multiple initial grids recorded in the candidate set to obtain a seed set, wherein the Euclidean distance between any two seed grids in the seed set is not less than a preset repulsion radius; taking each seed grid as the iteration starting point of the candidate grid, iteratively selecting the adjacent grid with the lowest retention priority as the candidate grid from multiple adjacent grids adjacent to the candidate grid, until the total area of ​​the candidate grids is not less than the target reduction area.

[0011] Optionally, taking each seed grid as the starting point for the iteration of the candidate grid, among multiple adjacent grids adjacent to the candidate grid, iteratively selecting the adjacent grid with the lowest retention priority as the candidate grid until the total area of ​​the candidate grid is not less than the target reduction area includes: determining the seed grid as the candidate grid; selecting adjacent grids that do not belong to the candidate grid among multiple grids adjacent to the candidate grid to obtain an adjacent grid set; determining the adjacent grid with the lowest retention priority in the adjacent grid set as the candidate grid and calculating the total area of ​​the candidate grid; if the total area of ​​the grid is less than the target reduction area, re-determining the adjacent grid set until the total area of ​​the candidate grid is not less than the target reduction area.

[0012] Optionally, performing morphological processing on multiple candidate grids to obtain exploration right reduction blocks includes: eliminating holes in the connected domains established based on the multiple candidate grids to obtain candidate reduction blocks, wherein each connected domain includes multiple adjacent candidate grids; extracting the closed contour of the candidate reduction blocks using a neighborhood tracking algorithm to obtain a first contour point set; thinning the inflection points of the first contour point set to obtain a second contour point set for representing the inflection points of a regular contour graphic; adjusting the second contour point set based on the deviation between the area of ​​the regular contour graphic enclosed by the second contour point set and the target reduction area to obtain the exploration right reduction block.

[0013] According to another aspect of the embodiments of this application, an apparatus for determining exploration right reduction blocks is also provided, comprising: a discretization module, used to discretize the exploration right block to be reduced into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes multiple grids of the same area; a determination module, used to determine the retention priority of each grid based on geological potential and surface resistance, wherein the geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority, and the surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority; a selection module, used to select multiple candidate grids that meet the target reduction area from the multiple grids in ascending order of the retention priority; and a processing module, used to perform morphological processing on the multiple candidate grids to obtain the exploration right reduction block, wherein the morphological processing is at least used to eliminate holes in the connected domains formed by the multiple candidate grids.

[0014] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the above-described method for determining exploration right withdrawal blocks.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the above-described method for determining exploration right reduction blocks.

[0016] In the embodiments described above, the exploration rights blocks to be degraded are discretized into a two-dimensional matrix composed of grids of equal area. The retention priority of each grid is calculated based on its geological potential and surface resistance. Higher geological potential corresponds to a stronger retention intention, while greater surface resistance corresponds to a weaker retention intention. A quantitative evaluation system reflecting the trade-off between exploration value and engineering difficulty can be constructed based on geological potential and surface resistance. On this basis, candidate grids are selected sequentially from low to high retention priority to ensure that, while meeting the target reduction area, blocks with the lowest exploration value and highest resistance are preferentially eliminated, thus achieving exploration... Resource loss is minimized; subsequently, morphological processing is performed on the selected candidate grid set to eliminate isolated grids and internal holes in connected domains, ensuring spatial continuity and geometric integrity of the retreat blocks, and avoiding blurred ownership boundaries or management failures due to fragmentation or internal voids; the exploration right retreat process is freed from experience dependence, achieving learnable quantification, ensuring regular block shape, solving the technical problem of the lack of scientific quantitative standards in traditional exploration right retreat schemes, and achieving the technical effect of improving the objectivity, accuracy and feasibility of retreat decisions, providing quantifiable, reproducible and manageable technical support for dynamic adjustment of mining rights. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for determining exploration rights reduction blocks is shown.

[0019] Figure 2 This is a flowchart of a method for determining exploration right reduction blocks according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram of a method for determining candidate meshes according to an embodiment of this application;

[0021] Figure 4 This is a flowchart of a method for generating the retreat boundary of oil and gas exploration rights according to an embodiment of this application;

[0022] Figure 5 This is a schematic diagram of an automatic generation system for exploration right retreat boundaries according to an embodiment of this application;

[0023] Figure 6 This is a schematic diagram of a device for determining exploration rights reduction blocks according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application 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 this application 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.

[0026] To address the problems existing in related technologies, embodiments of this application provide a method for determining exploration right withdrawal blocks. This method can be implemented in... Figure 1 The computer terminal shown is explained below.

[0027] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a method for determining exploration right withdrawal blocks is shown. Figure 1 As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission module 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0028] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0029] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for determining exploration right reduction blocks in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the above-mentioned method for determining exploration right reduction blocks. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0030] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0031] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0032] This application constructs a multi-dimensional coupled evaluation system that takes into account geological evaluation, data confidence, economic indicators and ecological compliance requirements. It accurately and automatically generates the outer boundary of the mining rights to be withdrawn, reduces the error of manually delineating the boundary, achieves the global optimization of the withdrawal plan, and preserves high-quality exploration assets to the maximum extent.

[0033] It should be noted here that, in some optional embodiments, the above... Figure 1 The computer terminal shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned computer terminal.

[0034] Under the above operating environment, this application provides an embodiment of a method for determining exploration right reduction blocks. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] Figure 2 This is a flowchart of a method for determining exploration right reduction blocks according to an embodiment of this application, as shown below. Figure 2 As shown, the method includes the following steps:

[0036] Step S202: Discretize the exploration rights block to be degraded into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes multiple grids with the same area;

[0037] Step S204: Based on geological potential and surface resistance, determine the retention priority of each grid. Geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority. Surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority.

[0038] Step S206: Select multiple candidate grids that meet the target reduction area from multiple grids in ascending order of retention priority;

[0039] Step S208: Morphological processing is performed on multiple candidate grids to obtain exploration right reduction blocks, wherein the morphological processing is used at least to eliminate holes in the connected domain formed by multiple candidate grids.

[0040] In the embodiments described above, the exploration rights blocks to be degraded are discretized into a two-dimensional matrix composed of grids of equal area. The retention priority of each grid is calculated based on its geological potential and surface resistance. Higher geological potential corresponds to a stronger retention intention, while greater surface resistance corresponds to a weaker retention intention. A quantitative evaluation system reflecting the trade-off between exploration value and engineering difficulty can be constructed based on geological potential and surface resistance. On this basis, candidate grids are selected sequentially from low to high retention priority to ensure that, while meeting the target reduction area, blocks with the lowest exploration value and highest resistance are preferentially eliminated, thus achieving exploration... Resource loss is minimized; subsequently, morphological processing is performed on the selected candidate grid set to eliminate isolated grids and internal holes in connected domains, ensuring spatial continuity and geometric integrity of the retreat blocks, and avoiding blurred ownership boundaries or management failures due to fragmentation or internal voids; the exploration right retreat process is freed from experience dependence, achieving learnable quantification, ensuring regular block shape, solving the technical problem of the lack of scientific quantitative standards in traditional exploration right retreat schemes, and achieving the technical effect of improving the objectivity, accuracy and feasibility of retreat decisions, providing quantifiable, reproducible and manageable technical support for dynamic adjustment of mining rights.

[0041] In step S202 above, the exploration rights block to be degraded is divided into a two-dimensional grid matrix. This matrix consists of multiple grid cells with the same area. Each grid cell serves as the basic unit for spatial discretization of the block, ensuring that the entire exploration rights block is uniformly and non-overlappingly divided into several identifiable discrete units in the spatial dimension, thereby providing a unified spatial reference framework for the subsequent quantitative processing of the degraded block.

[0042] Optionally, discretizing the exploration rights block to be degraded into a two-dimensional grid matrix includes: setting the spatial resolution. The exploration rights blocks to be degraded are discretized into a two-dimensional grid matrix. Grids that fall completely outside the blocks are removed to obtain the effective grid matrix. The two-dimensional grid matrix comprises multiple grids, and the area of ​​each complete grid is... For grids that intersect with the block boundary, the effective area is calculated according to the overlap ratio with the block to ensure the accuracy of area calculation.

[0043] In step S204 above, the retention priority is used to characterize the tendency of a grid to be included in the exploration right reduction block, wherein the lower the retention priority value, the higher its priority for reduction.

[0044] In step S204 above, the exploration value of each grid is quantified based on geological potential. Geological potential, as an indicator reflecting the underground natural hydrogen enrichment capacity, directly determines the priority level of the grid in resource evaluation. At the same time, the difficulty of surface exploration implementation of each grid is quantified based on surface resistance. Surface resistance, as an indicator reflecting the obstacles to exploration operations posed by topography, vegetation, infrastructure, or environmental limitations, directly reduces the retention priority of the grid. By using geological potential and surface resistance as positive and negative influencing factors respectively, the retention priority of each grid is comprehensively determined.

[0045] Optionally, for each valid grid Calculate its dynamic retention priority. The calculation logic is as follows: the priority of retaining the evaluation grid is positively correlated with the geological potential and negatively correlated with the difficulty of surface construction. The lower the score value, the higher the priority of the grid to be included in the reduction range.

[0046] In step S206 above, multiple grids are selected in ascending order of retention priority, that is, grids with lower priority are included in the selection range before grids with higher priority; then, candidate grids that meet the target set reduction area requirements are selected from these sorted grids to ensure that the set of selected grids can meet the preset set reduction area conditions, thereby directly realizing the precise selection and control of the grid set.

[0047] In step S208 above, morphological processing is performed on multiple candidate meshes to eliminate isolated meshes and ensure that only blocks with spatial connectivity with adjacent meshes are retained. At the same time, holes in the connected domains formed by these candidate meshes are eliminated to make the overall block structure more closed and complete, thereby achieving spatial morphological optimization of the original candidate mesh set.

[0048] In step S208 above, morphological processing is also used to eliminate isolated meshes.

[0049] As an optional embodiment, determining the retention priority of each grid based on geological potential and surface resistance includes: obtaining the geological potential score of each grid; obtaining the surface resistance score of each grid; adjusting the relative weight between the geological potential score and the surface resistance score of the same grid using a pre-set balance coefficient; and determining the retention priority based on the ratio of the adjusted geological potential score to the adjusted surface resistance score.

[0050] The embodiments described above in this application discretize the exploration rights block to be degraded into multiple grids of equal area, and obtain the geological potential score and surface resistance score for each grid. By combining these scores with a pre-set balance coefficient to adjust their relative weights, a retention priority quantification model is constructed based on the ratio of the adjusted geological potential score to the adjusted surface resistance score. This enables precise expression and dynamic adjustment of the nonlinear relationship between the exploration value and surface resistance of each grid. The determination of retention priority no longer relies on subjective experience or fixed thresholds, but is based on a configurable and calibrable mathematical ratio. This ensures that when subsequent candidate grids are selected in ascending order of priority and morphological processing is performed, the delineation of the degraded blocks can both fully retain high-exploration-value blocks and effectively avoid high-resistance blocks. This significantly improves the scientific rigor, adaptability, and operability of the degraded scheme, solving the problem of the lack of scientific quantitative standards in traditional exploration rights degraded schemes. It avoids the defects of rough retention priority assessment and unreasonable block selection caused by the lack of quantification and weight adjustment mechanisms for geological potential and surface resistance, achieving refined and intelligent decision-making for exploration rights degraded.

[0051] As an optional example, the formula for calculating priority is: ,in, For grid Priority of retention; For grid Geological potential score; For grid Surface resistance score; This is a balancing coefficient used to adjust the relative weight of geological value and construction resistance. The default value is 1, but it can be adjusted flexibly according to the actual situation.

[0052] As an optional embodiment, obtaining the geological potential score for each grid includes: obtaining the geological index score for each grid based on multiple geological evaluation indicators, wherein each geological evaluation indicator is a single dimension for evaluating geological potential; weighting and summing the multiple geological index scores according to the geological weights set for each geological evaluation indicator in advance to obtain the comprehensive geological score for each grid; adding a confidence penalty factor to the comprehensive geological score of the grid based on the Euclidean distance between the grid and the nearest exploration well to obtain the geological potential score, wherein the confidence penalty factor is negatively correlated with the Euclidean distance, and the geological potential score is positively correlated with the confidence penalty factor.

[0053] The embodiments described above in this application obtain geological index scores for each grid based on multiple single-dimensional geological evaluation indicators. These scores are then weighted and summed using pre-set geological weights for each indicator to construct a comprehensive geological score reflecting multi-dimensional geological characteristics. Furthermore, a negatively correlated confidence penalty factor is introduced based on the Euclidean distance between the grid and the nearest exploration well to spatially correct the comprehensive geological score. This causes the geological potential score to decrease as the well distance increases, thereby transforming geological potential assessment from a single empirical judgment to a data-driven, spatially weighted, and scientifically quantifiable approach. This solves the problem of traditional exploration right withdrawal schemes lacking scientific quantitative standards, effectively compensates for evaluation biases caused by relying solely on the generalized concept of geological potential, significantly improves the accuracy and spatial rationality of retention priority calculations, and ensures that the withdrawal block selection process achieves optimal decision-making while balancing exploration value and data reliability.

[0054] Optionally, geological evaluation indicators include: source rock organic matter abundance, reservoir porosity, caprock thickness, resource abundance, discovered reserve size, seismic data quality, and well logging data continuity.

[0055] As an alternative example, the geological potential score is used to quantify the exploration and development value of a grid, and to compress the geological potential of each grid area through a set confidence penalty factor. The calculation formula is as follows: ,in, For grid Geological potential score; K is the number of geological evaluation indicators; For the first k The geological weights of the geological evaluation indicators meet the following requirements. For the first k Geological evaluation indicators in the grid The normalized value; The confidence penalty factor is exponentially decayed based on the Euclidean distance between the grid and the nearest well.

[0056] It should be noted that the further away from the exploration well, the more geological blind areas there are. The smaller the value, the more its geological potential value is forcibly compressed, and it is given priority in the scope of reduction.

[0057] Optionally, the confidence penalty factor is calculated using the following formula: ,in, a The attenuation coefficient; The Euclidean distance from the grid to the nearest well; The economic control radius for exploration wells.

[0058] As an optional embodiment, obtaining the surface resistance score for each grid includes: obtaining the surface resistance score for each grid based on multiple surface resistance indicators, wherein each surface resistance indicator is a single dimension for evaluating surface resistance; weighting and summing the multiple surface resistance scores according to the surface weights set for each surface resistance indicator in advance to obtain the comprehensive surface resistance score for each grid; adding a veto factor to the comprehensive surface resistance score of the grid based on the positional relationship between the grid and a pre-set prohibited exploration block to obtain the surface resistance score, wherein the veto factor is maximized when the grid's position coincides with the prohibited exploration block, and is positive when the grid's position does not coincide with the prohibited exploration block, and the surface resistance score is positively correlated with the veto factor.

[0059] The embodiments described above in this application discretize the exploration rights block to be degraded into a two-dimensional matrix of multiple equal-area grids. For each grid, a quantitative evaluation is performed on surface resistance indicators from multiple single dimensions. A weighted sum is then calculated based on pre-set surface weights corresponding to each indicator to form a comprehensive surface score reflecting the combined influence of multiple factors. Furthermore, considering the spatial relationship between the grids and pre-defined prohibited exploration blocks, a veto factor is introduced. When a grid overlaps with a prohibited exploration block, this factor is maximized to forcibly block exploration possibilities; when they do not overlap, a positive value is taken to preserve relative resistance differences. This ensures that the surface resistance score is positively correlated with this factor, thereby achieving a comprehensive evaluation of the surface resistance. A refined and hierarchical model of surface exploration resistance is developed. After adjusting the weights of the surface resistance score and the geological potential score using a balancing coefficient, the retention priority of the grid is jointly determined. This ensures that the priority calculation fully integrates geological value and actual exploration constraints, solving the problem of the lack of scientific quantitative standards in traditional exploration right reduction schemes. After selecting candidate grids in ascending order of retention priority and performing morphological processing, reduction blocks that meet actual control requirements, avoid mandatory exploration bans, and possess spatial continuity and reasonable morphology are generated. This effectively avoids the shortcomings of traditional methods, such as coarse surface resistance assessment and neglect of mandatory constraints leading to inaccurate reduction decisions, thus improving the scientificity, compliance, and operability of exploration right adjustments.

[0060] Optionally, if the grid location does not coincide with a prohibited survey block, the veto factor is set to 1.

[0061] Optionally, surface resistance indicators include: slope resistance, pipeline distance resistance, and land use resistance.

[0062] As an alternative example, surface resistance scoring is used to quantify the surface exploration and development costs of a grid, while simultaneously enforcing priority reduction of ecological redline blocks through a veto parameter. The calculation formula is as follows: , , , These are the surface weights for slope resistance, pipeline distance resistance, and land use resistance, respectively, satisfying... ; For grid The normalized value of the slope; the steeper the slope, the higher the resistance value. For grid The normalized value of the distance to the nearest oil and gas infrastructure (gathering and transmission pipelines, access roads, existing well sites, etc.). The greater the distance, the higher the resistance value. For grid Normalized values ​​of resistance for land use types: resistance values ​​for forest land, cultivated land, and built-up areas are higher than those for wasteland, desert, and Gobi. To represent a grid The ecological red line is a veto factor, such as the grid system. In areas where exploration is legally prohibited, such as ecological protection red lines, nature reserves, and drinking water source areas, Pick ,at this time The grid Forced to be included in the reduction scope; when there is no overlap This does not affect the calculation.

[0063] As an optional embodiment, selecting multiple candidate grids that meet the target reduction area in ascending order of retention priority from multiple grids includes: selecting a preset number of initial grids in ascending order of retention priority from multiple grids to obtain a candidate set; selecting seed grids in ascending order of retention priority from the multiple initial grids recorded in the candidate set to obtain a seed set, wherein the Euclidean distance between any two seed grids in the seed set is not less than a preset repulsion radius; taking each seed grid as the iteration starting point for candidate grids, iteratively selecting the adjacent grid with the lowest retention priority as a candidate grid from multiple adjacent grids adjacent to the candidate grid, until the total area of ​​the candidate grids is not less than the target reduction area.

[0064] In the embodiments described above, the exploration rights block to be degraded is discretized into a two-dimensional grid matrix, and the retention priority of each grid is calculated based on geological potential and surface resistance. A candidate set is constructed by selecting a preset number of initial grids in ascending priority order. Further, multiple seed grids are selected from the candidate set in ascending priority order, ensuring that the Euclidean distance between any two sub-grids is not less than a preset repulsion radius, thereby forcing the spatial dispersion of the initial sampling points. Subsequently, starting from various sub-grids, the adjacent grids are iteratively selected level by level along the adjacent grids to expand the area, allowing the degraded block to be expanded from multiple... Discrete starting points adaptively spread according to priority gradients until the accumulated area meets the target reduction area requirement. Finally, morphological processing is used to eliminate isolated grids and holes in connected domains, forming a structurally complete, uniformly distributed, and precisely sized reduction block. This avoids the defects of existing technologies that rely solely on priority ranking, resulting in excessive aggregation of candidate grids and fragmented or discontinuous reduction block shapes. It solves the problem of the lack of scientific quantitative standards in traditional exploration right reduction schemes, achieving balanced spatial coverage of the reduction range and accurate achievement of the area target, thus improving the scientificity and feasibility of exploration right adjustment schemes.

[0065] Optionally, the selection of the seed set specifically includes: extraction and retention priority. The smallest N grids form a candidate set. A spatial non-maximum suppression algorithm is introduced to generate a spatially uniform initial set of inferior seeds, preventing excessive concentration of growth blocks in later stages due to seed grid clustering. The candidate set is then sorted according to... Sort the grids in ascending order (with the grids having the lowest scores at the top), take the top-ranked grid as the seed point, and add it to the initial seed set. Candidates whose Euclidean distance from the seed point is less than the preset rejection radius are removed. All grids, where the repulsion radius can be flexibly adjusted according to the block size and actual needs.

[0066] Figure 3 This is a schematic diagram of a method for determining candidate meshes according to an embodiment of this application, as shown below. Figure 3 As shown, taking each seed grid as the starting point for the iteration of candidate grids, among multiple adjacent grids adjacent to the candidate grid, the adjacent grid with the lowest retention priority is iteratively selected as the candidate grid, until the total area of ​​the candidate grids is not less than the target reduction area, including:

[0067] Step S302: Determine the seed mesh as the candidate mesh;

[0068] Step S304: Among the multiple grids adjacent to the candidate grid, select the adjacent grids that do not belong to the candidate grid to obtain the set of adjacent grids;

[0069] Step S306: Select the adjacent grid with the lowest priority from the adjacent grid set as the candidate grid, and calculate the total area of ​​the candidate grid.

[0070] Step S308: If the total area of ​​the grid is less than the target reduction area, redetermine the set of adjacent grids until the total area of ​​the candidate grids is not less than the target reduction area.

[0071] In the embodiments described above, the exploration rights block to be degraded is discretized into a two-dimensional grid matrix. After determining the retention priority of each grid based on geological potential and surface resistance, multiple seed grids with the lowest retention priority and spacing that meets the rejection radius are used as the starting point for expansion. The process iteratively expands to the adjacent unselected grids, selecting the adjacent grids with the lowest retention priority. This ensures that the candidate grid set continuously spreads along the priority decreasing path until the cumulative area is not less than the target reduction area. This process avoids area deviation and morphological fragmentation caused by discontinuous selection through local search of adjacency relationships and priority-driven greedy selection. At the same time, through morphological processing such as removing isolated grids and filling holes, the final reduction block has good connectivity and boundary regularity. Thus, under the premise of accurately meeting the area constraint, the disturbance to high-value exploration blocks is minimized, achieving scientific, systematic, and morphologically controllable delineation of exploration rights reduction blocks. This solves the problem of the lack of scientific quantitative standards in traditional exploration rights reduction schemes.

[0072] As an optional example, candidate grids are determined by starting with each seed grid and using the target setback area quota (i.e., the target setback area). As a hard constraint, a strict adaptive space boundary automatic growth from inferior to superior is achieved through a min-heap priority queue, and the following operations are performed:

[0073] Data structure initialization: Establish a PQ min-heap priority queue (such as an adjacency grid set), with the sorting rule being priority preservation. Sort in ascending order to ensure that the top of the heap is always the lowest priority grid in the current queue;

[0074] Queue initialization: Initialize the seed set Push all seed points and their four neighboring valid grids into PQ, mark the grid's enqueue status, and avoid duplicate enqueueing;

[0075] State initialization: Initialize the current cumulative reduction area (e.g., the total area of ​​the candidate grid). ): Initialize the degenerate connected components to be empty sets;

[0076] Boundary adaptive growth cycle: when During this time, continuously perform the following operations: pop the grid with the lowest current priority from the top of PQ. The candidate meshes are merged into the reduced connected components (i.e., the adjacent meshes with the lowest retention priority in the set of adjacent meshes are determined as candidate meshes), and their unvisited adjacent meshes are pushed into PQ, and the total area of ​​the candidate meshes is accumulated: ,in, The total area of ​​the candidate meshes obtained in the previous iteration, once The loop is interrupted, the boundary stops growing, and eventually a receding block that satisfies the area hard constraint is obtained.

[0077] As an optional embodiment, morphological processing of multiple candidate grids to obtain exploration right reduction blocks includes: eliminating holes in connected domains established based on multiple candidate grids to obtain candidate reduction blocks, wherein each connected domain includes multiple adjacent candidate grids; extracting the closed contour of the candidate reduction blocks using a neighborhood tracking algorithm to obtain a first contour point set; thinning the inflection points of the first contour point set to obtain a second contour point set for representing the inflection points of regular contour graphics; adjusting the second contour point set based on the deviation between the area of ​​the regular contour graphics enclosed by the second contour point set and the target reduction area to obtain the exploration right reduction block.

[0078] In the embodiments described above, the exploration rights block to be degraded is discretized into a two-dimensional grid matrix of equal area. The retention priority of each grid is comprehensively evaluated based on geological potential and surface resistance. Candidate grid sets matching the target reduction area are selected in ascending order of priority. Morphological processing is used to eliminate holes in connected domains to form continuous candidate reduction blocks. Then, a neighborhood tracking algorithm is used to accurately extract the closed boundary of the block, generating a first contour point set. The point set is then simplified using an inflection point thinning algorithm, retaining key inflection points to construct a second contour point set with approximately regular contours. Finally, the position or number of the second contour point set is dynamically adjusted based on the deviation between the area enclosed by the regular contour and the target reduction area until the area error meets a preset tolerance. This achieves the dual goals of regularizing the boundary of the reduction block and accurately matching the area, effectively avoiding the technical defects of irregular boundaries and difficulty in accurately controlling the area caused by the discrete distribution of candidate grids. It improves the scientific, standardized, and executable nature of exploration rights reduction operations and solves the problem of the lack of scientific quantitative standards in traditional exploration rights reduction schemes.

[0079] As an optional example, morphological processing is performed on multiple candidate grids to obtain exploration right retreat blocks. Morphological processing and boundary regularization of the retreating connected components can directly output vectorized orthogonal boundary coordinates conforming to the target specifications. Specifically, this includes: outer contour extraction, using the Moore neighborhood tracking algorithm to extract the outer contour of the retreat blocks to obtain an initial contour point set; and inflection point thinning, using the Douglas-Peucker algorithm to thin the initial contour point set, with the thinning threshold set to 1 times the spatial resolution by default. The process involves: eliminating jagged redundant inflection points while retaining core boundary inflection points; orthogonalization processing, performing orthogonal snapping to force all contour segments to align with the north-south or east-west coordinate axes, ensuring that the lines connecting all boundary points are horizontal or vertical broken lines, conforming to the legal specifications for mining rights boundaries; area verification and fine-tuning, recalculating the area of ​​the orthogonalized boundary, and controlling the error within a preset range by fine-tuning the position of the boundary segments if there is a deviation from the target reduction area; output: exporting a coordinate table in a format that meets the target specifications, which can be directly used for mining rights reduction operations.

[0080] The embodiments described above in this application pioneer a dual-dimensional retention priority model encompassing geology and engineering. This model couples underground geological potential, data confidence, surface construction costs, and ecological red line veto factors into a unified evaluation system. This ensures that priority for withdrawal is given to "geological blind areas without wells or seismic activity, high-construction-cost blocks, and ecological red line prohibited areas." While meeting withdrawal requirements, it maximizes the retention of high-quality exploration assets, reduces subsequent exploration and development costs for enterprises, and achieves a multi-objective global optimum of withdrawal compliance, asset optimization, and cost control. Furthermore, it can flexibly adapt to exploration rights blocks of different sizes and geological conditions. Evaluation indicators, weights, resolution, and other parameters can all be customized according to business needs. This method is not only applicable to the generation of withdrawal boundaries for oil and gas exploration rights but can also be directly extended to withdrawal scenarios for exploration and mining rights of other minerals such as coal and metallic minerals, as well as spatial planning scenarios such as ecological protection red line avoidance and construction land boundary delineation, demonstrating a wide range of applications.

[0081] Figure 4 This is a schematic diagram of a method for generating oil and gas exploration right retreat boundaries according to an embodiment of this application, as shown below. Figure 4 As shown, taking an oil and gas exploration rights block in a basin as the implementation target, the exploration period of this block is about to expire, and according to the requirements, a 20% reduction in area is required. The total area of ​​the block is 1000 km², and the target reduction area is: Specifically, it includes the following steps:

[0082] Step 1: Grid the evaluation units.

[0083] Obtain the official vector polygon boundary (SHP format) of the exploration right block, and set the spatial resolution based on the block size. Area of ​​a single complete grid .

[0084] Using a GIS rasterization tool, the blocks are discretized into a 1000×1000 two-dimensional grid matrix. Grids that fall completely outside the blocks are removed to obtain the effective grid matrix. For grids that intersect with block boundaries, the effective area is calculated based on the overlap ratio with the block to ensure the accuracy of area calculation.

[0085] Step 2: Calculation of the priority of two-dimensional preservation of geological surface.

[0086] For each valid grid cell, calculate the dynamic retention priority. Among them, the balance coefficient Choosing 1 achieves a linear balance between geological value and construction resistance.

[0087] Table 1 is a geological potential rating according to an embodiment of this application. The calculation is illustrated in Table 1, which selects four core geological evaluation indicators to calculate the geological potential score.

[0088] Table 1

[0089]

[0090] Optionally, geological potential scoring Confidence penalty factor The parameter settings include: an attenuation coefficient of 0.5 and an economic control radius for exploration wells. The calculation formula is: If there are exploratory wells within the grid, , The geological value remains unchanged; if the grid distance is 6000m from the nearest exploration well, The geological value was significantly compressed, and these areas were prioritized for inclusion in the regression range. The final calculated geological potential value for each grid is: .

[0091] Table 2 shows a surface resistance rating according to an embodiment of this application. The calculation is illustrated in Table 2, which selects three core surface evaluation indicators to calculate the surface resistance score.

[0092] Table 2

[0093]

[0094] Optionally, if the grid overlaps with a national nature reserve or ecological protection red line, the veto factor value is: ,otherwise .

[0095] Optionally, the surface resistance score for each grid is: .

[0096] Based on the above results, the retention priority of each valid grid is calculated. Among them, the lower the score, the worse the grid quality, and the more likely it is to be included in the reduction range.

[0097] Step 3: Spatial Non-Maximum Suppression (NMS) Multi-Source Seed Extraction.

[0098] Optionally, select a retention priority. The candidate set is composed of the top 200 smallest grid cells, and a preset rejection ratio is set. (10 times grid resolution), perform spatial nonmaximum suppression algorithm, specifically including:

[0099] Candidate set by Sort in ascending order; take the first grid in the sorted order as the seed point and add it to the seed set; remove all grids in the candidate set that are less than 1000m away from the seed point; repeat the above steps until the candidate set is empty, and finally obtain 12 initial inferior seed points with uniform spatial distribution.

[0100] Step 4: Min-heap priority queue adaptive boundary growth.

[0101] Optionally, initialize a min-heap priority queue PQ, with the following sorting rule: Sort in ascending order; push the 12 seed points and their four neighboring valid meshes into PQ, and mark the mesh enqueue status; initialize. Target reduction area ; Execute an adaptive growth cycle: continuously pop the worst mesh from the top of the PQ heap, incorporate it into the decaying connected domain, accumulate the area, and push its unvisited four neighboring meshes into the PQ.

[0102] Optionally, determine whether the current area is smaller than the target area. When, continue executing step S3, when When the area reached 200.08 km², a hard interruption was triggered, stopping the growth. The final area error was 0.04%, which fully met the area constraint.

[0103] Step 5: Morphological smoothing and compliant vectorization output.

[0104] Optionally, a 3×3 rectangular kernel closing operation is performed on the binary matrix of the retreating connected component to fill in the two internal micro-holes and eliminate internal islands; the Moore neighborhood tracking algorithm is used to extract the outer contour of the retreating block to obtain the initial contour point set; the Douglas-Peucker algorithm is used to thin out the contour points, with a thinning threshold set to 100m, reducing the initial 2862 contour points to 36 core inflection points to eliminate jagged boundaries; orthogonal snapping is performed to forcibly align all contour line segments to the due east, due west, due south, and due north directions to generate orthogonalized polyline boundaries; the area of ​​the orthogonalized boundaries is checked, and the positions of the two boundary segments are fine-tuned to control the final area error within 0.05%; the "Coordinate Table of Proposed Retreat Blocks" in the 2000 geodetic coordinate system and the SHP format vector file are exported, which can be directly used for mining rights retreat operations.

[0105] Figure 5This is a schematic diagram of an automatic generation system for exploration right retreat boundaries according to an embodiment of this application, as shown below. Figure 5 As shown, this system is deployed on Windows / Linux operating systems and supports integration with mainstream GIS platforms such as ArcGIS and QGIS. It is used to execute the aforementioned method for determining exploration right withdrawal blocks and includes the following functional modules:

[0106] Module 1: Data Preprocessing and Meshing Module. This module is used for inputting data and outputting a valid mesh matrix. Specifically, it acquires the vector polygon boundaries of the exploration rights block to be degraded, integrates geological, surface, and compliance-related basic data, sets the spatial resolution and discretizes the mesh, and generates a valid mesh matrix. This module supports importing exploration right boundary vector data in SHP format, geological and surface raster data in GeoTIFF format, and well and infrastructure point data. It completes coordinate system I, spatial resolution setting, mesh discretization, and generation of the valid mesh matrix.

[0107] Module 2: Grid Priority Calculation Module, used to output the priority matrix. Specifically, it executes a two-dimensional retention priority calculation model, calculates the geological potential value and surface construction resistance of each effective grid, couples the confidence penalty and redline veto factor, and outputs the full grid retention priority matrix. This grid priority calculation module has a built-in standardized two-dimensional retention priority calculation model, supports user-defined evaluation indicators, weights, attenuation coefficients, veto rules, and other parameters, automatically completes the retention priority calculation for the entire grid, and outputs the priority matrix and a visual raster map.

[0108] Module 3: Seed Point Extraction Module, used to generate a uniformly distributed seed point set. Specifically, it filters inferior candidate grids based on retention priority, executes the spatial non-maximum suppression algorithm, and generates an initial set of inferior seeds with a uniform spatial distribution. This seed point extraction module supports user-defined candidate set size and rejection radius, automatically executes the spatial non-maximum suppression algorithm to generate the initial seed point set, and supports manual adjustment and visualization of seed points.

[0109] Module 4: Adaptive Boundary Growth Core Module, used to output the retreat region. Specifically, it executes an adaptive spatial growth loop, using the target retreat area as a hard constraint, to generate retreat blocks that meet the requirements. This adaptive boundary growth core module has a built-in optimized min-heap priority queue data structure, supports user input of target retreat area quotas, automatically executes the adaptive spatial growth loop, displays the cumulative area and growth process in real time, and supports previewing and reverting the growth results.

[0110] Module 5: Boundary Regularization and Output Module. This module performs morphological smoothing, contour extraction, inflection point thinning, and orthogonalization on receding connected components, completes area verification and fine-tuning, and outputs a compliant boundary point coordinate table and accompanying vector files. This module incorporates morphological processing, contour extraction, DP thinning, and orthogonalization tools, supports user-defined thinning thresholds and orthogonalization precision, automatically completes area verification and fine-tuning, and finally outputs a boundary point coordinate table, vector boundary files, and a results report that conform to national standards.

[0111] Figure 6 This is a schematic diagram of a device for determining exploration right reduction blocks according to an embodiment of this application, as shown below. Figure 6 As shown, the system includes: a discretization module 62, used to discretize the exploration right block to be degraded into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes multiple grids with the same area; a determination module 64, used to determine the retention priority of each grid based on geological potential and surface resistance, wherein geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority, and surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority; a selection module 66, used to select multiple candidate grids that meet the target degraded area from the multiple grids in ascending order of retention priority; and a processing module 68, used to perform morphological processing on the multiple candidate grids to obtain the exploration right degraded block, wherein the morphological processing is at least used to eliminate holes in the connected domain formed by the multiple candidate grids.

[0112] It should be noted that the device for determining the exploration right reduction block can be used to execute the method for determining the exploration right reduction block in the embodiments of the present invention. Therefore, the relevant explanations in the above-mentioned method for determining the exploration right reduction block also apply to the device for determining the exploration right reduction block, and will not be repeated here.

[0113] It should be noted that each module in the above-mentioned device for determining the exploration right reduction block can be a program module (for example, a set of program instructions to implement a certain function) or a hardware module. For the latter, it can be manifested in the following forms, but is not limited to them: each of the above modules is manifested as a processor, or the functions of each of the above modules are implemented by a processor.

[0114] In the embodiments described above, the exploration rights blocks to be degraded are discretized into a two-dimensional matrix composed of grids of equal area. The retention priority of each grid is calculated based on its geological potential and surface resistance. Higher geological potential corresponds to a stronger retention intention, while greater surface resistance corresponds to a weaker retention intention. A quantitative evaluation system reflecting the trade-off between exploration value and engineering difficulty can be constructed based on geological potential and surface resistance. On this basis, candidate grids are selected sequentially from low to high retention priority to ensure that, while meeting the target reduction area, blocks with the lowest exploration value and highest resistance are preferentially eliminated, thus achieving exploration... Resource loss is minimized; subsequently, morphological processing is performed on the selected candidate grid set to eliminate isolated grids and internal holes in connected domains, ensuring spatial continuity and geometric integrity of the retreat blocks, and avoiding blurred ownership boundaries or management failures due to fragmentation or internal voids; the exploration right retreat process is freed from experience dependence, achieving learnable quantification, ensuring regular block shape, solving the technical problem of the lack of scientific quantitative standards in traditional exploration right retreat schemes, and achieving the technical effect of improving the objectivity, accuracy and feasibility of retreat decisions, providing quantifiable, reproducible and manageable technical support for dynamic adjustment of mining rights.

[0115] As an optional embodiment, the determining module includes: a first acquisition unit for acquiring the geological potential score of each grid; a second acquisition unit for acquiring the surface resistance score of each grid; an adjustment unit for adjusting the relative weight between the geological potential score and the surface resistance score of the same grid by means of a pre-set balance coefficient; and a determining unit for determining the retention priority based on the ratio of the adjusted geological potential score to the adjusted surface resistance score.

[0116] As an optional embodiment, the first acquisition unit includes: a first acquisition subunit, used to acquire geological index scores corresponding to each grid based on multiple geological evaluation indicators, wherein each geological evaluation indicator is a single dimension for evaluating geological potential; a first determination subunit, used to perform weighted summation of the multiple geological index scores according to the geological weights set for each geological evaluation indicator in advance, to obtain a comprehensive geological score for each grid; and a second determination subunit, used to add a confidence penalty factor to the comprehensive geological score of the grid based on the Euclidean distance between the grid and the nearest exploration well, to obtain a geological potential score, wherein the confidence penalty factor is negatively correlated with the Euclidean distance, and the geological potential score is positively correlated with the confidence penalty factor.

[0117] As an optional embodiment, the second acquisition unit includes: a second acquisition subunit, used to acquire surface resistance scores for each grid based on multiple surface resistance indicators, wherein each surface resistance indicator is a single dimension for evaluating surface resistance; a third determination subunit, used to perform weighted summation of multiple surface resistance scores according to the surface weights set for each surface resistance indicator in advance, to obtain a comprehensive surface score for each grid; and a fourth determination subunit, used to add a veto factor to the comprehensive surface score of the grid based on the positional relationship between the grid and a pre-set prohibited exploration block, to obtain a surface resistance score, wherein when the grid's position coincides with the prohibited exploration block, the veto factor takes the maximum value, and when the grid's position does not coincide with the prohibited exploration block, the veto factor takes a positive value, and the surface resistance score is positively correlated with the veto factor.

[0118] As an optional embodiment, the selection module includes: a first selection unit, used to select a preset number of initial grids from multiple grids in ascending order of retention priority to obtain a candidate set; a second selection unit, used to select seed grids from multiple initial grids recorded in the candidate set in ascending order of retention priority to obtain a seed set, wherein the Euclidean distance between any two seed grids in the seed set is not less than a preset repulsion radius; and an iteration unit, used to take each seed grid as the iteration starting point of the candidate grid, and iteratively select the adjacent grid with the lowest retention priority as the candidate grid from multiple adjacent grids adjacent to the candidate grid, until the total area of ​​the candidate grids is not less than the target reduction area.

[0119] As an optional embodiment, the iterative unit includes: a fifth determining subunit, used to determine the seed grid as a candidate grid; a selection subunit, used to select adjacent grids that do not belong to the candidate grid from multiple grids adjacent to the candidate grid, to obtain an adjacent grid set; a sixth determining subunit, used to retain the adjacent grid with the lowest priority in the adjacent grid set as the candidate grid, and to calculate the total grid area of ​​the candidate grid; and a seventh determining subunit, used to redetermine the adjacent grid set if the total grid area is less than the target reduction area, until the total grid area of ​​the candidate grid is not less than the target reduction area.

[0120] As an optional embodiment, the processing module includes: an elimination unit for eliminating holes in a connected region established based on multiple candidate grids to obtain candidate retreat blocks, wherein each connected region includes multiple adjacent candidate grids; an extraction unit for extracting the closed contour of the candidate retreat blocks using a neighborhood tracking algorithm to obtain a first contour point set; an inflection point thinning unit for thinning the inflection points of the first contour point set to obtain a second contour point set for representing the inflection points of a regular contour graphic; and an adjustment unit for adjusting the second contour point set based on the deviation between the area of ​​the regular contour graphic enclosed by the second contour point set and the target retreat area to obtain the exploration right retreat block.

[0121] This application also provides an electronic device, which includes a memory and a processor. The memory is used to store program instructions, and the processor is connected to the memory to execute the steps of determining the exploration right reduction block in the various embodiments of this application.

[0122] This application also provides a non-volatile storage medium, which includes a stored computer program, wherein the device containing the non-volatile storage medium executes the steps of the method for determining exploration right reduction blocks in various embodiments of this application by running the computer program.

[0123] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the method for determining exploration right reduction blocks in various embodiments of this application.

[0124] This application also provides a computer program that, when executed by a processor, implements the steps of the method for determining exploration right reduction blocks in various embodiments of this application.

[0125] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0126] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0128] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0131] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining exploration right reduction blocks, characterized in that, include: The exploration rights block to be degraded is discretized into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes multiple grids with the same area; Based on geological potential and surface resistance, a retention priority is determined for each grid, wherein the geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority, and the surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority; Among the multiple grids, multiple candidate grids that meet the target reduction area are selected in ascending order of retention priority; Morphological processing is performed on multiple candidate grids to obtain exploration right reduction blocks, wherein the morphological processing is at least used to eliminate holes in the connected domain formed by the multiple candidate grids.

2. The method according to claim 1, characterized in that, Based on geological potential and surface resistance, the retention priority of each grid is determined as follows: Obtain the geological potential score for each grid; Obtain the surface resistance score for each of the grids; The relative weights between the geological potential score and the surface resistance score of the same grid are adjusted by a pre-set balance coefficient. The retention priority is determined based on the ratio of the adjusted geological potential score to the adjusted surface resistance score.

3. The method according to claim 2, characterized in that, Obtaining the geological potential score for each grid includes: Obtain the geological index score corresponding to each grid based on multiple geological evaluation indicators, wherein each geological evaluation indicator is a single dimension for evaluating the geological potential; According to the geological weights set for each of the geological evaluation indicators in advance, the scores of multiple geological indicators are weighted and summed to obtain the comprehensive geological score of each grid. Based on the Euclidean distance between the grid and the nearest exploration well, a confidence penalty factor is added to the geological comprehensive score of the grid to obtain the geological potential score. The confidence penalty factor is negatively correlated with the Euclidean distance, and the geological potential score is positively correlated with the confidence penalty factor.

4. The method according to claim 2, characterized in that, Obtaining the surface resistance score for each of the grids includes: Obtain a surface resistance score for each grid based on multiple surface resistance indices, wherein each surface resistance index is a single dimension for evaluating the surface resistance. According to the surface weights set for each of the aforementioned surface resistance indicators in advance, the multiple surface resistance scores are weighted and summed to obtain the comprehensive surface score for each of the grids; Based on the positional relationship between the grid and the pre-set prohibited exploration blocks, a veto factor is added to the comprehensive surface score of the grid to obtain the surface resistance score. When the position of the grid coincides with the prohibited exploration block, the veto factor is at its maximum value; when the position of the grid does not coincide with the prohibited exploration block, the veto factor is a positive number. The surface resistance score is positively correlated with the veto factor.

5. The method according to claim 1, characterized in that, Among the multiple grids, selecting multiple candidate grids that meet the target reduction area in ascending order of retention priority includes: Among the multiple grids, a preset number of initial grids are selected in ascending order of retention priority to obtain a candidate set; Among the multiple initial grids recorded in the candidate set, seed grids are selected in ascending order of retention priority to obtain a seed set, wherein the Euclidean distance between any two seed grids in the seed set is not less than a preset repulsion radius; Taking each seed grid as the starting point for the iteration of the candidate grid, among the multiple adjacent grids adjacent to the candidate grid, the adjacent grid with the lowest retention priority is iteratively selected as the candidate grid until the total area of ​​the candidate grid is not less than the target reduction area.

6. The method according to claim 5, characterized in that, Using each seed grid as the starting point for the iteration of the candidate grid, among multiple adjacent grids adjacent to the candidate grid, the adjacent grid with the lowest retention priority is iteratively selected as the candidate grid, until the total area of ​​the candidate grid is not less than the target reduction area, including: The seed grid is determined as the candidate grid; Among the multiple grids adjacent to the candidate grid, select the adjacent grids that do not belong to the candidate grid to obtain the adjacent grid set; The adjacent mesh with the lowest retention priority in the set of adjacent meshes is determined as a candidate mesh, and the total area of ​​the candidate mesh is calculated. If the total area of ​​the grid is less than the target setback area, the set of adjacent grids is re-determined until the total area of ​​the candidate grids is not less than the target setback area.

7. The method according to claim 1, characterized in that, Morphological processing is performed on multiple candidate grids to obtain exploration right reduction blocks, including: Eliminating holes in the connected regions established based on multiple candidate grids yields candidate reduction blocks, wherein each connected region includes multiple adjacent candidate grids; The closed contours of candidate receding blocks are extracted using a neighborhood tracking algorithm to obtain the first contour point set; The first set of contour points is thinned out by inflection point extraction to obtain a second set of contour points used to represent the inflection points of regular contour graphics. Based on the deviation between the area of ​​the regular contour graphic enclosed by the second contour point set and the target reduction area, the second contour point set is adjusted to obtain the exploration right reduction block.

8. A device for determining exploration right withdrawal blocks, characterized in that, include: A discrete module is used to discretize the exploration rights block to be degraded into a two-dimensional grid matrix, wherein the two-dimensional grid matrix includes multiple grids with the same area; A determination module is used to determine the retention priority of each grid based on geological potential and surface resistance, wherein the geological potential is used to quantify the exploration value of the grid and is positively correlated with the retention priority, and the surface resistance is used to quantify the surface exploration resistance of the grid and is negatively correlated with the retention priority; The selection module is used to select multiple candidate grids that meet the target reduction area from among the multiple grids in ascending order of the retention priority; A processing module is used to perform morphological processing on multiple candidate grids to obtain exploration right reduction blocks, wherein the morphological processing is at least used to eliminate holes in the connected domain formed by the multiple candidate grids.

9. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the method for determining exploration right reduction blocks as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for determining the exploration right reduction block as described in any one of claims 1 to 7.

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