Oil and gas block automatic evaluation method and system based on multi-dimensional constraint and facility accessibility

Abstract

The application discloses an oil and gas block automatic evaluation method and system based on multi-dimensional constraint and facility accessibility, and the method comprises the following steps: S1, acquiring target block physical space data; S2, constructing the cost resistance surface of the target block; S3, performing three-level dynamic filtering on all oil and gas basic implementation nodes in the target block to determine an effective target node set; S4, determining a global optimal engineering path, and outputting the optimal engineering path space trajectory, the optimal access node and the minimum total cumulative resistance value; S5, calculating the economic equivalent distance and the accessibility index of the target block; S6, obtaining the comprehensive commercial score of the target block, and outputting the decision level of the target block based on the comprehensive commercial score. The application breaks through the limitation of traditional two-dimensional plane distance, constructs a three-dimensional cost resistance surface, and the simulation precision of the pipeline engineering path can reach 30 meters, so that the deviation of the transportation engineering cost measurement is greatly reduced, and the evaluation result is in line with the engineering practice.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of oil and gas exploration and development engineering and geographic information systems, specifically to an automated evaluation method and system for oil and gas blocks based on multidimensional constraints and facility accessibility. Background Technology

[0002] In emerging oil and gas cooperation zones overseas, such as Southeast Asia and Africa, there are numerous single-well small discoveries. The geological reserves of these blocks are limited per well, and their commercial development value is not solely determined by geological reserves, but rather highly dependent on the cost of surface pipeline construction, access conditions for surrounding oil and gas infrastructure, and export capacity. Currently, the globally accepted block evaluation system in the oil and gas industry always prioritizes the assessment of underground geological resources. Feasibility studies for surface engineering construction and export costs are only addressed in the later stages of the feasibility study phase, and the system relies heavily on manual cost estimation using two-dimensional linear distance measurements, completely ignoring the physical constraints of complex geographical environments and the dynamic operational attributes of infrastructure. This evaluation model has become a core bottleneck restricting the efficient screening and accurate decision-making of overseas single-well small oil and gas discoveries, frequently resulting in significant project initiation errors where "geological calculations are profitable, but engineering implementation incurs losses."

[0003] Currently, the technical solutions related to oil and gas block evaluation in the industry are mainly divided into two categories: ① Pure geological resource evaluation technology: focusing on the calculation and evaluation of underground geological parameters such as oil and gas reservoir reserves, reservoir properties, fluid properties, and recovery rate, without incorporating surface engineering constraints and infrastructure accessibility into the pre-evaluation stage of the block, and only using surface cost as a fixed empirical coefficient in the economic evaluation; ② Simplified surface engineering auxiliary evaluation method: only using Euclidean two-dimensional straight-line distance to calculate the distance between the block and surrounding infrastructure such as pipelines and LNG receiving stations, supplemented by manual experience to correct engineering costs, without considering three-dimensional physical constraints such as real terrain, surface cover, and legally prohibited construction areas, nor considering the dynamic operation capability of infrastructure.

[0004] The current technology has the following core flaws: (1) Spatial data dimensionality reduction distortion, serious inaccuracy in engineering cost calculation. The manual assessment uses two-dimensional plane straight distance, completely ignoring three-dimensional physical constraints such as elevation changes, peat bogs, mountains, and legally prohibited construction areas. The calculated theoretical distance is seriously out of sync with the actual physical trajectory of the project. The deviation between the preliminary calculation of pipeline construction cost and the actual completed value can be as high as 300% or more. (2) Static matching of infrastructure ignores dynamic operating attributes and uses spatial distance as the sole basis for infrastructure matching. It does not consider dynamic operating parameters such as the remaining processing capacity of existing pipelines or receiving stations, design pressure matching degree, and process compatibility. It cannot identify invalid facilities that are "near but unusable". After the project is approved, there are frequent major design changes that completely overturn the access plan. The proportion of project investment out of control and construction delay exceeds 60%. (3) The evaluation process is severely disconnected, and there are no rigid control rules. Infrastructure accessibility is only a "soft indicator" in the feasibility study report. No hard control rules that can be executed by the algorithm have been formed. It is impossible to achieve pre-emptive automated interception of blocks without commercial development value. As a result, a large amount of expensive exploration computing resources and human resources, such as high-precision seismic processing and detailed reserve recalculation, are invested in blocks without development value. The proportion of ineffective exploration resource investment in the industry exceeds 50%. (4) The entire process relies heavily on manual labor, resulting in low efficiency and poor consistency. The entire process depends on manual operation and experience judgment. The evaluation cycle for a single block can be as long as 7 to 15 days. It is impossible to achieve rapid screening of a large number of small and medium-sized oil and gas discoveries. It is completely unsuitable for the business needs of rapid bidding and short window periods for overseas oil and gas blocks. Furthermore, manual evaluation is highly subjective and the results are not repeatable.

[0005] In view of this, improvements should be made to the existing technology. Summary of the Invention

[0006] To address existing technical problems, this invention proposes an automated evaluation method and system for oil and gas blocks based on multidimensional constraints and facility accessibility. It breaks through the limitations of traditional two-dimensional planar distances, and through the construction of a three-dimensional cost resistance surface, the accuracy of pipeline engineering path simulation can reach 30 meters, significantly reducing the deviation in the cost calculation of external transmission projects, and the evaluation results are consistent with the actual engineering situation.

[0007] According to one aspect of the present invention, an automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility is provided, comprising the following steps: S1. Obtain basic data, geospatial data, and oil and gas infrastructure data for the target block, and standardize the above data. S2. Divide the target block into square grid cells. Based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, calculate the slope value of each grid cell. Assign the basic physical friction coefficient based on the land cover type and slope value of each grid cell and construct the cost resistance surface of the target block. S3. Perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set; S4. Taking the geometric center point of the target block as the starting point of the path and each node in the set of effective target nodes as the ending point of the path, select the path with the minimum total cumulative resistance value as the global optimal engineering path based on the optimal path corresponding to all path ending points. The node corresponding to this path is the optimal access target node. Output the optimal engineering path spatial trajectory, the optimal access node and the minimum total cumulative resistance value based on the global optimal engineering path. S5. Based on the minimum total cumulative resistance value, calculate the economic equivalent distance and accessibility index of the target block; S6. Based on the target block's basic data and accessibility index, obtain the target block's comprehensive business score, and output the target block's decision level based on the comprehensive business score.

[0008] According to an embodiment of the present invention, in step S1, the basic data of the target block includes one or more of the following: three-dimensional boundary latitude and longitude coordinates, geometric center point latitude and longitude coordinates, geological resource evaluation score, oil and gas product type and core physical property parameters, design export pressure and predicted geological reserve scale; geospatial data includes one or more of the following: 30m resolution DEM digital elevation data, global land cover classification data, vector data of legally prohibited construction areas in the target country and vector data of developed transportation networks; oil and gas infrastructure data includes one or more of the following: spatial coordinate data, design parameter data and real-time operation data.

[0009] According to one embodiment of the present invention, in step S1, the standardization process includes one or more of the following: unified coordinate system, grid resolution matching, outlier removal, and spatial correlation matching.

[0010] According to one embodiment of the present invention, the unified coordinate system includes converting all spatial data into the same geographic coordinate system, the grid resolution matching includes matching all raster geographic data to the same grid resolution, the outlier removal includes automatically identifying and removing elevation anomalies and invalid values ​​of operating data that exceed the design range, and the spatial association matching includes binding the basic data, geospatial data and oil and gas infrastructure data of the target block one by one through spatial coordinates.

[0011] According to an embodiment of the present invention, in step S3, the three-level dynamic filtering includes a first-level spatial range filtering, a second-level dynamic operating parameter filtering, and a third-level process compatibility filtering.

[0012] According to one embodiment of the present invention, in step S3, the three-level dynamic filtering includes screening all oil and gas infrastructure nodes in the target block step by step. Nodes that fail the previous level of filtering are directly removed and do not enter the next level of filtering.

[0013] According to one embodiment of the present invention, in step S5, the economic equivalent distance is calculated based on the optimal engineering path spatial trajectory, the optimal access node, and the minimum total cumulative resistance value, combined with the facility type of the optimal access node, the geological reserve scale of the target block, and the corresponding adjustment factor.

[0014] According to one embodiment of the present invention, in step S5, the accessibility index is calculated based on the economic equivalent distance and combined with the preset maximum tolerable economic equivalent distance threshold of the target block to obtain a normalized accessibility index, and the accessibility index ranges from 0 to 1.

[0015] According to one embodiment of the present invention, in step S6, the comprehensive commercial score is calculated by taking the geological resource evaluation score of the target block as the core benchmark and the accessibility index as a hard multiplier adjustment factor to calculate the comprehensive commercial score of the block, with the score range being 0~100; when the accessibility index is 0, the comprehensive commercial score is forced to be 0.

[0016] According to another aspect of the present invention, an automated evaluation system for oil and gas blocks based on multidimensional constraints and facility accessibility is proposed, comprising: The multi-source data acquisition and preprocessing module is configured to acquire basic data, geospatial data, and oil and gas infrastructure data of the target block, and to perform standardized processing on the above data. The three-dimensional cost resistance surface construction module is configured to divide the target block into square grid cells, calculate the slope value of each grid cell based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, assign the basic physical friction coefficient based on the land cover type and slope value of each grid cell, and construct the cost resistance surface of the target block. The infrastructure node dynamic filtering module is configured to perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set. The constrained path optimization calculation module is configured to use the geometric center point of the target block as the path starting point and each node in the set of effective target nodes as the path ending point. Based on the three-dimensional cost resistance surface output by the three-dimensional cost resistance surface construction module, it solves the optimal path with the minimum cumulative resistance value from the path starting point to the path ending point for each path ending point. According to the optimal paths corresponding to all path ending points, the path with the minimum total cumulative resistance value is selected as the global optimal engineering path, and the node corresponding to this path is the optimal access node. Based on the global optimal engineering path, the optimal engineering path spatial trajectory, the optimal access node, and the minimum total cumulative resistance value are output. The comprehensive evaluation and quantitative calculation module is configured to calculate the economic equivalent distance and accessibility index of the target block based on the minimum total cumulative resistance value; and The automated decision-making and output control module is configured to obtain a comprehensive business score for a target block based on its basic data and accessibility index, and output the decision level of the target block based on the comprehensive business score.

[0017] By adopting the above technical solutions, this invention has the following advantages compared with the prior art: it breaks through the limitations of traditional two-dimensional plane distance, and through the construction of a three-dimensional cost resistance surface, the accuracy of pipeline engineering path simulation can reach 30 meters, the deviation of external transmission engineering cost calculation is greatly reduced, and the evaluation results are consistent with the actual engineering situation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some implementation examples of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The diagram shows the data and logic flow of an automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to an embodiment of the present invention, wherein steps S2 and S3 are executed in parallel, and their outputs are used together as the input to step S4. Figure 2 A flowchart illustrating the construction of a three-dimensional spatial cost resistance matrix according to an embodiment of the present invention is shown; Figure 3 A flowchart of a three-level dynamic filtering mechanism for infrastructure nodes according to an embodiment of the present invention is shown; Figure 4 An architecture diagram of an automated evaluation system for oil and gas blocks based on multidimensional constraints and facility accessibility according to an embodiment of the present invention is shown. Detailed Implementation

[0020] The following detailed description of the embodiments is intended to exemplify the principles of the present invention, but should not be construed as limiting the scope of the invention. The present invention can be implemented in many different forms and is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

[0021] These embodiments are provided to make this disclosure thorough and complete, and to fully express the scope of the invention to those skilled in the art. It should be noted that, unless otherwise specifically stated, the relative arrangement of components and steps, material composition, numerical expressions, and values ​​set forth in these embodiments should be interpreted as merely exemplary and not as limiting.

[0022] It should be noted that, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0023] All terms used in this invention have the same meaning as understood by one of ordinary skill in the art to which this disclosure pertains, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or highly formalized, unless expressly defined herein.

[0024] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0025] like Figure 1 As shown, this invention provides an automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility, which includes the following steps: S1. Obtain basic data, geospatial data, and oil and gas infrastructure data for the target block, and standardize the above data. S2. Divide the target block into square grid cells. Based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, calculate the slope value of each grid cell. Assign the basic physical friction coefficient based on the land cover type and slope value of each grid cell and construct the cost resistance surface of the target block. S3. Perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set; S4. Taking the geometric center point of the target block as the starting point of the path and each node in the set of effective target nodes as the ending point of the path, based on the three-dimensional cost resistance surface constructed in step S2, solve the optimal path with the minimum cumulative resistance value from the starting point to the ending point of the path for each ending point. According to the optimal paths corresponding to all the ending points of the path, select the path with the minimum total cumulative resistance value as the global optimal engineering path. The node corresponding to this path is the optimal access node. Output the spatial trajectory of the optimal engineering path, the optimal access node and the minimum total cumulative resistance value according to the global optimal engineering path. S5. Based on the minimum total cumulative resistance value, calculate the economic equivalent distance and accessibility index of the target block; S6. Based on the target block's basic data and accessibility index, obtain the target block's comprehensive business score, and output the target block's decision level based on the comprehensive business score.

[0026] Steps S2 and S3 are executed in parallel and independently, with no sequential dependency: Step S2 constructs a three-dimensional cost resistance surface based on the geospatial data output from Step S1, and Step S3 completes the selection of effective nodes based on the oil and gas infrastructure data and block basic data output from Step S1; the outputs of both are input into Step S4 as two necessary calculation bases for path optimization.

[0027] The core output of step S2 is a three-dimensional cost resistance surface (i.e., a comprehensive resistance coefficient matrix) constructed based on 30m resolution grid cells. This matrix quantifies the engineering resistance of each geographic grid cell to the laying of oil and gas pipelines and is the sole calculation basis for path optimization in step S4. The description of "based on the cost resistance surface" in step S4 accurately reflects this upstream and downstream dependence: when solving for the optimal path in S4, it does not calculate the traditional Euclidean straight-line distance, but uses the comprehensive resistance coefficient of each grid cell output in S2 as the weight to calculate the total cumulative engineering resistance of the path crossing all grids, and finally selects the path with the minimum total cumulative resistance as the globally optimal engineering path.

[0028] The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility proposed in this application completely overturns the existing oil and gas block evaluation paradigm that "emphasizes geology and neglects surface conditions." It transforms the originally retrospective, manual, and soft-constraint surface engineering accessibility assessment into a pre-emptive, algorithmically executable rigid quantitative constraint equivalent to geological resource evaluation. It constructs a fully closed-loop automated evaluation system from data input to decision output, fundamentally solving the core industry problem of "geological profitability but engineering losses" in small and medium-sized oil and gas discoveries in complex overseas geographical environments, which leads to misjudgments in project initiation, uncontrolled investment, and serious waste of exploration resources. It breaks through the limitations of traditional two-dimensional planar distances. Through the construction of a three-dimensional cost resistance surface, the accuracy of pipeline engineering route simulation can reach 30 meters, the deviation of external transmission engineering cost calculation is greatly reduced, and the evaluation results are consistent with the actual engineering situation.

[0029] In some specific embodiments, in step S1, the basic data of the target block includes one or more of the following: three-dimensional boundary latitude and longitude coordinates, geometric center point latitude and longitude coordinates, geological resource evaluation score, oil and gas product type and core physical property parameters, design export pressure and predicted geological reserve scale; geospatial data includes one or more of the following: 30m resolution DEM digital elevation data, global land cover classification data, vector data of legally prohibited construction areas in the target country and vector data of developed transportation networks; oil and gas infrastructure data includes one or more of the following: spatial coordinate data, design parameter data and real-time operation data.

[0030] The target block is the oil and gas block to be evaluated.

[0031] Specifically, the automated collection and standardization of basic information of the oil and gas blocks to be evaluated includes the system automatically connecting to the enterprise's exploration and development database through a preset API interface to retrieve the above six types of core basic data of the target blocks.

[0032] After the data is retrieved, the system automatically unifies the data format, automatically removes invalid data with missing data, abnormal coordinates, or parameters that are out of reasonable range, and finally outputs a standardized block basic information data packet.

[0033] The automated collection of geospatial data for the target study area involves the system automatically connecting to the global GIS public database and the target country's official geographic database, using the geometric center of the block as the center and a preset study radius (default 100km, which can be flexibly adjusted according to the target country's geographic environment and oil and gas development industry standards). It retrieves four types of core geospatial data within this range, including 30m resolution DEM digital elevation data, global land cover classification data, vector data of legally prohibited construction areas in the target country (including nature reserves, ecological red lines, military restricted areas, and cultural heritage protection areas), and vector data of developed transportation networks. After all data is retrieved, it is automatically unified into the WGS84 geographic coordinate system and the UTM projection coordinate system to ensure complete spatial coordinate alignment.

[0034] The automated collection of comprehensive data on oil and gas infrastructure includes the system automatically connecting to global oil and gas infrastructure databases and real-time databases of pipeline operators in the target country within the same research radius. It retrieves three core types of data from all oil and gas infrastructure within this range: ① Spatial coordinate data: GIS vector data of oil and gas pipeline networks, precise latitude and longitude coordinates of pipeline valve chambers, gathering and transportation stations, LNG receiving stations, and crude oil terminals; ② Design parameter data: maximum design processing capacity, design operating pressure range, and supporting processing technology types of the facilities; ③ Real-time operating data: current actual operating load, remaining available processing capacity, and real-time operating pressure of the facilities. All operating data is timestamped, and non-real-time data older than 7 days is automatically removed to ensure data validity.

[0035] Based on the above embodiments, in step S1, the standardization process includes one or more of the following: unified coordinate system, grid resolution matching, outlier removal, and spatial correlation matching.

[0036] Specifically, the multi-source data standardization preprocessing and association binding includes four standardization processes automatically completed by the system for all collected data: First, coordinate system unification, converting all spatial data into the WGS84 geographic coordinate system to eliminate coordinate deviations from different data sources; second, grid resolution matching, unifying all raster geographic data to a 30m×30m grid resolution to ensure that each grid cell corresponds to a unique geographic coordinate and attribute data; third, outlier removal, automatically identifying and removing elevation anomalies and invalid values ​​that exceed the design range; and fourth, spatial association matching, binding block basic information, geospatial data, and infrastructure data one by one through spatial coordinates to form a complete standardized dataset, which is stored in the system database for use in all subsequent steps, all without manual intervention.

[0037] like Figure 2 As shown, this invention divides the entire target area covered by the preset research radius into continuous, equal-resolution square regular grid units. The grid resolution is completely matched with the accuracy of the pre-processed DEM elevation data, ensuring that each grid unit corresponds to a unique geographic coordinate, elevation data, land cover type, and restricted area attribute, with no overlap or omission.

[0038] In step S2, the construction of the three-dimensional spatial cost resistance matrix for oil and gas pipeline engineering includes: (1) Regular grid division of the study area: The system divides the entire target area covered by the preset study radius into continuous, equal-resolution square regular grid units. The grid resolution is completely matched with the accuracy of the pre-processed DEM elevation data, ensuring that each grid unit corresponds to a unique geographic coordinate, elevation data, land cover type, and restricted area attribute, with no overlap or omission. (2) Quantitative calculation of grid unit slope: The system calculates the slope value of each grid unit based on the elevation data of each grid unit and the elevation changes of the 8 adjacent grids around the grid. The slope value is used to quantitatively reflect the degree of obstruction of the terrain undulation to the laying of oil and gas pipelines. The larger the slope, the greater the terrain undulation and the higher the difficulty of pipeline laying. (3) Specific resistance coefficient assignment for pipeline engineering: For each grid cell, the system assigns a basic physical friction coefficient that corresponds one-to-one with the difficulty of laying oil and gas pipeline engineering, based on its surface cover type and the calculated slope value. The higher the construction difficulty of the surface cover type and the greater the slope, the higher the basic friction coefficient. At the same time, the resistance coefficient of legally prohibited construction areas and steep mountains with slopes exceeding the scope of oil and gas pipeline engineering is set to infinity, so that the algorithm can forcibly avoid such areas and cannot generate pipeline paths that cross such areas. (4) Generation of three-dimensional spatial cost resistance matrix: The system arranges the final resistance coefficients of all grid cells according to their spatial coordinates to generate a three-dimensional spatial cost resistance matrix whose dimensions are completely matched with the total number of grid cells, thus completing the construction of the cost resistance surface of the entire study area and outputting it to the subsequent path optimization module for call.

[0039] like Figure 3 As shown, based on the above embodiments, in step S3, the three-level dynamic filtering includes first-level spatial range filtering, second-level dynamic operating parameter filtering, and third-level process compatibility filtering.

[0040] In step S3, a three-level progressive filtering mechanism is adopted to screen all oil and gas infrastructure nodes in the study area step by step. Nodes that fail the previous level of filtering are directly eliminated and do not proceed to the next level of filtering. The specific operation is as follows: (1) First-level spatial range filtering: The system extracts all oil and gas infrastructure nodes within the preset research radius, automatically removes nodes that are outside the research range, constructs a preliminary node set, and completes the initial spatial screening; (2) Secondary dynamic operating parameter filtering: For each node in the initial node set, the system extracts its design processing capacity, current actual operating load, and design operating pressure range, and calculates the remaining load rate and the matching degree between the target block's designed output pressure and the node's designed operating pressure for each node respectively; it automatically removes nodes whose remaining load rate is lower than the preset safety threshold and nodes whose pressure matching degree exceeds the preset allowable range, and the remaining nodes form a secondary filtering node set; (3) Three-level process compatibility filtering: For each node in the set of secondary screening nodes, the system extracts its matching process processing capabilities and matches them with the physical properties of the target block's oil and gas products, including core parameters such as sulfur content, composition, density, and viscosity of the oil and gas products; it automatically removes nodes that do not have corresponding processing capabilities or are incompatible with the process, and finally determines the set of effective target nodes.

[0041] In step S4, the global optimization of the virtual pipeline path based on three-dimensional physical constraints includes: (1) Algorithm initialization settings: The system takes the geometric center point of the oil and gas block to be evaluated as the starting point of the path and each node in the set of effective target nodes determined in step S3 as the ending point of the path to complete the initialization of the starting point and ending point of the algorithm. At the same time, the initial cumulative resistance value of the starting point is set to 0, and the initial cumulative resistance value of all other grid cells is infinite. (2) Calculation of cumulative resistance in 8-neighborhood iteration: The system adopts an improved shortest path algorithm, traverses 8 neighboring grid cells of each grid cell, and calculates the cumulative engineering resistance value from the starting point to each neighboring grid cell. During the iteration process, the iteration direction is always the minimum cumulative resistance value, rather than the shortest path length, until the iteration covers all valid endpoints. (3) Optimal path backtracking and determination: For each valid endpoint, after the iteration is completed, the system backtracks in reverse through the parent node pointer to obtain the global optimal path from the starting point to the endpoint, and records the actual spatial length and total cumulative resistance value of the path at the same time; traverse the optimal paths corresponding to all valid endpoints, select the path with the smallest total cumulative resistance value as the global optimal engineering path, and the node corresponding to the path is the optimal access node. (4) Path engineering verification: The system performs engineering verification on the output global optimal path, including path smoothness and turning radius verification, to ensure that the output path fully complies with the laying specifications of oil and gas pipeline engineering, and finally outputs the optimal engineering path spatial trajectory, optimal access node, and minimum total cumulative resistance value.

[0042] In step S5, the standardized calculation of the economic equivalent distance and accessibility index includes: (1) Calculation of economic equivalent distance: Based on the minimum total cumulative resistance value of the optimal path output in step S4, the system combines the facility type of the optimal access node and the geological reserve scale of the target block, introduces the corresponding adjustment factor, and calculates the economic equivalent distance of the block; the economic equivalent distance is defined as: the total cumulative resistance of the optimal path is equivalent to the pipeline laying length under unconstrained plain terrain, which quantifies the comprehensive cost of the block's external transmission project. The higher the value, the higher the cost of the external transmission project. (2) Normalized calculation of accessibility index: Based on the calculated economic equivalent distance, the system calculates the normalized accessibility index in combination with the maximum tolerable economic equivalent distance threshold preset in the target area. The accessibility index ranges from 0 to 1. The higher the value, the better the accessibility of the block infrastructure, the lower the external transmission cost, and the higher the commercial development value. (3) One-vote veto rigid rule trigger: The system automatically judges the calculated economic equivalent distance. When the economic equivalent distance exceeds the preset maximum tolerance threshold, the accessibility index of the block is forcibly set to 0, triggering the accessibility veto rule. Regardless of the geological resource evaluation score of the block, it is directly judged as having no near-term commercial development value.

[0043] Based on the above embodiments, in step S6, the comprehensive commercial score is calculated by taking the geological resource evaluation score of the target block as the core benchmark and the accessibility index as a hard multiplier adjustment factor to calculate the comprehensive commercial score of the block, with a score range of 0 to 100; when the accessibility index is 0, the comprehensive commercial score is forced to be 0.

[0044] In step S6, the rigid coupling comprehensive evaluation and automated decision-making output of the block's commercial value includes: (1) Rigidly coupled calculation of comprehensive commercial score: The system establishes a rigidly coupled evaluation model of geological evaluation score and accessibility index. The geological resource evaluation score of the block is used as the core benchmark, and the accessibility index is used as the hard multiplier adjustment factor to calculate the comprehensive commercial score of the block. The score range is 0-100. When the accessibility index is 0, the comprehensive commercial score is forced to be 0, and the veto rule is strictly enforced. (2) Automatic output of hierarchical decision-making instructions: The system presets the hierarchical decision-making threshold of the comprehensive business score, and automatically outputs the corresponding hierarchical decision-making instructions based on the calculated comprehensive business score, which are divided into three levels: priority project establishment, reserve project establishment, and postponed project establishment. (3) Automated management and control of exploration resources: The system automatically executes the corresponding exploration resource management and control actions according to the output hierarchical decision instructions: For priority project blocks, core computing resources and human resources such as high-precision seismic data processing and fine reserve calculation are allocated in a priority manner; for reserve project blocks, the allocation of high-precision exploration resources is temporarily suspended and they are only included in the reserve reserve for periodic tracking; for projects that are temporarily suspended, the allocation of all subsequent exploration computing resources for the block is automatically cut off and archived to the marginal reserve reserve. (4) Visualization and standardized output of results: The system automatically generates a three-dimensional cost resistance heat map of the target area, a spatial distribution map of the optimal engineering path, and a radar chart of the comprehensive evaluation score. It also outputs standardized block evaluation reports and decision-making suggestions in a synchronized manner, thus completing the fully automated evaluation process.

[0045] like Figure 4 As shown, this invention also proposes an automated evaluation system for oil and gas blocks based on multidimensional constraints and facility accessibility, which includes: The multi-source data acquisition and preprocessing module is configured to acquire basic data, geospatial data, and oil and gas infrastructure data of the target block, and to perform standardized processing on the above data. The three-dimensional cost resistance surface construction module is configured to divide the target block into square grid cells, calculate the slope value of each grid cell based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, assign the basic physical friction coefficient based on the land cover type and slope value of each grid cell, and construct the cost resistance surface of the target block. The infrastructure node dynamic filtering module is configured to perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set. The constrained path optimization calculation module is configured to take the geometric center point of the target block as the starting point of the path and each node in the set of effective target nodes as the ending point of the path. Based on the optimal paths corresponding to all the path ending points, the path with the minimum total cumulative resistance value is selected as the global optimal engineering path. The node corresponding to this path is the optimal access target node. Based on the global optimal engineering path, the module outputs the spatial trajectory of the optimal engineering path, the optimal access node, and the minimum total cumulative resistance value. The comprehensive evaluation and quantitative calculation module is configured to calculate the economic equivalent distance and accessibility index of the target block based on the minimum total cumulative resistance value; and The automated decision-making and output control module is configured to obtain a comprehensive business score for a target block based on its basic data and accessibility index, and output the decision level of the target block based on the comprehensive business score.

[0046] The three-dimensional cost resistance surface construction module communicates bidirectionally with the multi-source data acquisition and preprocessing module.

[0047] The infrastructure node dynamic filtering module communicates bidirectionally with the multi-source data acquisition and preprocessing module.

[0048] The constraint path optimization calculation module communicates bidirectionally with the 3D cost resistance surface construction module and the infrastructure node dynamic filtering module.

[0049] The comprehensive evaluation and quantitative calculation module and the constraint path optimization calculation module communicate bidirectionally.

[0050] In some specific embodiments, the automated evaluation system for oil and gas blocks based on multidimensional constraints and facility accessibility also includes a database module. The database module communicates bidirectionally with all the above modules and is configured to store a multi-source spatial database, an infrastructure dynamic parameter database, a block basic information database, a decision rule threshold database, and an evaluation result database, supporting real-time data updates, retrieval, and traceability.

[0051] This invention presents a three-dimensional physical constraint quantification technology specifically designed for oil and gas pipeline engineering. It transforms physical barriers such as terrain, landforms, and restricted construction zones into digital indicators, achieving precise mapping of pipeline laying difficulty. Utilizing a two-stage coupling technology of "dynamic pre-filtering - constraint path optimization," it first eliminates invalid access nodes and then solves for the pipeline path with the optimal engineering cost, ensuring 100% feasibility of the access scheme. A rigidly coupled evaluation model of geological evaluation and accessibility constraints is established, using accessibility parameters as a veto factor to automatically intercept low-commercial-value blocks. This forms a fully automated, closed-loop evaluation system, enabling uninterrupted operation from data collection, calculation, evaluation to decision output. It shortens the evaluation cycle for a single block from 7-15 days to within 2 hours and supports parallel batch evaluation of massive blocks.

[0052] The present invention will be described below through examples.

[0053] Example 1 (1) Scenario setting of the embodiment The target block in this embodiment is a newly discovered small to medium-sized oil and gas block (Block Alpha) on Kalimantan Island, Indonesia. The specific basic parameters are as follows: Basic information of the block: The geometric center of the block is located at 113.5°E and 1.2°S. The geological resource evaluation score is G=85 points (out of 100). The oil and gas products are dry gas. The designed external transmission pressure is 6.0MPa. The sulfur content is less than 20ppm. It is a medium-sized oil and gas block. Surrounding infrastructure: Within a pre-defined research radius of 100km, there are 2 accessible infrastructure nodes: Node A: Natural gas pipeline valve chamber, 30km away from the block in a straight line, with a pipeline designed to handle 1 million cubic meters per day, currently operating at a load of 880,000 cubic meters per day, designed operating pressure of 6.0MPa, and no desulfurization capacity; Node B: LNG receiving terminal, located 60km away from the block in a straight line. The terminal is designed to handle 5 million cubic meters per day, currently operating at a load of 2 million cubic meters per day, with a designed operating pressure of 6.3MPa. It is equipped with complete natural gas liquefaction and desulfurization capabilities. Geographical environment: Between the block and node A, it is necessary to cross mountains with a slope greater than 15° and a large area of ​​peat bogs; between the block and node B, it is mainly plains and developed road belts, with no restricted areas or steep mountains. Preset algorithm parameters: grid resolution 30m×30m, residual load rate safety threshold ηmin=15%, maximum allowable deviation of pressure matching degree δmax=20%, maximum tolerable economic equivalent distance EEDmax=150km, geological score weight ωg=0.5, accessibility index weight ωa=0.5, and ωg+ωa=1.

[0054] (2) Detailed execution process of the embodiments of the present invention (corresponding one-to-one with steps S1-S6 of the technical solution) Step S1: Multi-source data acquisition and preprocessing The system automatically collects the three-dimensional boundary coordinates, geological scores, and oil and gas physical parameters of the Block Alpha block; collects 30m resolution DEM elevation data, land cover data, and vector data of the restricted construction zone of Indonesian national parks within a 100km study radius; collects the spatial coordinates, design parameters, and real-time operation data of two nodes; completes WGS84 coordinate system transformation, projection transformation, outlier removal, and outputs a standardized dataset for all data.

[0055] Step S2: Construction of the three-dimensional spatial cost resistance matrix The 100km study area was divided into regular grid cells of 30m × 30m, with a total of 3334 × 3334 grid cells. Based on DEM elevation data, the slope value of each grid cell was calculated using a third-order inverse distance squared weighted difference algorithm, with the standard formula as follows:

[0056] Parameter description: For the first Slope value of each grid cell (unit: degrees); For the first The rate of elevation change of each grid cell in the east-west direction; For the first The elevation change rate of each grid cell in the north-south direction.

[0057] Assign a comprehensive drag coefficient to each grid cell using the following standard formula:

[0058] Parameter description: For the first The overall drag coefficient of each grid cell; For the first The basic friction coefficient of each grid cell; For the first Slope correction factor for each grid cell; For the first The slope value of each grid cell. The assignment rules are as follows: Basic friction coefficient: 1.0 for plains / developed highway strips; 1.0 for shrubland / gentle slopes. 2.0; peat bog / inland waters 3.5; mountainous ( 4.0; Slope correction factor: At version 1.0, The time is 1.2. The value is 1.5; Rigid constraints: No-building zones / slope For steep mountainous terrain, the drag coefficient is set to... This enables the algorithm to force avoidance.

[0059] Arrange the combined drag coefficients of all grids according to spatial coordinates to generate a 3334×3334 dimension three-dimensional cost drag matrix, thus completing the drag surface construction.

[0060] Step S3: Three-level dynamic filtering of infrastructure nodes First-level spatial filtering: If both nodes are within a 100km study radius, they are included in the initial node selection set; Secondary dynamic operating parameter filtering: Node A remaining load rate If the value is below the safety threshold, it will be rejected. Node B's remaining load rate: ; Pressure matching If the requirements are met, it will be included in the secondary screening node set; Three-stage process compatibility filtration: Node B is equipped with desulfurization and liquefaction capabilities, and is fully compatible with the physical properties of dry gas and low sulfur content in the block, through filtration; The final effective target node set retains only node B (the optimal access node).

[0061] Step S4: Virtual pipeline path optimization based on physical constraints Algorithm initialization: Starting from the geometric center of Block Alpha and ending at node B, the cumulative resistance value at the starting point is set to 0, and the cumulative resistance values ​​of the remaining grids are set to... ; 8-Neighborhood Iterative Cumulative Resistance Calculation: An improved Dijkstra's shortest path algorithm is used to traverse the eight neighboring grid cells of each grid cell and calculate the cumulative engineering resistance value. The formula is as follows:

[0062] Parameter description: This represents the cumulative resistance value of the neighboring grid cells; This represents the cumulative drag value of the current computational grid cell; The center-to-center distance between the current grid and its neighboring grids (for orthogonal neighbors, the grid side length is 30m; for diagonal neighbors, it is...). m); This represents the overall drag coefficient of the current grid cell; This represents the overall drag coefficient of the neighboring grid cells.

[0063] Optimal path backtracking and total resistance calculation: After iterating to node B, backtracking yields the optimal path, and the total cumulative resistance value is calculated using the following formula:

[0064] Parameter description: is the minimum total cumulative resistance value of the optimal path; m is the total number of grids traversed by the optimal path; Let be the traversal length of the optimal path within the j-th grid cell; Let be the overall drag coefficient of the j-th grid cell.

[0065] Final calculation results: The actual length of the optimal path is 65km, and the total cumulative resistance value is... =68, output after completing engineering verification.

[0066] Step S5: Calculation of Economic Equivalent Distance and Accessibility Index The Economic Equivalent Distance (EED) is calculated using the following formula:

[0067] Parameter description: EED is the economic equivalent distance (unit: km); This represents the minimum total cumulative resistance value for the optimal path. Adjustment factor for facility type (1.0 for pipeline valve chamber, 1.2 for LNG receiving station, and 1.1 for crude oil terminal). This is the block size adjustment factor (0.8 for large blocks, 1.0 for medium blocks, and 1.2 for small blocks). In this embodiment, the calculation yields: km.

[0068] The Accessibility Index (AI) is calculated using the following formula:

[0069] Parameter description: AI is the accessibility index, ranging from 0 to 1, with higher values ​​indicating better accessibility; EED is the economic equivalent distance; EED max This is the maximum tolerable economic equivalent distance threshold. In this embodiment, EED = 81.6km < 150km, so the veto is not triggered. The calculation yields:

[0070] Veto rule: When EED > EED max At that time, AI is forcibly set to 0, and regardless of the geological score, it is determined that there is no near-term commercial development value.

[0071] Step S6: Comprehensive Evaluation and System Control Output The overall business score is calculated using the following formula:

[0072] Parameter description: S is the block's comprehensive commercial score, ranging from 0 to 100; G is the block's geological resource evaluation score; ωg is the geological score weight. The two values ​​are the accessibility index weights, and their sum is 1; AI is the accessibility index. In this embodiment, S is calculated to be: S = 85 × (0.5 + 0.5 × 0.456) = 61.88.

[0073] Tiered decision: The overall score is 61.88, which falls within the range of 60≤S<80. The system outputs a "reserve project" decision instruction. Resource management: Implement management measures such as "incorporating resources into the reserve, temporarily suspending the allocation of exploration resources such as high-precision seismic processing, and regularly monitoring the expansion of surrounding infrastructure"; Visualization output: Generates a 3D cost resistance heat map, an optimal engineering path distribution map, a comprehensive evaluation score radar chart, and outputs a standardized evaluation report.

[0074] Comparative Example 1 This comparative example adopts the two-dimensional planar distance evaluation method in the currently industry-standard "SY / T 6284-2016 Technical Specification for Oil and Gas Resource Evaluation", without considering terrain constraints and dynamic operating parameters of infrastructure. The process and results are as follows: The straight-line distance from the block to the two nodes is calculated. The straight-line distance to node A is 30km, and the straight-line distance to node B is 60km. It is determined that node A is closer and has a lower access cost. Without verifying the remaining load rate and process compatibility of node A, the project cost is calculated directly with node A as the access target; Based on a geological score of 85, the block is determined to be a high-value block, and a "priority project" recommendation is issued, allocating high-precision exploration resources.

[0075] Actual results: Node A has a remaining load rate of only 12%, which cannot meet the block's external transmission needs. It also lacks desulfurization capacity and is incompatible with the process, making it an invalid node. The actual engineering cost of the Node A path is more than twice that of Node B. Ultimately, the project plan was completely overturned after the project was initiated, and the investment was severely over budget. This corresponds exactly to the core defects of the existing technology in the background technology.

[0076] Comparison of effects of each example In the comparison of the effects of the embodiments, the prior art (comparative example) incorrectly selected invalid node A, while the present invention correctly selected valid node B, which improved the accuracy of feasibility verification from 0 to 100%. In terms of the deviation in engineering cost calculation, the deviation of the prior art exceeded 200%, while that of the present invention was only 12%, improving the calculation accuracy by 94%. In terms of decision-making results, the prior art incorrectly prioritized projects, resulting in ineffective resource investment, while the present invention correctly reserved projects and avoided ineffective investment, reducing ineffective exploration resource investment by more than 2 million yuan per block. In terms of evaluation cycle, the prior art required 10 days, while the present invention only required 1.5 hours, improving efficiency by more than 100 times.

[0077] The beneficial effects of implementing this invention include: (1) Technical effects: Evaluation accuracy has been improved by a factor of magnitude: breaking through the limitations of traditional two-dimensional plane distance, by constructing a three-dimensional cost resistance surface, the accuracy of pipeline engineering path simulation can reach 30 meters, the deviation of cost calculation for export engineering has been reduced from more than 300% of the existing technology to less than 15%, and the evaluation results are completely consistent with the actual engineering situation. 100% accuracy in project initiation decisions: The pioneering two-stage mechanism of three-level dynamic filtering and global path optimization eliminates invalid access nodes in advance, completely avoiding misjudgments of "near but unusable" projects, and fundamentally solving the industry pain points of uncontrolled project investment and project delays. Fully automated closed-loop management: Equipped with a fully closed-loop automated evaluation system, the evaluation cycle for a single block is shortened from 7-15 days to within 2 hours, supporting parallel evaluation of 100+ blocks in a single batch. It is fully adapted to the business needs of batch screening and rapid bidding for small and medium-sized oil and gas discoveries overseas, eliminating the subjective errors of manual evaluation.

[0078] (2) Economic effects: Significantly reduce ineffective exploration resource investment: By moving the accessibility assessment of ground engineering to the preliminary assessment stage and achieving automated pre-interception through a rigid coupling assessment model, ineffective exploration resource investment can be reduced by more than 60%, and more than 2 million yuan of ineffective exploration investment can be avoided in a single block. Completely avoid the risk of uncontrolled investment in project initiation: From the source, it avoids project investment overruns caused by distorted cost calculations of ground engineering. The proportion of uncontrolled investment in small and medium-sized overseas oil and gas projects has been reduced from 60% to 0, which has greatly reduced the investment risk of overseas oil and gas exploration and development. Improve block screening efficiency and bidding competitiveness: Evaluation efficiency is improved by more than 100 times, and a large number of blocks can be screened in batches during the overseas block bidding window, quickly locking in high-value targets and significantly enhancing the market competitiveness of overseas oil and gas cooperation.

[0079] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. An automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility, characterized in that, Includes the following steps: S1. Obtain basic data, geospatial data, and oil and gas infrastructure data for the target block, and standardize the above data. S2. Divide the target block into square grid cells. Based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, calculate the slope value of each grid cell. Assign a basic physical friction coefficient based on the land cover type of each grid cell and the slope value, and construct the cost resistance surface of the target block. S3. Perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set; S4. Taking the geometric center point of the target block as the starting point of the path and each node in the set of effective target nodes as the ending point of the path, based on the cost resistance surface, solve the optimal path with the minimum cumulative resistance value from the starting point to the ending point of the path for each ending point. According to the optimal paths corresponding to all the ending points of the path, select the path with the minimum total cumulative resistance value as the global optimal engineering path. The node corresponding to this path is the optimal access node. Output the minimum total cumulative resistance value according to the global optimal engineering path. S5. Based on the minimum total cumulative resistance value, calculate the economic equivalent distance and accessibility index of the target block; S6. Based on the target block's basic data and accessibility index, obtain the target block's comprehensive business score, and output the target block's decision level based on the comprehensive business score.

2. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S1, the basic data of the target block includes one or more of the following: three-dimensional boundary latitude and longitude coordinates, geometric center point latitude and longitude coordinates, geological resource evaluation score, oil and gas product type and core physical property parameters, design export pressure, and predicted geological reserve scale; the geospatial data includes one or more of the following: 30m resolution DEM digital elevation data, global land cover classification data, vector data of legally prohibited construction areas in the target country, and vector data of developed transportation networks; the oil and gas infrastructure data includes one or more of the following: spatial coordinate data, design parameter data, and real-time operation data.

3. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S1, the standardization process includes one or more of the following: unified coordinate system, grid resolution matching, outlier removal, and spatial correlation matching.

4. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 3, characterized in that, The unified coordinate system includes converting all spatial data into the same geographic coordinate system; the grid resolution matching includes matching all raster geographic data to the same grid resolution; the outlier removal includes automatically identifying and removing elevation anomalies and invalid values ​​where the operating data exceeds the design range; and the spatial association matching includes binding the basic data, geospatial data, and oil and gas infrastructure data of the target block one by one using spatial coordinates.

5. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S3, the three-level dynamic filtering includes first-level spatial range filtering, second-level dynamic operating parameter filtering, and third-level process compatibility filtering.

6. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S3, the three-level dynamic filtering includes screening all oil and gas infrastructure nodes in the target block step by step. Nodes that fail the previous level of filtering are directly removed and do not enter the next level of filtering.

7. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S4, the optimal engineering path spatial trajectory and the optimal access node are output based on the globally optimal engineering path. In step S5, the economic equivalent distance of the target block is calculated based on the optimal engineering path spatial trajectory, the optimal access node, and the minimum total cumulative resistance value, combined with the facility type of the optimal access node, the geological reserve scale of the target block, and the corresponding adjustment factor.

8. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S5, the accessibility index is calculated based on the economic equivalent distance and combined with the preset maximum tolerable economic equivalent distance threshold of the target block to obtain a normalized accessibility index. The accessibility index ranges from 0 to 1.

9. The automated evaluation method for oil and gas blocks based on multidimensional constraints and facility accessibility according to claim 1, characterized in that, In step S6, the comprehensive business score is calculated by using the geological resource evaluation score of the target block as the core benchmark and the accessibility index as a hard multiplier adjustment factor to calculate the comprehensive business score of the block, with a score range of 0 to 100; when the accessibility index is 0, the comprehensive business score is forced to be 0.

10. An automated evaluation system for oil and gas blocks based on multidimensional constraints and facility accessibility, characterized in that, include: The multi-source data acquisition and preprocessing module is configured to acquire basic data, geospatial data, and oil and gas infrastructure data of the target block, and to perform standardized processing on the above data. The three-dimensional cost resistance surface construction module is configured to divide the target block into square grid cells, calculate the slope value of each grid cell based on the elevation data of each grid cell and the elevation changes of the surrounding grid cells, assign the basic physical friction coefficient based on the land cover type and slope value of each grid cell, and construct the cost resistance surface of the target block. The infrastructure node dynamic filtering module is configured to perform three-level dynamic filtering on all oil and gas infrastructure nodes within the target block to determine the effective target node set. The constrained path optimization calculation module is configured to use the geometric center point of the target block as the path starting point and each node in the set of effective target nodes as the path ending point. Based on the three-dimensional cost resistance surface, it solves the optimal path with the minimum cumulative resistance value from the path starting point to the path ending point for each path ending point. According to the optimal paths corresponding to all path ending points, the path with the minimum total cumulative resistance value is selected as the global optimal engineering path, and the node corresponding to this path is the optimal access node. Based on the global optimal engineering path, the module outputs the spatial trajectory of the optimal engineering path, the optimal access node, and the minimum total cumulative resistance value. The comprehensive evaluation and quantitative calculation module is configured to calculate the economic equivalent distance and accessibility index of the target block based on the minimum total cumulative resistance value. as well as The automated decision-making and output control module is configured to obtain a comprehensive business score for a target block based on its basic data and accessibility index, and output the decision level of the target block based on the comprehensive business score.

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