Geophysical exploration data management methods and systems combining GIS

Abstract

This invention provides a geophysical exploration data management method and system integrated with GIS, belonging to the field of geophysical exploration data management technology. First, it extracts the topological relationships of geographic elements in the target exploration area from GIS to generate a set of topological relationship descriptions. Based on this set, it constructs a set of spatial topological association rules between the data and geographic elements. Then, it topologically reconstructs the data according to these rules, generating a structure containing topological nodes and edges. Finally, it dynamically adjusts the strength of topological edge associations based on the exploration task requirements. Finally, it enables spatial access and display of the data in GIS, thereby significantly improving the efficiency and quality of geophysical exploration data management and contributing to increased accuracy and success rate in exploration work.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration data management technology, and more specifically, to a geophysical exploration data management method and system that integrates GIS. Background Technology

[0002] In the field of geophysical exploration, effective management of exploration data is a crucial link in ensuring the smooth progress of exploration work and accurate decision-making. With the continuous development of Geographic Information System (GIS) technology, its powerful spatial analysis and visualization capabilities have brought new opportunities for geophysical exploration data management.

[0003] However, existing methods for managing geophysical exploration data have many shortcomings. On the one hand, traditional data management methods often focus on simple storage and classification of data, neglecting the intrinsic connections between data and geospatial elements. Geophysical exploration data is usually acquired within specific geographical areas, and these data have close spatial relationships with geographical elements (such as topography, landforms, and geological structures). However, traditional methods have failed to fully explore and utilize these relationships, resulting in a lack of spatial integration in data management and utilization, making it difficult to intuitively present the distribution and interrelationships of data in geographic space.

[0004] On the other hand, existing GIS-based data management methods, when processing geophysical exploration data, mostly simply associate the data with geographic coordinates to achieve the data's location and display on a map, but lack in-depth analysis and processing of the spatial topological relationships between the data. Complex spatial relationships may exist between different geophysical exploration data; for example, data from adjacent areas may have similar geological characteristics, and data from the same geological structure may be correlated. Traditional methods cannot effectively capture these spatial topological relationships, resulting in low efficiency in data management and retrieval, making it difficult to meet the needs of comprehensive data utilization for complex exploration tasks, and affecting the quality and efficiency of geophysical exploration work. Summary of the Invention

[0005] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, the present invention provides a geophysical exploration data management method incorporating GIS, the method comprising:

[0006] Extract the topological relationships of geographic elements in the target exploration area from GIS, and generate a set of topological relationship descriptions of geographic elements. The set of topological relationship descriptions of geographic elements includes the connection relationships between geographic elements, the inclusion relationships between geographic elements, and the adjacency relationships between geographic elements.

[0007] Based on the geographical element topology relationship description set, spatial topology association rules between geophysical exploration data and geographical elements are constructed to obtain a spatial topology association rule set.

[0008] Based on the aforementioned set of spatial topological association rules, geophysical exploration data are topologically reconstructed to generate an exploration data topology structure containing topological nodes and topological edges. The topological nodes correspond to a single geophysical exploration data, and the topological edges correspond to the spatial association relationships between different geophysical exploration data.

[0009] Based on the requirements of the target exploration task, the topological edge correlation strength in the topological structure of the exploration data is dynamically adjusted to obtain the adjusted topological structure of the exploration data.

[0010] Based on the adjusted exploration data topology, the spatialization of geophysical exploration data in GIS is realized, and the spatialization results of exploration data are obtained.

[0011] Furthermore, the present invention also provides a geophysical exploration data management system integrated with GIS, characterized in that it includes:

[0012] A processor; a machine-readable storage medium for storing machine-executable instructions of the processor; wherein the processor is configured to perform the above-described geophysical exploration data management method in conjunction with GIS by executing the machine-executable instructions.

[0013] In another aspect, the present invention also provides a computer program product, the computer program product including machine-executable instructions stored in a computer-readable storage medium, wherein a processor of a geophysical exploration data management system integrated with GIS reads the machine-executable instructions from the computer-readable storage medium, and the processor executes the machine-executable instructions, causing the geophysical exploration data management system integrated with GIS to perform the above-described geophysical exploration data management method integrated with GIS.

[0014] Based on the above, the topological relationships of geographic elements in the target exploration area are extracted from GIS, and a set of topological relationship descriptions is generated. The spatial topological association rule set constructed based on this set of topological relationship descriptions accurately reflects the spatial connections between data and geographic elements. The topological reconstruction of geophysical exploration data generates an exploration data topological structure, presenting the spatial relationships between data in the form of topological nodes and topological edges. The strength of the topological edge associations is dynamically adjusted according to the needs of the target exploration task, allowing the exploration data topological structure to flexibly adapt to different exploration scenarios. Finally, based on the adjusted topological structure, the spatial access and display of geophysical exploration data in GIS is realized. This allows for an intuitive and accurate presentation of the distribution and interrelationships of data in geographic space, providing exploration personnel with comprehensive and convenient data query and analysis tools. This significantly improves the efficiency and quality of geophysical exploration data management, contributing to increased accuracy and success rate in exploration work. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the execution flow of the geophysical exploration data management method combined with GIS provided in the embodiments of the present invention.

[0016] Figure 2 This is a schematic diagram of exemplary hardware and software components of a geophysical exploration data management system integrated with GIS provided in an embodiment of the present invention. Detailed Implementation

[0017] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a geophysical exploration data management method integrating GIS, provided in one embodiment of the present invention. The following is a detailed description of this geophysical exploration data management method integrating GIS.

[0018] Step S110: Extract the topological relationships of geographic elements in the target exploration area from the GIS, and generate a set of topological relationship descriptions of geographic elements. The set of topological relationship descriptions of geographic elements includes the connection relationships between geographic elements, the inclusion relationships between geographic elements, and the adjacency relationships between geographic elements.

[0019] In this embodiment, the target exploration area is defined as a specific mineral resource exploration area, which contains various geographic elements. It is necessary to accurately extract the topological relationships between these geographic elements from the GIS system. First, the specific operational process for obtaining the topological relationships of geographic elements in the target exploration area from the GIS must be clarified. Through a comprehensive analysis of the geographic elements in this mineral resource exploration area, their connectivity, inclusion, and adjacency relationships are determined.

[0020] Step S111: Determine the spatial range of the target exploration area in the GIS, extract the geographic feature types within the spatial range, and obtain a set of geographic feature types, which include topographic features, water features, stratigraphic features, and artificial structure features.

[0021] Within the aforementioned target exploration area, the first step is to determine its spatial extent in GIS. Using the coordinate positioning function of the GIS system, the latitude and longitude range of the mineral resource exploration area is delineated. Then, within this spatial range, geographic elements are categorized and extracted. Topographic elements include different landforms such as mountains, hills, and plains; water elements encompass rivers, lakes, and groundwater distribution areas; stratigraphic elements involve the distribution of strata of different ages and lithologies; and man-made structures include facilities formed by human activities such as exploration wells, roads, and buildings. These different types of geographic elements are organized and summarized to form a set of geographic element types, ensuring that subsequent topological relationship analysis of various geographic elements can comprehensively cover the main geographic features of the area.

[0022] Step S112: For each type of geographic feature, extract the spatial coordinates and boundary information of all geographic features under that geographic feature type to obtain a set of geographic feature spatial information. The set of geographic feature spatial information includes the vertex coordinate sequence of geographic features and the boundary contour description of geographic features.

[0023] For each geographic feature type in the set of geographic feature types, such as mountains in the topographic feature, it is necessary to extract the spatial coordinates and boundary information of all specific geographic features under that type. Taking mountains as an example, the vertices coordinate sequence of the mountains is obtained through the GIS system. These vertex coordinates are arranged in a certain order, forming the general outline of the mountains. At the same time, the boundary outline of the mountains is described in detail, including the direction and curvature of the boundaries. For rivers in the water feature, the vertex coordinate sequence of the river channel and the outline description of the river boundary are also extracted, such as the width variation of the river and the location of tributary confluence. For stratigraphic features, it is necessary to extract the spatial coordinates and boundary information of different stratigraphic interfaces to clarify the boundaries between each layer. For man-made structure features such as exploration wells, the coordinate position of the wellhead and the boundary outline of the well platform are recorded. All this information is summarized to form a set of spatial information of geographic features.

[0024] Step S113: Perform pairwise comparisons on the geographic elements in the geographic element spatial information set to determine whether any two geographic elements have a connection relationship. The connection relationship refers to the existence of a common line segment on the boundary of the two geographic elements.

[0025] After obtaining the spatial information set of geographic elements, pairwise comparisons are performed on each geographic element. Any two geographic elements are selected from the set, such as a mountain range in the terrain elements and a river in the water elements. The boundary information of these two geographic elements is obtained, namely, the boundary outline descriptions of the mountain range and the river. By comparing the boundary segments, it is determined whether there are any common segments. Specifically, it is checked whether a segment on the mountain boundary completely or partially overlaps with a segment on the river boundary. If such a common segment exists, it is determined that the two geographic elements are connected. Following this method, all geographic elements in the spatial information set are compared pairwise to ensure that no potentially connected element pairs are overlooked.

[0026] Step S114: Record the coordinate information of geographical feature pairs with connectivity and their common line segments, and generate a connectivity record table.

[0027] Once a connection between two geographic features is identified, their identification information, such as the unique identifiers of mountains and rivers, is immediately recorded, forming a geographic feature pair. Simultaneously, the coordinate information of the common boundary segment between the two features is recorded in detail, including the starting and ending coordinates of the common segment, as well as the coordinates of several key intermediate points along the segment. This information is then organized according to a specific format, such as geographic feature pair identifiers, starting coordinates of the common segment, ending coordinates of the common segment, and a sequence of intermediate point coordinates, to generate a connection relationship record table. This connection relationship record table reflects which geographic features are connected and their specific locations.

[0028] Step S115: Determine whether any two geographic elements have an inclusion relationship, wherein the inclusion relationship means that the entire spatial range of one geographic element is within the spatial range of another geographic element.

[0029] After determining the connectivity, the next step is to determine the inclusion relationship between any two geographic elements. Again, select two geographic elements from the spatial information set, such as a coal seam from the stratigraphic elements and a basin from the topographic elements. Obtain the spatial extent information of the coal seam, i.e., its 3D coordinate distribution in GIS, and the spatial extent information of the basin. By comparing their spatial extents, determine whether the entire space of the coal seam is within the spatial extent of the basin. Specifically, check whether the coordinates of each vertex of the coal seam are within the spatial range enclosed by the boundary coordinates of the basin, while also considering factors such as the thickness of the coal seam to ensure that the entire coal seam is contained within the basin. Following this method, perform pairwise checks on all geographic elements to determine whether an inclusion relationship exists between them.

[0030] Step S116: Record the geographic feature pairs with inclusion relationships and their spatial extent inclusion ratio information, and generate an inclusion relationship record table.

[0031] Once an inclusion relationship is established between two geographic features (e.g., a basin containing a coal seam), the identifiers of these two features are recorded, forming an inclusion feature pair. Next, the inclusion ratio is calculated, which is the ratio of the spatial volume of the included feature (coal seam) to the spatial volume of the containing feature (basin). This calculation requires using the spatial analysis functions of the GIS system based on the spatial coordinates of the geographic features to calculate the volumes of both features separately. The geographic feature pair identifiers and inclusion ratio information are then recorded to generate an inclusion relationship record table. This record table visually displays the degree of inclusion between geographic features.

[0032] Step S117: Determine whether any two geographic elements have an adjacent relationship. The adjacent relationship refers to the boundary distance between the two geographic elements being less than a preset distance and having no common line segments.

[0033] After determining connectivity and inclusion relationships, the adjacency relationship is determined. Two geographic features are selected, such as an exploration well in the man-made structure feature and a shale layer in the stratigraphic feature. First, it is checked whether these two geographic features have a common line segment. If not, the shortest distance between their boundaries is calculated. Using the distance measurement tool of the GIS system, the shortest distance value between a point on the boundary of the exploration well and a point on the boundary of the shale layer is obtained. This distance value is compared with a preset distance. If it is less than the preset distance, the two geographic features are determined to be adjacent. The preset distance needs to be determined based on the actual situation of the mineral resource exploration area and the type of geographic feature to ensure the accuracy of the adjacency relationship determination.

[0034] Step S118: Record the geographical feature pairs with adjacent relationships and their shortest boundary distance information, and generate an adjacent relationship record table.

[0035] Once an adjacency relationship is determined between two geographic features, their identifiers are recorded to form an adjacency pair. Simultaneously, the shortest distance between their boundaries is accurately recorded; this shortest distance is a specific value obtained using the aforementioned GIS distance measurement tool. The geographic feature pair identifiers and shortest distance information are recorded in a specific format to generate an adjacency relationship record table.

[0036] Step S119: Integrate the connection relationship record table, the inclusion relationship record table, and the adjacent relationship record table to generate a geographic feature topology relationship description set that includes the topology relationships of all geographic features.

[0037] After generating the connection relationship record table, inclusion relationship record table, and adjacency relationship record table separately, these three tables need to be integrated. First, check whether the geographic feature identifiers in the three tables are consistent to ensure there is no confusion. Then, classify and organize the information in the three tables according to the type and spatial distribution characteristics of the geographic features. For each geographic feature, summarize its connection, inclusion, and adjacency information with other geographic features. For example, for a specific stratigraphic feature, integrate its connection with surrounding topographic features, its inclusion status, and its distance from adjacent man-made structures. Through this integration, a geographic feature topology description set is formed, which contains various topological relationships between all geographic features within the target exploration area.

[0038] Step S120: Based on the topological relationship description set of the geographic elements, construct spatial topological association rules between geophysical exploration data and geographic elements to obtain a spatial topological association rule set.

[0039] Once a set of topological relationship descriptions for geographic elements is available, spatial topological association rules between geophysical exploration data and geographic elements can be constructed. By analyzing the topological relationships between geographic elements and combining them with the characteristics of geophysical exploration data, the inherent connections between the two can be identified, thereby formulating a series of association rules. These rules will be used to guide subsequent topological reconstruction of geophysical exploration data.

[0040] Step S121: Extract the attribute information of geophysical exploration data to obtain a set of exploration data attribute information. The set of exploration data attribute information includes the exploration type of geophysical exploration data, the exploration time of geophysical exploration data, the exploration depth of geophysical exploration data, and the measurement parameters of geophysical exploration data.

[0041] Within the aforementioned mineral resource exploration areas, a wealth of geophysical exploration data exists, such as seismic exploration data, gravity exploration data, and magnetic exploration data. For each piece of geophysical exploration data, detailed attribute information needs to be extracted. The exploration type clarifies which exploration method was used to obtain the data; the exploration time records the specific time the data was collected, which is crucial for analyzing geological changes at different periods; the exploration depth indicates the range of underground depth reached, reflecting the depth information of the subsurface geological bodies involved in the data; and the measurement parameters include various physical quantities measured during the exploration process, such as seismic wave propagation velocity, gravitational acceleration, and magnetic field strength. Organizing this attribute information according to a specific structure forms a set of exploration data attribute information.

[0042] Step S122: Extract the attribute features of each geographic element from the geographic element topology relationship description set to obtain a geographic element attribute feature set. The geographic element attribute feature set includes the material features, structural features, and spatial distribution features of the geographic elements.

[0043] The topological relationship description set of geographic elements not only includes the topological relationships between geographic elements but also implicitly contains the attribute characteristics of various geographic elements. From this set, attribute characteristics are extracted for each type of geographic element. Material characteristics include, for example, rock types and mineral composition in stratigraphic elements; different rock types have different physical properties, affecting the response of geophysical exploration data. Structural characteristics include the internal structure of geographic elements, such as folds and faults in strata, and the slope and orientation of mountains. Spatial distribution characteristics involve the spatial distribution patterns of geographic elements, such as variations in stratum thickness and the distribution range of water bodies. These attribute characteristics are categorized and organized to form a set of geographic element attribute characteristics, enabling effective comparison and correlation between the attribute information of geophysical exploration data and the attribute characteristics of geographic elements.

[0044] Step S123: Establish the mapping relationship between the attribute information of exploration data and the attribute characteristics of geographic elements, determine the core attribute items that can link geophysical exploration data and geographic elements, and obtain the core attribute mapping items.

[0045] By comparing and analyzing the set of attribute information from exploration data with the set of attribute characteristics from geographic elements, attribute items with inherent connections between the two are identified. For example, the exploration depth of geophysical exploration data is directly related to the depth range in the spatial distribution characteristics of stratigraphic elements; the magnetic field strength in measurement parameters may be related to the content of magnetic minerals in the material characteristics of stratigraphic elements. Through matching and analyzing these attribute items one by one, core attribute items that play a key role in linking geophysical exploration data and geographic elements are identified. These core attribute items accurately reflect the inherent connection between the two and are key elements in constructing spatial topological association rules. The identified core attribute items are organized into core attribute mapping items, clarifying the correspondence between each core attribute item in the exploration data attribute information and the geographic element attribute characteristics.

[0046] Step S124: For each core attribute mapping item, analyze the value range of the core attribute mapping item in geophysical exploration data and geographic elements, calculate the overlap of the value range, and obtain the attribute value overlap.

[0047] For example, step S1241: Extract the value type of the core attribute mapping item and determine whether the core attribute mapping item is a continuous value or a discrete value.

[0048] Before calculating the overlap of values, it is necessary to first clarify the value type of the core attribute mapping item. Different value types have different characteristics and manifestations, thus requiring different overlap calculation methods. By analyzing the attribute descriptions and data characteristics of the core attribute mapping items, it is determined whether they are continuous or discrete values. Continuous values ​​are typically attributes that can be represented numerically and change continuously within a certain range, such as the thickness of geographic elements or the measurement accuracy of exploration data; discrete values, on the other hand, are manifested as different categories or states, such as the lithological classification of geographic elements or the model of the acquisition instrument used in exploration data.

[0049] Step S1242: If the value is continuous, then perform the following steps:

[0050] When a core attribute mapping item is determined to be a continuous value, the overlap of its value ranges needs to be calculated according to the characteristics of continuous values. The calculation of the overlap of continuous values ​​mainly focuses on the degree of overlap between two value ranges. The overlap is quantified through mathematical methods to accurately reflect the degree of correlation between geophysical exploration data and geographic elements on this attribute.

[0051] Step S12421: Extract the value range of the core attribute mapping item in the geophysical exploration data attribute information to obtain the exploration data attribute value range. The exploration data attribute value range is a continuous numerical interval, including the upper limit and the lower limit of the value.

[0052] From the attribute information of geophysical exploration data, extract the value range corresponding to the core attribute mapping item. This value range is represented as a continuous numerical interval, including a clearly defined upper and lower limit. For example, the value range of the core attribute mapping item "exploration depth" for a certain geophysical exploration data may be from one depth value to another, where the smaller depth value is the lower limit and the larger depth value is the upper limit. Accurately extracting this interval is the basis for calculating the overlap.

[0053] Step S12422: Extract the value range of the same core attribute mapping item in the geographic element attribute features to obtain the geographic element attribute value range. The geographic element attribute value range is a continuous numerical interval, including the upper limit and the lower limit of the value.

[0054] Similarly, the value range of the same core attribute mapping item is extracted from the attribute characteristics of geographic features. This range is also a continuous numerical interval with an upper and lower limit. For example, the value range of a geographic feature for the core attribute mapping item "stratum thickness" may range from one thickness value to another. It is necessary to ensure that the extracted geographic feature attribute value range and the attribute value range of the geophysical exploration data belong to the same core attribute mapping item and have consistent units to ensure the validity of subsequent calculations.

[0055] Step S12423: Determine whether there is an overlap between the attribute value range of the exploration data and the attribute value range of the geographic element. If there is no overlap, the attribute value overlap is zero.

[0056] After obtaining the attribute value ranges of exploration data and geographic element attributes, the first step is to determine whether these two ranges overlap. Intersection refers to the overlapping portion of the two ranges. If the two ranges do not overlap at all, that is, the lower limit of one range is greater than the upper limit of the other range, or the upper limit of one range is less than the lower limit of the other range, it indicates that there is no correlation between the geophysical exploration data and geographic elements on this core attribute mapping item, and the attribute value overlap is zero.

[0057] Step S12424: If an intersection exists, calculate the size of the intersection range, which is the difference between the upper limit and the lower limit of the intersection.

[0058] When two ranges of values ​​intersect, it is necessary to calculate the size of the intersection range. The intersection range is determined by comparing the upper and lower limits of the two intervals. The lower limit of the intersection is the larger of the two lower limits, and the upper limit is the smaller of the two upper limits. Then, the difference between the upper and lower limits of the intersection is the size of the intersection range, reflecting the length of the overlapping portion of the two ranges.

[0059] Step S12425: Calculate the size of the union of the attribute value range of the exploration data and the attribute value range of the geographic element. The size of the union is the difference between the upper limit and the lower limit of the union.

[0060] When calculating the size of the intersection range, it is also necessary to calculate the size of the union range of the two ranges. The union range refers to all the areas covered by the merged intervals, with its lower limit being the smaller of the lower limits of the two intervals and its upper limit being the larger of the upper limits of the two intervals. The difference between the upper limit and the lower limit of the union range is the size of the union range, which reflects the total length covered by the merged ranges.

[0061] Step S12426: Use the ratio of the intersection range size to the union range size as the attribute value overlap.

[0062] Dividing the calculated intersection range by the union range yields the attribute value overlap for that core attribute mapping item. This ratio ranges from 0 to 1. A ratio closer to 1 indicates a higher degree of overlap between the two ranges, signifying a closer correlation between geophysical exploration data and geographic elements on that attribute; a ratio closer to 0 indicates a lower degree of overlap and a looser correlation.

[0063] Step S12427: Check whether there is any overlap between the boundary of the attribute value range of the exploration data and the boundary of the attribute value range of the geographic element. If there is boundary overlap, increase the boundary compensation value by a preset ratio for the attribute value overlap.

[0064] In some cases, two value ranges may not have obvious interval overlap, but they may have boundary overlap, meaning the upper limit of one range equals the lower limit of another, or vice versa. Although the intersection of these boundary overlaps is zero, they may still have some correlation in spatial topology. Therefore, it is necessary to check for such boundary overlaps. If they exist, a preset boundary compensation value should be added to the original attribute value overlap to appropriately increase the overlap and more comprehensively reflect the actual correlation. The preset boundary compensation value is set according to the importance placed on boundary correlation in practical applications.

[0065] Step S1243: If the value is discrete, then perform the following steps:

[0066] When a core attribute mapping item is determined to be a discrete value, a method for calculating the degree of overlap suitable for discrete categories is used. The calculation of the degree of overlap for discrete values ​​mainly focuses on the number of common elements between two sets of values, quantifying the degree of association by comparing the overlap of elements.

[0067] Step S12431: Extract the value range of the core attribute mapping item in the attribute information of geophysical exploration data to obtain the value range of exploration data attributes, wherein the value range of exploration data attributes is a discrete value set.

[0068] From the attribute information of geophysical exploration data, the value range corresponding to the core attribute mapping item is extracted. At this time, the value range is represented as a discrete set of values, and the elements in the set are the possible value categories of the attribute. For example, for the core attribute mapping item "lithology type", the value range of the exploration data may be a set including categories such as sandstone, shale, and limestone.

[0069] Step S12432: Extract the value range of the same core attribute mapping item in the geographic element attribute features to obtain the geographic element attribute value range, wherein the geographic element attribute value range is a discrete value set.

[0070] Similarly, the range of values ​​for the same core attribute mapping item can be extracted from the attribute characteristics of geographic features. This range is also a discrete set of values. For example, the range of values ​​for a geographic feature in the core attribute mapping item "tectonic type" may be a set including categories such as anticlines, synclines, and faults.

[0071] Step S12433: Calculate the intersection of the attribute value range of the exploration data and the attribute value range of the geographic element to obtain the discrete value set of the intersection.

[0072] The intersection operation is performed on two discrete sets of values: the range of values ​​for exploration data attributes and the range of values ​​for geographic element attributes. The result of this intersection operation is a new set that contains elements that exist in both original sets, representing the common value categories of the two ranges. The size of this intersection set reflects the degree of overlap in the categories between the two ranges.

[0073] Step S12434: Calculate the union of the attribute value range of the exploration data and the attribute value range of the geographic element to obtain the discrete value set of the union.

[0074] Simultaneously, a union operation is performed on the two discrete value sets to obtain a union discrete value set. This set contains all elements from the two original sets, with duplicate elements removed. The size of the union discrete value set reflects the total number of all different categories included after merging the two value ranges.

[0075] Step S12435: Count the number of values ​​in the discrete value set of the intersection to obtain the number of values ​​in the intersection.

[0076] Count the elements in the discrete value sets of the intersection, and determine the number of values ​​contained in each set; this is the number of values ​​in the intersection. The higher this number, the greater the overlap between the two value ranges in terms of discrete categories.

[0077] Step S12436: Count the number of values ​​in the discrete set of the union to obtain the number of values ​​in the union.

[0078] Similarly, by counting the elements in the discrete set of the union, we obtain the number of union values, which is a measure of the overall coverage of the two value ranges.

[0079] Step S12437: Use the number of values ​​in the intersection and the number of values ​​in the union as the attribute value overlap.

[0080] The ratio obtained by dividing the number of values ​​in the intersection by the number of values ​​in the union is the degree of overlap of attribute values ​​on the mapping item of this core attribute. Similar to continuous values, this ratio is between 0 and 1. The larger the ratio, the higher the degree of overlap between the two discrete value sets, and the closer the correlation between geophysical exploration data and geographic elements on this attribute.

[0081] Step S1244: Record the overlap of attribute values ​​corresponding to each core attribute mapping item and generate an attribute value overlap table.

[0082] After calculating the attribute value overlap for all core attribute mapping items, each core attribute mapping item and its corresponding overlap degree are recorded. A unique identifier is assigned to each core attribute mapping item, and the identifier is mapped one-to-one with the corresponding overlap degree value to form an attribute value overlap table. This table systematically organizes the correlation between geophysical exploration data and geographic elements on various core attributes. It serves as a key basis for subsequently assigning correlation weights to core attribute mapping items and constructing spatial topological correlation rules, ensuring the objectivity and accuracy of the correlation rule formulation process.

[0083] Step S125: Based on the overlap of attribute values, assign association weights to each core attribute mapping item to obtain a core attribute association weight table.

[0084] Based on the calculated attribute value overlap, association weights are assigned to each core attribute mapping item. A higher attribute value overlap indicates greater importance of the core attribute mapping item in associating geophysical exploration data with geographic features, thus warranting a higher weight; conversely, core attribute mapping items with lower overlap are assigned lower weights. When assigning weights, the relative importance of multiple core attribute mapping items needs to be comprehensively considered to ensure the rationality of the weight allocation. Each core attribute mapping item and its corresponding association weight are compiled into a core attribute association weight table.

[0085] Step S126: Based on the core attribute association weight table, construct the association judgment conditions between geophysical exploration data and geographic elements. When the weighted consistency of geophysical exploration data and geographic elements on the core attribute mapping item reaches a preset threshold, it is determined that there is a spatial topological association between geophysical exploration data and geographic elements.

[0086] A correlation determination criterion is constructed using a core attribute association weight table. For each geophysical exploration data set and each geographic feature, the degree of overlap of their values ​​on each core attribute mapping item is calculated. Each degree of overlap is multiplied by the corresponding association weight, and all products are summed to obtain a weighted degree of overlap. This weighted degree of overlap is compared with a preset threshold. If the weighted degree of overlap is greater than or equal to the preset threshold, a spatial topological association is determined between the geophysical exploration data and the geographic feature. The preset threshold needs to be adjusted according to actual exploration needs and data characteristics to ensure the accuracy and reliability of the association determination. Through this method, a valid spatial topological association between geophysical exploration data and geographic features can be objectively determined.

[0087] Step S127: For different types of geographic element topological relationships, construct corresponding association judgment conditions to obtain categorized association judgment conditions. The different types of geographic element topological relationships include connection relationships between geographic elements, inclusion relationships between geographic elements, and adjacency relationships between geographic elements.

[0088] Because geographic elements exhibit different types of topological relationships, such as connection, inclusion, and adjacency, it is necessary to construct association determination conditions for each type. For connection relationships, the focus is on the degree of association between geophysical exploration data and two connected geographic elements. For example, when the measurement parameters of geophysical exploration data are simultaneously related to the material characteristics of two connected geographic elements, a stronger association may exist. For inclusion relationships, attention is paid to the dual association between geophysical exploration data and both the containing and included geographic elements; the calculation of the weighted consistency degree needs to comprehensively consider the association with both. For adjacency relationships, in addition to the weighted consistency degree of the core attribute mapping item, the impact of distance factors between geographic elements on association determination can also be appropriately considered. By developing specific association determination conditions for different types of topological relationships, spatial topological association rules become more refined and targeted, improving the accuracy of association determination.

[0089] Step S128: Integrate the categorized association judgment conditions with the core attribute association weight table to form a spatial topology association rule. The spatial topology association rule includes association attribute items, association weights, and judgment thresholds.

[0090] By integrating the categorized association determination criteria with the core attribute association weight table, a complete spatial topological association rule is formed. This rule clearly defines the associated attribute items (i.e., core attribute mapping items), the association weight of each associated attribute item, and the determination thresholds for different types of topological relationships. For example, for geographic feature pairs with a connection relationship, the association rule specifies the core attribute mapping items participating in the association determination and their weights, as well as the determination threshold that the weighted consistency must reach; there are also corresponding provisions for inclusion and adjacency relationships. Through this integration, the spatial topological association rule becomes a systematic and comprehensive rule system, effectively guiding the determination of spatial topological associations between geophysical exploration data and geographic features.

[0091] Step S129: Collect all spatial topological association rules for different geographic element topological relationships and different geophysical exploration data types, and generate a spatial topological association rule set.

[0092] Considering the potential for different association patterns between various geographic feature topological relationships (connection, inclusion, adjacency) and different geophysical exploration data types (seismic, gravity, magnetic, etc.), it is necessary to develop corresponding spatial topological association rules for each combination. For example, the connection relationship between seismic exploration data and stratigraphic features may require specific association attribute items and judgment thresholds, while the adjacency relationship between gravity exploration data and topographic features may have different rule settings. All these spatial topological association rules for different situations are collected and categorized according to geographic feature topological relationship type and geophysical exploration data type to generate a spatial topological association rule set. This set of spatial topological association rules covers all possible association scenarios.

[0093] Step S130: Based on the spatial topological association rule set, the geophysical exploration data is topologically reconstructed to generate an exploration data topology structure containing topological nodes and topological edges. The topological nodes correspond to a single geophysical exploration data, and the topological edges correspond to the spatial association relationship between different geophysical exploration data.

[0094] With a set of spatial topological association rules, geophysical exploration data can be topologically reconstructed according to these rules. Each piece of geophysical exploration data is treated as a topological node, and topological edges are constructed based on their spatial relationships, forming a topological structure that reflects the spatial relationships between geophysical exploration data. This facilitates dynamic adjustment and spatial retrieval based on the needs of the target exploration mission.

[0095] Step S131: Treat each geophysical exploration data as an independent topological node, extract the attribute information and spatial location information of each geophysical exploration data, and generate an attribute description set for the topological node. The attribute description set of the topological node includes the geophysical exploration data identifier, the exploration type of the geophysical exploration data, the spatial coordinate range of the geophysical exploration data, and the core attribute values ​​of the geophysical exploration data.

[0096] In the geophysical exploration data of the aforementioned mineral resource exploration areas, each data set is considered an independent topological node. For each topological node, its attribute information and spatial location information need to be extracted from the geophysical exploration data. The geophysical exploration data identifier is a unique identifier for each data set, used to distinguish different topological nodes; the exploration type indicates which exploration method the data corresponding to the node belongs to; the spatial coordinate range is obtained through a GIS system, clarifying the geographical area covered by the data; and the core attribute value is the specific value or range of the data on the core attribute mapping item. Integrating the above information, a detailed attribute description is generated for each topological node, forming an attribute description set for the topological node. This attribute description set can comprehensively reflect the characteristics of each topological node.

[0097] Step S132: Based on the spatial topology association rule set, perform association determination on the geophysical exploration data corresponding to any two topology nodes, and determine whether the geophysical exploration data corresponding to any two topology nodes satisfy the spatial topology association rules.

[0098] Using a spatial topological association rule set, the geophysical exploration data corresponding to any two topological nodes in the attribute description set of topological nodes are used to determine their association. For each pair of topological nodes, based on their attribute information and spatial location information, and in conjunction with the corresponding rules in the spatial topological association rule set, it is determined whether they satisfy the spatial topological association rules. For example, for two topological nodes corresponding to seismic exploration data and gravity exploration data respectively, it is checked whether their exploration type, exploration depth, measurement parameters, and other attributes satisfy the association determination conditions on the core attribute mapping item, and whether the weighted consistency reaches a preset threshold. Through the above step-by-step determination method, it is determined whether a spatial association relationship exists between any two topological nodes.

[0099] Step S133: For two topological nodes that satisfy the spatial topological association rules, construct a topological edge connecting the two topological nodes, extract the weighted consistency of the geophysical exploration data corresponding to the two topological nodes on the core attribute mapping item, and use the weighted consistency as the association strength parameter of the topological edge.

[0100] When two topological nodes are determined to satisfy the spatial topological association rules, a topological edge is constructed between them. Simultaneously, the weighted coincidence degree of the geophysical exploration data corresponding to these two topological nodes on the core attribute mapping terms is calculated. Specifically, the coincidence degree of each core attribute mapping term is multiplied by its association weight and then summed. This weighted coincidence degree is used as the association strength parameter of the topological edge, reflecting the tightness of the spatial association between the two topological nodes. A larger association strength parameter indicates a closer spatial association between the two geophysical exploration data sets, which should be given more attention in subsequent data retrieval and analysis.

[0101] Step S134: Record the starting node identifier, ending node identifier, and association strength parameters of the topological edge, and generate a topological edge information table.

[0102] For each constructed topological edge, its starting node identifier and ending node identifier are recorded in detail to clearly identify which two topological nodes the edge connects. Simultaneously, the association strength parameter of the topological edge is also recorded. This information is then organized according to a specific format, including fields such as starting node identifier, ending node identifier, and association strength parameter, to generate a topological edge information table. This table displays the connection status and association strength of all topological edges in the topology.

[0103] Step S135: Sort all topological nodes by spatial location. Based on the topological relationships of geographic elements in GIS, adjust the spatial distribution order of the topological nodes so that the distribution order of the topological nodes is consistent with the spatial distribution order of the geographic elements.

[0104] To ensure that the distribution of topological nodes intuitively reflects the spatial distribution characteristics of geographic features, it is necessary to spatially sort all topological nodes. First, based on the spatial coordinate range of each topological node, its approximate location in the GIS is determined. Then, referencing the topological relationships of geographic features in the GIS, such as their distribution density and relative positions, the spatial distribution order of the topological nodes is adjusted. For example, in mountainous regions, where geographic features are more densely distributed, the corresponding topological nodes should also be relatively concentrated in their spatial distribution order; conversely, in plains regions where geographic features are sparsely distributed, the topological nodes should be correspondingly sparser. Through these adjustments, the distribution order of the topological nodes is made consistent with the spatial distribution order of the geographic features, enhancing the spatial intuitiveness of the topological structure.

[0105] Step S136: Construct a preliminary exploration data topology structure based on the spatial distribution order of the topology nodes and the topology edge information table. The preliminary exploration data topology structure includes a set of nodes and a set of edges.

[0106] After completing the spatial ordering of topological nodes and generating the topological edge information table, a preliminary exploration data topology is constructed. The node set consists of all topological nodes, each containing information from its attribute description set; the edge set consists of all topological edges from the topological edge information table, each containing a start node identifier, an end node identifier, and a correlation strength parameter. Following the spatial distribution order of the topological nodes, they are arranged in a virtual spatial coordinate system. Then, based on the connection relationships in the topological edge information table, topological edges are drawn between the corresponding nodes, forming a preliminary exploration data topology. This preliminary exploration data topology can roughly reflect the spatial relationships between geophysical exploration data, but there may still be some areas that require optimization.

[0107] Step S137: Extract the neighboring node information of each topological node in the preliminary exploration data topology structure and generate a node adjacency table.

[0108] For each topological node in the preliminary exploration data topology, extract the information of its directly connected topological nodes, i.e., adjacent nodes. For example, if a topological node is connected to three other topological nodes through topological edges, then these three topological nodes are its adjacent nodes. Record the identifier of each topological node and the identifiers of its adjacent nodes one-to-one to generate a node adjacency table. This node adjacency table facilitates subsequent examination of indirect relationships between topological nodes and helps to discover potential hidden connections in the preliminary topology.

[0109] Step S138: Based on the node adjacency relationship table, check whether there is an indirect association between the topology nodes. An indirect association refers to two topology nodes being associated through one or more intermediate topology nodes.

[0110] The node adjacency table reflects the direct relationships between topological nodes. However, in complex exploration data topologies, nodes may also have indirect relationships connected by one or more intermediate nodes. Examining these indirect relationships helps to fully understand the complex connections between exploration data, supplementing hidden relationships in the topology and making the topology more complete and accurate.

[0111] For example, in step S1381: select a topological node in the node adjacency relationship table as the starting check node, extract the direct adjacent nodes of the starting check node, and obtain the direct adjacency table of the starting node.

[0112] A topological node is randomly or sequentially selected from the node adjacency table as the starting check node. Starting from this node, all directly connected topological nodes are searched in the node adjacency table; these directly connected nodes constitute the starting node's direct adjacency nodes. The identifiers of these direct adjacency nodes are compiled into the starting node's direct adjacency table, which serves as the starting point for exploring indirect relationships.

[0113] Step S1382: Add the starting node to the set of checked nodes, and add the nodes in the direct adjacency list of the starting node to the set of nodes to be checked.

[0114] To avoid repeatedly processing nodes and getting stuck in loops during the inspection process, it is necessary to manage the inspection status of nodes. Adding the starting node to the set of inspected nodes indicates that the node has completed initial processing; adding all nodes in the direct adjacency list of the starting node to the set of nodes to be inspected indicates that these nodes are the objects to be inspected next, and they may form indirect connections with other nodes through the starting node.

[0115] Step S1383: Select a node from the set of nodes to be checked as the current node to be checked, extract the direct neighboring nodes of the current node to obtain the direct adjacency list of the current node.

[0116] A node is selected from the set of nodes to be checked in a certain order (e.g., first-in-first-out, random, etc.) as the current node to be checked. Then, based on the node adjacency table, all directly adjacent nodes of the current node to be checked are extracted to form the direct adjacency list of the current node. The direct adjacency list of the current node contains information about all nodes that are directly related to the current node to be checked.

[0117] Step S1384: Exclude nodes from the checked node set from the current node's direct adjacency list to obtain the unchecked adjacency nodes of the current node.

[0118] To focus on unprocessed nodes and avoid duplicate checks, nodes already in the checked node set need to be excluded from the current node's direct adjacency list. The remaining nodes are the current node's unchecked adjacency nodes, which are potential intermediate or terminating nodes that can form new indirect relationships.

[0119] Step S1385: Determine whether the current node has checked whether its adjacent nodes include other existing nodes besides the node being checked. If so, determine that the two nodes are indirectly associated through the current node.

[0120] The current node checks if its unchecked adjacent nodes include any nodes that already exist in the entire topology, excluding the starting node (these nodes may be outside the set of checked nodes but are part of the topology). If such nodes exist, it means that the starting node and this node are indirectly related through the current node, with the current node acting as an intermediary. For example, if the starting node is A, the current node is B, and the current node's unchecked adjacent nodes include C, but C is not the starting node, then A and C are indirectly related through B.

[0121] Step S1386: Record the starting node, intermediate node (currently checked node), and ending node of the indirect association, and generate an indirect association record table.

[0122] Once an indirect relationship is confirmed, detailed information about the relationship needs to be recorded, including the starting node (the initial node to be checked), the intermediate nodes (the current node to be checked), and the ending node (an existing node found among the unchecked adjacent nodes of the current node). These node identifiers are recorded in the order of starting node-intermediate node-ending node to generate an indirect relationship record table. This table is an important tool for tracking and organizing indirect relationships.

[0123] Step S1387: Add the currently checked node to the set of checked nodes, and add the unchecked adjacent nodes of the current node to the set of nodes to be checked.

[0124] After processing the current node, add it to the set of checked nodes and mark it as processed; at the same time, add the unchecked adjacent nodes of the current node to the set of nodes to be checked, so that the above nodes can be checked later to explore whether there are indirect associations with longer paths.

[0125] Step S1388: Repeat the above steps of selecting nodes from the set of nodes to be checked, extracting directly adjacent nodes, and determining indirect associations until the set of nodes to be checked is empty.

[0126] Following the steps described above, nodes are continuously selected from the set of nodes to be checked as the current node to be checked. Their direct adjacent nodes are extracted, it is determined whether a new indirect relationship is formed, the relationship information is recorded, and the set of checked nodes and the set of nodes to be checked are updated. This process is repeated until the set of nodes to be checked is empty, that is, all possible nodes have been checked and no new indirect relationships can be found.

[0127] Step S1389: Change the starting check node and repeat all the above steps until all topology nodes have completed the check as starting check nodes. Integrate all indirect association record tables and remove duplicate indirect association records. Duplicate indirect association records refer to indirect association records where the starting node, ending node, and intermediate node sequences are exactly the same.

[0128] After completing the indirect association check of a starting node, change the starting node and select the next topological node in the node adjacency table that was not used as a starting node. Repeat all the steps from extracting directly adjacent nodes to emptying the set of nodes to be checked. Once all topological nodes have been checked as starting nodes, integrate all the generated indirect association record tables. During the integration process, duplicate indirect association records need to be removed. The criteria for duplication are records with identical starting node, ending node, and intermediate node sequences, ensuring that each indirect association record is unique.

[0129] Step S13810: For each indirect association record, determine the number of intermediate nodes, distinguish between single intermediate node indirect association and multi-intermediate node indirect association, count the number of different types of indirect associations, and generate an indirect association statistical report. The indirect association statistical report includes indirect association records, the number of intermediate nodes, and the number of associated node pairs.

[0130] Further analysis is performed on the integrated indirect relationship records to determine the number of intermediate nodes for each record. Based on the number of intermediate nodes, indirect relationships are categorized into single-intermediate-node indirect relationships (with only one intermediate node) and multi-intermediate-node indirect relationships (with two or more intermediate nodes). The number of these two types of indirect relationships, as well as the total number of related node pairs (i.e., the number of start and end node pairs without considering intermediate nodes), are counted. This statistical information, along with the indirect relationship records, is then compiled to generate an indirect relationship statistical report. This report illustrates the distribution and complexity of indirect relationships within the topology.

[0131] Step S13811: Based on the indirect association statistics report, confirm all topological node pairs with indirect associations and complete the indirect association check.

[0132] Based on the indirect correlation statistical report, all indirectly related topological node pairs in the topological structure were comprehensively confirmed. By checking each indirect correlation record in the report, it was ensured that no node pair linked through one or more intermediate nodes was missed. This completed a comprehensive check of the indirect correlations between topological nodes, laying the foundation for subsequently constructing a complete exploration data topology.

[0133] Step S139: For topological nodes with indirect relationships, construct additional indirect topological edges, calculate the total indirect relationship strength, which is the product of the relationship strengths of each intermediate topological edge, and update the topological edge information table.

[0134] When indirect connections are found between topological nodes, indirect topological edges are constructed to supplement them. Simultaneously, the total connection strength of this indirect connection is calculated by multiplying the connection strength parameters of all intermediate topological edges on the path connecting the two nodes. For example, if the connection strength parameter from topological node A to topological node B is 'a', and the connection strength parameter from topological node B to topological node C is 'b', then the total indirect connection strength from topological node A to topological node C is 'a' multiplied by 'b'. The newly constructed indirect topological edges and their total connection strength parameters are added to the topological edge information table, updating the table to ensure it comprehensively reflects both direct and indirect connections between topological nodes.

[0135] Step S1310: Integrate the updated topology edge information table and node set to generate the topology structure of the exploration data.

[0136] The updated topological edge information table and node set are integrated to form the final exploration data topology. In this topology, the node set contains all the topological nodes and their attribute information corresponding to the geophysical exploration data, while the edge set covers all directly and indirectly related topological edges and their association strength parameters. Through this integration, the exploration data topology can completely and accurately reflect the spatial relationships between geophysical exploration data.

[0137] Step S140: Based on the requirements of the target exploration task, dynamically adjust the topological edge correlation strength in the topological structure of the exploration data to obtain the adjusted topological structure of the exploration data.

[0138] Since different exploration missions have different requirements, it is necessary to dynamically adjust the topological edge correlation strength in the exploration data topology according to specific mission requirements. By adjusting the correlation strength, the topology can better adapt to mission requirements, highlight the correlation between geophysical exploration data related to the mission, and improve the efficiency of data retrieval and analysis.

[0139] Step S141: Analyze the target exploration task requirements, extract the key requirement parameters in the target exploration task, and obtain a set of key requirement parameters. The set of key requirement parameters includes the target exploration type, the target exploration depth, and the type of key geographic features.

[0140] In the aforementioned mineral resource exploration area, assume the current target exploration task is to find a specific type of mineral resource. First, a detailed analysis of the requirements for this target exploration task is conducted. The target exploration type clarifies the main exploration methods to be used, such as seismic exploration or magnetic exploration; the target exploration depth specifies the required underground depth to determine the possible locations of mineral resources; and the key geographic feature types indicate the geographic elements related to the formation of this mineral resource, such as specific strata or structural zones. These key requirement parameters are extracted to form a set of key requirement parameters.

[0141] Step S142: Based on the set of key requirement parameters, determine the core attribute mapping items that are important to the target exploration task, and obtain the task core attribute items.

[0142] Based on the set of key requirement parameters, analyze which core attribute mapping items are most important to the target exploration task. For example, if the target exploration type is magnetic exploration, then the core attribute mapping items corresponding to the measurement parameters related to magnetic field strength are the core attribute items of the task; if the focus is on a specific geological feature type, then the core attribute mapping items related to the material characteristics and spatial distribution characteristics of that stratum will also become the core attribute items of the task. Through a step-by-step analysis of the key requirement parameters, select those core attribute mapping items that play a decisive role in achieving the target exploration task, and determine them as the core attribute items of the task.

[0143] Step S143: For the task core attribute item, adjust the association weight of the task core attribute item in the core attribute association weight table, increase the weight ratio of the task core attribute item, and obtain the adjusted core attribute association weight table.

[0144] In the core attribute association weight table, locate the association weights corresponding to the core attribute items of the task and adjust them. Based on the importance of the core attribute items to the target exploration task, appropriately increase their weight percentage. For example, increase the weight of core attribute items that originally had a certain weight by a certain proportion, allowing them to play a greater role in calculating the association strength of topological edges. After adjustment, the adjusted core attribute association weight table is obtained, which will be used to recalculate the association strength parameters of topological edges.

[0145] Step S144: Based on the adjusted core attribute association weight table, recalculate the association strength parameter of each topological edge in the topological structure of the exploration data to obtain the adjusted association strength parameter.

[0146] Step S1441: For each core attribute mapping item, determine the value type of that core attribute mapping item.

[0147] When recalculating the correlation strength parameters, it is essential to first clarify the value type of each core attribute mapping item. The value types of core attribute mapping items are mainly divided into two categories: continuous values ​​and discrete values. Continuous values ​​typically represent numerical values ​​that change continuously within a certain range, such as exploration depth and physical quantities in measurement parameters; discrete values, on the other hand, represent discontinuous categories or states, such as lithological types of strata and methods of acquiring exploration data. Accurately determining the value type is fundamental to subsequent calculations of the overlap degree, as different value types correspond to different overlap degree calculation methods.

[0148] Step S1442: If the core attribute mapping item is a continuous value and the attribute value is represented as a numerical range, then calculate the overlap of the values ​​of the two topological nodes on the core attribute mapping item as the ratio of the size of the intersection range of the two value ranges to the size of the size of the union range of the two value ranges.

[0149] When a core attribute mapping term has continuous values ​​and is represented as a numerical range, for example, the exploration depth range of the exploration data corresponding to one topological node is from a certain lower depth limit to a certain upper depth limit, and the exploration depth range of the exploration data corresponding to another topological node is from another lower depth limit to another upper depth limit, it is necessary to calculate the size of the intersection range and the size of the union range of these two numerical ranges. The size of the intersection range refers to the length of the overlapping part of the two value ranges, which is calculated by comparing the upper and lower limits of the two ranges to determine the overlapping interval. The size of the union range refers to the total length covered by the merged value ranges, which is calculated by taking the minimum lower limit and the maximum upper limit of the two ranges to determine the merging interval. Dividing the size of the intersection range by the size of the union range gives the value overlap degree on this core attribute mapping term. The larger the ratio, the closer the association between the two topological nodes on this attribute.

[0150] Step S1443: If the core attribute mapping item is a continuous value and the attribute value is a single numerical value, then if the values ​​of two topological nodes on the core attribute mapping item are equal, the value overlap is 1; otherwise, it is 0.

[0151] For core attribute mapping items with continuous values ​​but single numerical values, such as a specific measurement parameter value, the method determines whether the corresponding values ​​of two topological nodes are exactly the same. Since it is a single numerical value, there is no range overlap issue. Therefore, if the two values ​​are equal, it indicates complete overlap in that attribute, and the overlap degree is 1; if the values ​​are not equal, it indicates no overlap, and the overlap degree is 0. The above calculation method is applicable to attributes with clear single-point numerical characteristics and can quickly determine the consistency of two topological nodes in that attribute.

[0152] Step S1444: If the core attribute mapping item is a discrete value and the attribute value is a discrete set of values, then calculate the ratio of the intersection size to the union size of the two value sets as the value overlap.

[0153] When a core attribute mapping term has discrete values ​​and is represented as a set of discrete values, for example, if the stratigraphic lithology type set corresponding to one topological node includes sandstone and shale, and the stratigraphic lithology type set corresponding to another topological node includes shale and limestone, then it is necessary to calculate the intersection and union sizes of the two sets. The intersection size refers to the number of discrete values ​​commonly contained in the two sets; in the example above, shale is a common element, so the intersection size is 1. The union size refers to the total number of all distinct discrete values ​​in the two sets; in the example above, the union includes sandstone, shale, and limestone, so the size is 3. Dividing the intersection size by the union size yields the overlap of values ​​for that core attribute mapping term, reflecting the similarity between the two topological nodes in their discrete category attributes.

[0154] Step S1445: If the core attribute mapping item is a discrete value and the attribute value is a single discrete value, then if the values ​​of two topological nodes on the core attribute mapping item are equal, the value overlap is 1; otherwise, it is 0.

[0155] For core attribute mapping items with discrete values ​​and individual discrete values, such as exploration types like seismic exploration or gravity exploration, we directly compare whether the values ​​corresponding to two topological nodes are consistent. If the two values ​​are the same, such as both being seismic exploration, the overlap is 1; if the values ​​are different, such as one being seismic exploration and the other gravity exploration, the overlap is 0. This method is simple and direct, and suitable for cases where attribute values ​​are mutually exclusive.

[0156] Step S1446: Multiply the overlap of values ​​of each core attribute mapping item by the association weight of the core attribute mapping item in the adjusted core attribute association weight table to obtain the weighted contribution value of the core attribute mapping item.

[0157] After obtaining the overlap degree of each core attribute mapping item, it is necessary to calculate the corresponding association weight in the adjusted core attribute association weight table. Multiplying the overlap degree of each core attribute mapping item by its association weight yields the weighted contribution value of that core attribute mapping item to the topological edge association strength. The association weight reflects the importance of the core attribute mapping item in the target exploration task; the higher the weight, the greater the impact of its corresponding overlap degree on the association strength. Through this step, the association degree of each core attribute mapping item is weighted differently.

[0158] Step S1447: Sum the weighted contribution values ​​of all core attribute mapping items to obtain the association strength parameter of the topological edge.

[0159] The weighted contribution values ​​of all core attribute mapping terms are summed, and the result is the association strength parameter of the topological edge. The association strength parameter integrates the influence of all core attribute mapping terms and is a quantitative indicator measuring the degree of spatial correlation between the geophysical exploration data corresponding to two topological nodes. A larger association strength parameter value indicates a closer correlation between the two datasets, and they should be given higher priority in subsequent data retrieval and analysis.

[0160] Step S1448: Record the identifier of each topological edge and its corresponding adjusted association strength parameter, and generate an adjusted topological edge strength table.

[0161] After calculating the association strength parameters for each topological edge after adjustment, the above information needs to be recorded and organized. A unique identifier is assigned to each topological edge, and these identifiers are mapped one-to-one with their corresponding association strength parameters to form an adjusted topological edge strength table. This table displays the adjusted association strength of all topological edges and serves as a crucial basis for subsequent selection of topological edges to be optimized and for adjusting the topological structure. It also facilitates quick querying and comparison of the association degrees of different topological edges.

[0162] Step S1449: Extract the maximum and minimum values ​​of the associated strength parameters from the adjusted topological edge strength table, and calculate the strength distribution interval.

[0163] To better analyze and apply the association strength parameters, it is necessary to understand their overall distribution. Extract the maximum and minimum values ​​of all association strength parameters from the adjusted topological edge strength table. The maximum value represents the strongest association in the topological structure, and the minimum value represents the weakest association. Subtracting the maximum and minimum values ​​gives the strength distribution interval.

[0164] Step S14410: Based on the intensity distribution range, divide the associated intensity parameters into different intensity level ranges and generate an intensity level classification standard.

[0165] Based on the intensity distribution range and the sensitivity of the target exploration task to the correlation strength, the correlation strength parameter is divided into several different intensity level ranges. For example, the intensity distribution range can be divided into several segments, each corresponding to a strength level, such as strong correlation, moderate correlation, weak correlation, etc. Alternatively, non-uniform interval division criteria can be set according to actual needs to further subdivide important correlation strength ranges. Each intensity level range has clear upper and lower limits. The generated intensity level division criteria are used for the subsequent intuitive description and display of the topological edge correlation strength, enabling exploration personnel to quickly determine the correlation type of topological edges.

[0166] Step S14411: According to the strength level classification standard, mark the corresponding strength level for each topological edge and add the strength level to the adjusted topological edge strength table.

[0167] Based on the strength level classification standard, each topological edge in the adjusted topological edge strength table is labeled with its strength level. By comparing the associated strength parameters of each topological edge with the upper and lower limits of the strength level range, its strength level is determined, and this level information is added to the adjusted topological edge strength table. Thus, the adjusted topological edge strength table not only contains the specific values ​​of the associated strength parameters but also includes an intuitive description of the strength level, further enriching the attribute information of the topological edges.

[0168] Step S14412: Integrate the adjusted topology edge strength table with the node connection information of each topology edge to obtain the adjusted topology edge information. The adjusted correlation strength parameter includes specific values ​​and strength level labels.

[0169] Finally, the adjusted topology edge strength table is integrated with the node connection information of each topology edge. The node connection information includes the start node identifier and end node identifier of the topology edge. The integrated adjusted topology edge information fully describes the connected objects, the specific values ​​of the associated strength parameters, and the corresponding strength level of each topology edge.

[0170] Step S145: Extract the topological edges in the topological structure of the exploration data whose correlation strength parameters are lower than the adjusted preset threshold, and mark the corresponding topological edges as topological edges to be optimized.

[0171] After obtaining the adjusted correlation strength parameters, an adjusted preset threshold is set. This preset threshold is determined based on the specific requirements of the target exploration task and the adjusted core attribute correlation weight table, and is used to filter out topological edges with low correlation strength. All topological edges with correlation strength parameters below this threshold are extracted and marked as topological edges to be optimized. The correlation between the geophysical exploration data corresponding to these topological edges to be optimized may have low relevance to the target exploration task and requires further analysis and optimization.

[0172] Step S146: Analyze the geophysical exploration data corresponding to the two topological nodes connected by the topological edge to be optimized, and determine whether the geophysical exploration data corresponding to the two topological nodes connected by the topological edge to be optimized have task-related attributes that are not included in the core attribute mapping item.

[0173] For each topological edge marked as an edge to be optimized, analyze the attribute information of the geophysical exploration data corresponding to the two topological nodes it connects. Carefully examine these data for attributes that are relevant to the target exploration task but have not yet been included in the core attribute mapping. For example, in a task searching for a specific mineral resource, a geophysical exploration document may contain measurement data related to associated elements of that mineral, but this attribute has not previously been included as a core attribute mapping item. Through the above analysis, uncover potentially overlooked task-related attributes.

[0174] Step S147: If a task-related attribute exists, add the task-related attribute as a new core attribute mapping item, calculate the overlap of the values ​​of the new core attribute mapping item between the two topology nodes, assign association weights to the new core attribute mapping item, and update the adjusted core attribute association weight table.

[0175] If a task-related attribute not included in the core attribute mapping is found in the geophysical exploration data of the topological edge connections to be optimized, this attribute is added as a new core attribute mapping term. Then, the overlap of values ​​for the two topological nodes on this new core attribute mapping term is calculated, and an appropriate association weight is assigned to it based on the importance of the attribute to the target exploration task. The new core attribute mapping term and its association weight are added to the adjusted core attribute association weight table, completing the table update. By adding a new core attribute mapping term, task-related factors can be considered more comprehensively, improving the accuracy of topological edge association strength calculation.

[0176] Step S148: Based on the updated and adjusted core attribute association weight table, recalculate the association strength parameters of the topology edge to be optimized, and determine whether the association strength parameters of the topology edge to be optimized have reached the adjusted preset threshold.

[0177] Using the updated and adjusted core attribute association weight table, recalculate the association strength parameters of the topological edges to be optimized. Multiply the overlap of newly added core attribute mapping terms by their association weights and add this product to the weighted overlap calculation. Then, compare the recalculated association strength parameters with the adjusted preset threshold to see if they reach or exceed the threshold. If the threshold is reached, it means that by adding new core attribute mapping terms, the association strength of the topological edge to be optimized has been effectively improved, and it can no longer be considered as an optimization target; if the threshold is still not reached, further optimization is required.

[0178] Step S149: For topological edges that have not yet reached the adjusted preset threshold, check whether the geophysical exploration data corresponding to the topological nodes connected to the topological edge are related to the key geographic features of the target exploration task.

[0179] For topological edges that, after the above optimization, still do not reach the adjusted preset threshold in terms of correlation strength parameters, further checks are made to determine whether the geophysical exploration data corresponding to the topological nodes they connect are related to the key geographic features of the target exploration task. Key geographic features are determined based on a set of critical requirement parameters and are closely related to the target exploration task. For example, if the key geographic feature is a fault zone, it is checked whether the geophysical exploration data corresponding to the topological edge to be optimized is within the spatial range of that fault zone, or whether its measurement parameters reflect the characteristics of that fault zone.

[0180] Step S1410: If a correlation exists, extract the attribute features of the key geographic elements, use the attribute features of the key geographic elements as additional correlation factors, add them to the calculation process of the correlation strength of the topological edge, and recalculate the correlation strength parameters of the topological edge.

[0181] If the geophysical exploration data of the topological edge to be optimized is related to a key geographic feature, then the attribute characteristics of that key geographic feature, such as its structural and material characteristics, are extracted. These attribute characteristics are then added as additional correlation factors to the calculation of the topological edge correlation strength. Specifically, the degree of matching between the geophysical exploration data and the key geographic feature on these additional correlation factors is quantified, multiplied by an appropriate weight, and added to the weighted consistency factor to recalculate the topological edge correlation strength parameter. By introducing additional correlation factors, the correlation between the topological edge to be optimized and the target exploration task can be further enhanced, potentially bringing its correlation strength parameter to the adjusted preset threshold.

[0182] Step S1411: Integrate all adjusted correlation strength parameters, update the topology edge information table, and adjust the topology of the exploration data based on the updated topology edge information table to obtain the adjusted topology of the exploration data.

[0183] All adjusted and recalculated correlation strength parameters are integrated, and the corresponding fields in the topology edge information table are updated. Then, based on the updated topology edge information table, the exploration data topology is adjusted. For topology edges whose correlation strength parameters have changed, their correlation strength parameters are updated; for newly constructed topology edges, they are added to the topology; for those topology edges whose correlation strength is still too low after optimization and cannot be improved, they can be temporarily removed from the topology or marked as weakly correlated edges. Through these adjustments, an adjusted exploration data topology is obtained, which better meets the needs of the target exploration mission and highlights the correlations between geophysical exploration data related to the mission.

[0184] Step S150: Based on the adjusted exploration data topology, realize the spatial calling and display of geophysical exploration data in GIS, and obtain the spatial calling result of exploration data.

[0185] The adjusted exploration data topology can now effectively reflect the spatial relationships between geophysical exploration data required by the target exploration mission. The next step is to leverage this topology to enable spatial access and display of the geophysical exploration data within a GIS, allowing exploration personnel to intuitively view and analyze the relevant data.

[0186] Step S151: Receive the exploration data retrieval request from the GIS, parse the spatial range parameter and the task requirement parameter in the exploration data retrieval request, and obtain the retrieval spatial range and retrieval task requirements.

[0187] In a GIS system, exploration personnel issue data retrieval requests based on the actual needs of their exploration work. These requests include spatial extent parameters and task requirement parameters. The spatial extent parameters specify the geographical area from which the data needs to be retrieved, such as a specific latitude and longitude range; the task requirement parameters clarify the purpose and related requirements of the retrieved data, such as its use for structural analysis or reservoir prediction. The request is parsed to extract the spatial extent and task requirements.

[0188] Step S152: Based on the called spatial range, query the distribution of geographic elements in the GIS, extract the topological relationships of geographic elements within the called spatial range, and obtain the topological topology of geographic elements within the called range.

[0189] Based on the parsed spatial scope, the distribution of geographic features within that scope is queried in the GIS system. Then, the topological relationships between these geographic features are extracted, including connectivity, containment, and adjacency relationships, forming a topology of the geographic features within the scope. This topology reflects the spatial organization of the geographic features within the scope.

[0190] Step S153: Spatial matching is performed between the topology of the geographic features in the call range and the topology of the adjusted exploration data to determine the topological nodes in the adjusted exploration data topology that are within the call space range, thus obtaining a set of nodes within the call range.

[0191] The topology of the geographic features within the call area reflects the spatial distribution and interrelationships of geographic features within the call area, while the adjusted exploration data topology contains the correlation information of geophysical exploration data related to the target exploration task. Spatially matching the two aims to accurately locate the topological nodes within the call area. The exploration data corresponding to these nodes are the core objects of this call, and their accuracy directly affects the effectiveness of subsequent data analysis.

[0192] Step S1531: Parse the topology of the geographic features in the call range, extract the spatial coordinate range of all geographic features in the topology of the geographic features in the call range, and obtain the geographic coordinate set of the call range.

[0193] First, the topology of the geographic features within the call area is parsed. This topology contains spatial information on various geographic features within the call area, such as topography, strata, water bodies, and man-made structures. Through this parsing process, the spatial coordinate range of each geographic feature is extracted. These coordinate ranges are typically represented by latitude and longitude or Cartesian coordinates, defining the location and extent of the geographic feature in space. Finally, the spatial coordinate ranges of all geographic features are aggregated to form the geographic coordinate set of the call area. This set comprehensively reflects the spatial coverage of geographic features within the call area.

[0194] Step S1532: Extract the spatial coordinate range of geophysical exploration data corresponding to each topological node in the adjusted exploration data topology structure to obtain the node spatial coordinate set.

[0195] In the adjusted exploration data topology, each topological node corresponds to a specific geophysical exploration data set, and each data set has a defined spatial coordinate range, which represents the geographical area covered by the data. By traversing all topological nodes in the topology, the spatial coordinate range of the corresponding geophysical exploration data is extracted one by one. These coordinate ranges are also based on the same coordinate system as the geographic coordinate set of the called range to ensure consistency in spatial matching.

[0196] Step S1533: Compare the spatial range of the node spatial coordinate set with the geographic coordinate set of the calling range to determine whether the spatial coordinate range of each topology node is completely within the geographic coordinate set of the calling range.

[0197] The spatial coordinate range of each topology node in the node spatial coordinate set is compared one by one with the geographic coordinate set of the calling scope. The core of the comparison is to determine whether the spatial coordinate range of the topology node is completely contained within the geographic coordinate set of the calling scope. Specifically, it checks whether all boundaries of the spatial coordinate range of the topology node are within the spatial boundaries defined by the geographic coordinate set of the calling scope. If all boundaries are within them, then the spatial coordinate range of the topology node is completely within the calling scope. This step is the basis for screening nodes within the calling scope, ensuring that nodes that fully meet the spatial range requirements are initially identified.

[0198] Step S1534: Record the topological nodes whose spatial coordinate range is completely within the geographic coordinate set of the call range, and generate a complete list of nodes.

[0199] For topological nodes whose spatial coordinates are determined to be entirely within the geographic coordinate set of the call area, their unique identifiers are recorded to form a complete list of included nodes. The geophysical exploration data corresponding to these nodes are spatially located entirely within the call area and represent the most direct and relevant part of the data call; therefore, they should be prioritized for inclusion in the node set within the call area. Generating a complete list of included nodes helps to quickly filter out the core call data.

[0200] Step S1535: Determine whether the spatial coordinate range of each topology node is partially within the geographical coordinate set of the calling range. Partially within the geographical coordinate set of the calling range means that the spatial coordinate range of the node and the geographical coordinate set of the calling range have an intersection.

[0201] Besides topological nodes that are entirely within the call space, there are also topological nodes whose spatial coordinate ranges partially overlap with the geographic coordinate set of the call space. For these nodes, it is necessary to determine whether their spatial coordinate ranges intersect with the geographic coordinate set of the call space; that is, part of the node's spatial location is within the call space, and part is outside the call space. The above-mentioned situation is quite common in actual exploration and may involve cross-regional exploration data, requiring further evaluation of its relevance to the call task requirements.

[0202] Step S1536: Record the topological nodes whose spatial coordinate range is partially within the geographic coordinate set of the call range, and generate a partial list of nodes.

[0203] The identifiers of topological nodes whose spatial coordinate range partially falls within the geographic coordinate set of the call area are recorded to generate a partially contained node list. Although the exploration data corresponding to these nodes are not entirely within the call area, their partial coverage area is related to the call area and may contain information valuable to the target exploration task. The generation of the partially contained node list provides an object for subsequent correlation analysis and filtering.

[0204] Step S1537: Analyze the correlation between the geophysical exploration data corresponding to each topological node in the partially included node list and the call task requirements, extract the attribute items related to the call task requirements, and obtain the partially included node association attributes.

[0205] For each topological node in the partially included node list, it is necessary to conduct an in-depth analysis of the correlation between its corresponding geophysical exploration data and the task requirements. Based on the exploration objectives and geological features of interest clearly stated in the task requirements, relevant attribute items are extracted from the attribute information of the geophysical exploration data. For example, measurement parameters related to the target mineral type and stratigraphic information related to specific geological structures are extracted. The extracted attribute items constitute the association attributes of the partially included nodes and are specific indicators for evaluating the correlation between nodes.

[0206] Step S1538: Calculate the matching degree between the node association attributes and the calling task requirement parameters. The matching degree is the ratio of the number of overlapping related attribute items to the total number of calling task requirement parameters.

[0207] After obtaining the associated attributes of some included nodes, their matching degree is calculated against the task requirement parameters. The task requirement parameters are the standard for measuring data relevance and contain all the necessary requirements for achieving the target exploration task. Each attribute item in the associated attributes of the included nodes is compared with its corresponding item in the task requirement parameters, and the number of overlapping attribute items is counted. The ratio of the overlapping number to the total number of task requirement parameters is the matching degree. The higher the matching degree, the stronger the relevance between the exploration data corresponding to that included node and the task requirements.

[0208] Step S1539: Record the partially contained nodes whose matching degree reaches the task matching threshold, and generate a list of valid partially contained nodes.

[0209] Based on the importance of the target exploration task and the requirements for data relevance, a task matching threshold is set. The calculated matching degree of partially contained nodes is compared with this task matching threshold. If the matching degree reaches or exceeds the task matching threshold, the exploration data corresponding to the partially contained node is considered to have sufficient value for the calling task, and its node identifier is recorded to generate a list of valid partially contained nodes. Although the nodes in this list are spatially partially contained within the calling scope, they are included as candidates in the node set within the calling scope due to their high relevance to the task requirements.

[0210] Step S15310: Integrate the fully contained node list with the valid partially contained node list, and remove duplicate topology node identifiers.

[0211] The complete list of nodes and the list of nodes with valid partial inclusion are integrated into a preliminary set of nodes within the call scope. Since some nodes may appear in both lists simultaneously—for example, a node's spatial coordinates may be entirely within the call scope, and its associated attributes may also meet the task requirements—the integrated list needs to be deduplicated to ensure that each topology node identifier appears only once, avoiding duplicate operations during subsequent data extraction and processing.

[0212] Step S15311: Label the spatial inclusion type of each integrated topology node. The spatial inclusion type is divided into complete inclusion and effective partial inclusion. Generate a node set within the call range. The node set within the call range includes node identifier and spatial inclusion type.

[0213] After integration and deduplication, the spatial inclusion type of each topological node is labeled. There are two types: "complete inclusion" and "partially contained," corresponding to nodes in the complete inclusion node list and the partially contained node list, respectively. Labeling the spatial inclusion type helps distinguish exploration data with different spatial relationships during subsequent data retrieval and display, providing exploration personnel with more comprehensive spatial information. The final generated set of nodes within the retrieval scope includes node identifiers and their corresponding spatial inclusion types, fully defining the topological nodes involved in this retrieval.

[0214] Step S154: Extract the complete geophysical exploration data corresponding to each topological node in the node set within the call range to obtain the exploration data set within the call range.

[0215] The complete geophysical exploration data corresponding to each topological node in the node set within the scope of the database is extracted. This data includes the raw data, processing reports, and image data. The data is then organized according to the identifiers of the topological nodes to form a collection of exploration data within the scope of the database. It is ensured that every piece of data in the collection is complete and accurate, meeting the needs of exploration personnel for detailed data analysis.

[0216] Step S155: Based on the task request, extract the topological edge association information that matches the task request from the adjusted exploration data topology structure to obtain task association edge information.

[0217] Based on the task requirements, such as structural analysis, topological edge association information relevant to the task is extracted from the adjusted exploration data topology. Topological edges with high association strength parameters and strong relevance to the task requirements are selected, and their association information, such as start node identifier, end node identifier, and association strength parameters, is compiled into task-related edge information. This information reflects the task-related relationships between geophysical exploration data within the scope of the call.

[0218] Step S156: Based on the task association edge information, determine the geophysical exploration data group with association relationship in the exploration data set within the call range, and obtain the associated data group.

[0219] Based on the task-related edge information, geophysical exploration data groups with correlations are identified within the exploration data set within the scope of the call. Each topological edge connecting two topological nodes forms a correlated data group. If indirect correlations exist, a correlated data group containing multiple data sets can also be formed. By combining interconnected geophysical exploration data in this way, it becomes easier for exploration personnel to analyze the relationships between data as a whole and discover potential geological patterns.

[0220] Step S157: Spatially overlay each geophysical exploration data in the set of exploration data within the scope of the call with the corresponding geographic elements in the GIS, so that the spatial location of the geophysical exploration data corresponds precisely with the spatial location of the geographic elements, and obtain the spatial overlay result.

[0221] Each geophysical exploration data point within the retrieved data set is spatially overlaid with its corresponding geographic features in the GIS system, based on its spatial coordinate range. This spatial overlay function of GIS ensures a precise correspondence between the spatial locations of geophysical exploration data and geographic features. For example, overlaying seismic exploration profiles with corresponding stratigraphic features aligns the reflection layers in the profiles with actual stratigraphic interfaces; overlaying gravity anomaly data with topographic features visually demonstrates the relationship between gravity anomalies and topographic relief. Through spatial overlay, the resulting spatial distribution characteristics of the geophysical exploration data become more clearly visible.

[0222] Step S158: For the associated data group, connect the spatial locations corresponding to the associated geophysical exploration data with lines of different styles in the spatial overlay results. Set the line style to the style corresponding to the association strength level of the topological edge. Different association strength levels correspond to different line widths and line colors.

[0223] For associated data sets, the spatial locations of the associated geophysical exploration data are connected by lines in the spatial overlay results. Based on the association strength parameters of the topological edges, the association strength is divided into different levels, such as strong association, moderate association, and weak association. Different line styles are set for different association strength levels; for example, strong association corresponds to a wider red line, moderate association to a medium-width yellow line, and weak association to a narrower blue line. This visualization method allows exploration personnel to intuitively judge the tightness of the association between the data in the associated data set and quickly identify important relationships.

[0224] Step S159: Extract the geophysical exploration data attribute information from the spatial overlay result, generate attribute annotation boxes, and bind the attribute annotation boxes to the corresponding spatial locations of the geophysical exploration data to obtain annotated spatial overlay results.

[0225] Attribute information, such as exploration type, exploration depth, and measurement parameters, is extracted from the spatial overlay results of geophysical exploration data. An attribute label box is generated for each data set, displaying the aforementioned attribute information within it. Then, the attribute label boxes are bound to the corresponding spatial location of the geophysical exploration data in the GIS, allowing the label boxes to move with the spatial location of the data. When exploration personnel click on the spatial location of a data set in the GIS, the corresponding attribute label box will appear, facilitating the viewing of detailed attribute information. By adding attribute labels, annotated spatial overlay results are obtained, further enriching the displayed content.

[0226] Step S1510: Adjust the display scale parameter of the labeled spatial overlay result according to the display resolution of the GIS, and set the display scale parameter to a value that is compatible with the display resolution of the GIS.

[0227] To ensure that labeled spatial overlay results are displayed clearly and completely on the GIS display interface, the display scale parameter needs to be adjusted according to the GIS display resolution. Different display resolutions require different suitable display scales. By calculating the pixel size of the display interface and the actual geographical extent of the spatial overlay results, a suitable display scale parameter is determined, allowing the spatial overlay results to be displayed completely on the interface while ensuring that details are clearly visible. After adjusting the display scale parameter, the labeled spatial overlay results can better adapt to the GIS display environment.

[0228] Step S1511: Output the labeled spatial overlay result after adjusting the display scale parameters to the GIS display interface, and generate a call result log at the same time. The call result log includes the call time, call spatial range, number of called data and number of associated data groups.

[0229] The labeled spatial overlay results, with adjusted display scale parameters, are output to the GIS display interface for exploration personnel to view and analyze. Simultaneously, a data retrieval log is generated, recording relevant information for this data retrieval, including retrieval time, spatial range, number of retrieved data sets, and number of associated data groups. The retrieval log helps track and manage data retrieval activities.

[0230] Step S1512: Integrate the output content of the display interface with the call result log to obtain the spatial call result of the exploration data.

[0231] The labeled spatial overlay results output on the GIS display interface are integrated with the retrieval result log to form the final spatial retrieval result of exploration data. This spatial retrieval result not only includes the visualized spatial distribution and correlation of the data, but also relevant information about the retrieval process, which can comprehensively meet the needs of exploration personnel for spatial retrieval of geophysical exploration data.

[0232] Throughout the process, potentially sensitive data, such as geophysical exploration data, was processed. To protect this data's privacy and prevent leakage, data encryption technology was employed to encrypt data during transmission and storage, ensuring that data was not stolen during transmission and not illegally accessed during storage. Simultaneously, strict access control was implemented for users accessing the data; only authorized personnel could access the relevant data, and all data access operations were logged for auditing and traceability. These technical measures effectively guaranteed data security and privacy.

[0233] In one exemplary embodiment, a geophysical exploration data management system integrated with GIS is provided. This system may be a terminal, server, etc., and its internal structure diagram may be as follows: Figure 2 As shown, the GIS-integrated geophysical exploration data management system includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a GIS-integrated geophysical exploration data management method. The display unit of this GIS-integrated geophysical exploration data management system is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of this GIS-integrated geophysical exploration data management system can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad set on the casing of the GIS-integrated geophysical exploration data management system, or an external keyboard, touchpad, or mouse, etc.

[0234] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A method for managing geophysical exploration data combined with GIS, characterized in that, The method includes: Extract the topological relationships of geographic elements in the target exploration area from GIS, and generate a set of topological relationship descriptions of geographic elements. The set of topological relationship descriptions of geographic elements includes the connection relationships between geographic elements, the inclusion relationships between geographic elements, and the adjacency relationships between geographic elements. Based on the topological relationship description set of geographic elements, spatial topological association rules between geophysical exploration data and geographic elements are constructed to obtain a set of spatial topological association rules. Based on the aforementioned set of spatial topological association rules, geophysical exploration data are topologically reconstructed to generate an exploration data topology structure containing topological nodes and topological edges. The topological nodes correspond to a single geophysical exploration data, and the topological edges correspond to the spatial association relationships between different geophysical exploration data. Based on the requirements of the target exploration task, the topological edge correlation strength in the topological structure of the exploration data is dynamically adjusted to obtain the adjusted topological structure of the exploration data. Based on the adjusted topology of the exploration data, the spatialization of geophysical exploration data in GIS is realized, and the spatialization result of the exploration data is obtained. The process of topologically reconstructing geophysical exploration data based on the spatial topological association rule set to generate an exploration data topological structure containing topological nodes and edges includes: Each geophysical exploration data is treated as an independent topological node. The attribute information and spatial location information of each geophysical exploration data are extracted to generate an attribute description set for the topological node. The attribute description set of the topological node includes the geophysical exploration data identifier, the exploration type of the geophysical exploration data, the spatial coordinate range of the geophysical exploration data, and the core attribute values ​​of the geophysical exploration data. Based on the aforementioned spatial topology association rule set, the geophysical exploration data corresponding to any two topology nodes are associated to determine whether the geophysical exploration data corresponding to any two topology nodes satisfy the spatial topology association rules. For two topological nodes that satisfy the spatial topological association rules, construct a topological edge connecting the two topological nodes, extract the weighted consistency of the geophysical exploration data corresponding to the two topological nodes on the core attribute mapping item, and use the weighted consistency as the association strength parameter of the topological edge; Record the starting node identifier, ending node identifier, and association strength parameter of the topological edge to generate a topological edge information table. All topological nodes are spatially sorted, and the spatial distribution order of the topological nodes is adjusted based on the topological relationships of geographic elements in GIS so that the distribution order of the topological nodes is consistent with the spatial distribution order of geographic elements. Based on the spatial distribution order of topological nodes and the topological edge information table, a preliminary exploration data topological structure is constructed, which includes a set of nodes and a set of edges. Extract the neighboring node information of each topological node in the preliminary exploration data topology structure to generate a node adjacency table; Based on the node adjacency table, check whether there is an indirect association between topological nodes. An indirect association means that two topological nodes are associated through one or more intermediate topological nodes. For topological nodes with indirect relationships, supplement the indirect relationship topological edges, calculate the total indirect relationship strength, which is the product of the relationship strengths of each intermediate topological edge, and update the topological edge information table. Integrate the updated topology edge information table and node set to generate the topology structure of the exploration data; The step of dynamically adjusting the topological edge correlation strength in the topological structure of the exploration data according to the requirements of the target exploration task, to obtain the adjusted topological structure of the exploration data, includes: The target exploration task requirements are analyzed, and key requirement parameters in the target exploration task are extracted to obtain a set of key requirement parameters. The set of key requirement parameters includes the target exploration type, the target exploration depth, and the types of key geographic features of interest. Based on the set of key requirement parameters, the core attribute mapping items that are important to the target exploration task are determined, and the core attribute items of the task are obtained. For the core attribute items of the task, adjust the association weight of the core attribute items in the core attribute association weight table to increase the weight ratio of the core attribute items of the task, and obtain the adjusted core attribute association weight table. Based on the adjusted core attribute association weight table, the association strength parameter of each topological edge in the topological structure of the exploration data is recalculated to obtain the adjusted association strength parameter. Extract the topological edges in the topological structure of the exploration data whose correlation strength parameters are lower than the adjusted preset threshold, and mark the corresponding topological edges as topological edges to be optimized. Analyze the geophysical exploration data corresponding to the two topological nodes connected by the topological edge to be optimized, and determine whether the geophysical exploration data corresponding to the two topological nodes connected by the topological edge to be optimized have any task-related attributes that are not included in the core attribute mapping item. If a task-related attribute exists, add the task-related attribute as a new core attribute mapping item, calculate the overlap of the value of the new core attribute mapping item between the two topology nodes, assign association weights to the new core attribute mapping item, and update the adjusted core attribute association weight table. Based on the updated and adjusted core attribute association weight table, the association strength parameters of the topology edge to be optimized are recalculated, and it is determined whether the association strength parameters of the topology edge to be optimized reach the adjusted preset threshold. For topological edges that have not yet reached the adjusted preset threshold, check whether the geophysical exploration data corresponding to the topological nodes connected by the topological edge to be optimized are related to the key geographic features of the target exploration task. If a correlation exists, extract the attribute features of the key geographic elements and use them as additional correlation factors in the calculation of the correlation strength of the topological edges. Recalculate the correlation strength parameters of the topological edges. Integrate all adjusted correlation strength parameters, update the topology edge information table, and adjust the topology of the exploration data based on the updated topology edge information table to obtain the adjusted topology of the exploration data.

2. The geophysical exploration data management method combined with GIS according to claim 1, characterized in that, The step of extracting the topological relationships of geographic features in the target exploration area from the GIS and generating a set of topological relationship descriptions of geographic features includes: Determine the spatial extent of the target exploration area in GIS, extract the geographic feature types within the spatial extent, and obtain a set of geographic feature types, which include topographic features, water features, stratigraphic features, and man-made structure features. For each type of geographic feature, the spatial coordinates and boundary information of all geographic features under that geographic feature type are extracted to obtain a set of geographic feature spatial information. The set of geographic feature spatial information includes the vertex coordinate sequence of the geographic feature and the boundary contour description of the geographic feature. The geographic elements in the spatial information set of geographic elements are compared pairwise to determine whether any two geographic elements have a connection relationship. The connection relationship refers to the existence of a common line segment on the boundary of the two geographic elements. Record the coordinate information of connected geographic feature pairs and their common line segments, and generate a connection relationship record table; Determine whether any two geographic elements have an inclusion relationship, where the inclusion relationship means that the entire spatial range of one geographic element is within the spatial range of another geographic element; Record the geographic feature pairs that have an inclusion relationship and the inclusion ratio information of their spatial extent, and generate an inclusion relationship record table; Determine whether any two geographic elements have an adjacent relationship, wherein the adjacent relationship refers to the boundary distance between the two geographic elements being less than a preset distance and having no common line segments; Record the pairs of geographical features that are adjacent and their shortest distances to each other, and generate an adjacent relationship record table; By integrating the connection relationship record table, the inclusion relationship record table, and the adjacent relationship record table, a geographic feature topology relationship description set containing all geographic feature topology relationships is generated.

3. The geophysical exploration data management method combined with GIS according to claim 1, characterized in that, Based on the topological relationship description set of geographic elements, spatial topological association rules between geophysical exploration data and geographic elements are constructed, resulting in a set of spatial topological association rules, including: The attribute information of geophysical exploration data is extracted to obtain a set of exploration data attribute information. The set of exploration data attribute information includes the exploration type of geophysical exploration data, the exploration time of geophysical exploration data, the exploration depth of geophysical exploration data, and the measurement parameters of geophysical exploration data. The attribute features of each geographic element are extracted from the set of topological relationship descriptions of geographic elements to obtain a set of geographic element attribute features. The set of geographic element attribute features includes the material features, structural features, and spatial distribution features of geographic elements. Establish a mapping relationship between the attribute information of exploration data and the attribute characteristics of geographic elements, identify the core attribute items that can link geophysical exploration data and geographic elements, and obtain the core attribute mapping items; For each core attribute mapping item, analyze the value range of the core attribute mapping item in geophysical exploration data and geographic elements, calculate the overlap of value ranges, and obtain the attribute value overlap. Based on the overlap of the attribute values, an association weight is assigned to each core attribute mapping item to obtain the core attribute association weight table. Based on the core attribute association weight table, the association judgment conditions between geophysical exploration data and geographic elements are constructed. When the weighted consistency of geophysical exploration data and geographic elements on the core attribute mapping item reaches a preset threshold, it is determined that there is a spatial topological association between geophysical exploration data and geographic elements. For different types of topological relationships of geographic elements, corresponding association judgment conditions are constructed to obtain categorized association judgment conditions. The different types of topological relationships of geographic elements include connection relationships between geographic elements, inclusion relationships between geographic elements, and adjacency relationships between geographic elements. The categorized association judgment conditions and the core attribute association weight table are integrated to form spatial topology association rules, which include association attribute items, association weights and judgment thresholds. Collect all spatial topological association rules for different geographic element topological relationships and different geophysical exploration data types, and generate a spatial topological association rule set.

4. The geophysical exploration data management method combined with GIS according to claim 1, characterized in that, Based on the adjusted core attribute association weight table, the association strength parameters of each topological edge in the exploration data topology are recalculated to obtain the adjusted association strength parameters, including: For each core attribute mapping item, determine the value type of that core attribute mapping item; If the core attribute mapping item is a continuous value and the attribute value is represented as a numerical range, then the overlap of the values ​​of two topological nodes on the core attribute mapping item is calculated as the ratio of the size of the intersection range of the two value ranges to the size of the size of the union range of the two value ranges. If the core attribute mapping item is a continuous value and the attribute value is a single numerical value, then if two values ​​are equal, the value overlap is 1; otherwise, it is 0. If the core attribute mapping item is a discrete value and the attribute value is a discrete set of values, then the ratio of the size of the intersection to the size of the union of the two value sets is used as the value overlap. If the core attribute mapping item is a discrete value and the attribute value is a single discrete value, then if two values ​​are equal, the degree of overlap is 1; otherwise, it is 0. The weighted contribution value of each core attribute mapping item is obtained by multiplying the overlap of the values ​​of each core attribute mapping item by the association weight of that core attribute mapping item in the adjusted core attribute association weight table. The weighted contribution values ​​of all core attribute mapping items are summed to obtain the association strength parameter of the topological edge; Record the identifier of each topological edge and its corresponding adjusted association strength parameters to generate an adjusted topological edge strength table; Extract the maximum and minimum values ​​of the associated strength parameters from the adjusted topological edge strength table, and calculate the strength distribution interval; Based on the intensity distribution range, the associated intensity parameters are divided into different intensity level ranges to generate an intensity level classification standard; Based on the strength level classification standard, assign a corresponding strength level to each topological edge and add the strength level to the adjusted topological edge strength table; By integrating the adjusted topological edge strength table with the node connection information of each topological edge, the adjusted topological edge information is obtained. The adjusted associated strength parameters include specific values ​​and strength level labels.

5. The geophysical exploration data management method combined with GIS according to claim 1, characterized in that, Based on the adjusted exploration data topology, the spatialization of geophysical exploration data in GIS is realized, resulting in spatialized exploration data retrieval results, including: Receive exploration data retrieval requests from GIS, parse the spatial extent parameters and task requirement parameters in the exploration data retrieval requests, and obtain the retrieval spatial extent and retrieval task requirements. Based on the called spatial range, query the distribution of geographic elements in the GIS, extract the topological relationships of geographic elements within the called spatial range, and obtain the topology of geographic elements within the called range. Spatial matching is performed between the topology of the geographic features within the call range and the topology of the adjusted exploration data to determine the topological nodes within the call range in the adjusted exploration data topology, thereby obtaining a set of nodes within the call range. Extract the complete geophysical exploration data corresponding to each topological node in the node set within the scope of the call to obtain the exploration data set within the scope of the call; Based on the task request requirements, topological edge association information matching the task request requirements is extracted from the adjusted exploration data topology to obtain task association edge information; Based on the task association edge information, determine the geophysical exploration data groups with related relationships in the exploration data set within the scope of the call, and obtain the associated data groups; Each geophysical exploration data in the exploration data set within the scope of the call is spatially overlaid with the corresponding geographic elements in the GIS, so that the spatial location of the geophysical data corresponds precisely to the spatial location of the geographic elements, and a spatial overlay result is obtained. For the aforementioned associated data group, the spatial locations corresponding to the associated geophysical exploration data are connected by lines of different styles in the spatial overlay results. The line style is set to the style corresponding to the association strength level of the topological edge, and different association strength levels correspond to different line widths and line colors. Extract the geophysical exploration data attribute information from the spatial overlay result, generate attribute annotation boxes, and bind the attribute annotation boxes to the corresponding spatial locations of the geophysical exploration data to obtain an annotated spatial overlay result; Adjust the display scale parameter of the labeled spatial overlay results according to the display resolution of the GIS, and set the display scale parameter to a value that is compatible with the display resolution of the GIS; The labeled spatial overlay result after adjusting the display scale parameters is output to the GIS display interface, and a call result log is generated at the same time. The call result log includes the call time, call spatial range, number of called data and number of associated data groups. By integrating the output content of the display interface with the call result log, the spatialized call result of the exploration data is obtained.

6. The geophysical exploration data management method combined with GIS according to claim 5, characterized in that, The step involves spatially matching the topology of the geographic features within the call range with the adjusted exploration data topology to determine the topological nodes within the call range in the adjusted exploration data topology, thus obtaining a set of nodes within the call range, including: Parse the topology of the geographic features within the call range, extract the spatial coordinate range of all geographic features in the topology of the geographic features within the call range, and obtain the geographic coordinate set of the call range; Extract the spatial coordinate range of geophysical exploration data corresponding to each topological node in the adjusted exploration data topology to obtain the node spatial coordinate set; The spatial range of the node spatial coordinate set is compared with the geographical coordinate set of the calling range to determine whether the spatial coordinate range of each topology node is completely within the geographical coordinate set of the calling range. Record the topology nodes whose spatial coordinate range is entirely within the geographic coordinate set of the call range, and generate a complete list of nodes; Determine whether the spatial coordinate range of each topology node is partially within the geographical coordinate set of the calling scope. Partially within the geographical coordinate set of the calling scope means that the spatial coordinate range of the node and the geographical coordinate set of the calling scope have an intersection. Record the topological nodes whose spatial coordinate range is partially within the geographic coordinate set of the call range, and generate a partial list of nodes; The correlation between the geophysical exploration data corresponding to each topological node in the partially included node list and the call task requirements is analyzed. Attribute items related to the call task requirements are extracted to obtain the associated attributes of the partially included nodes. The matching degree between the associated attributes of the partially included nodes and the call task requirement parameters is calculated. The matching degree is the ratio of the number of overlapping related attribute items to the total number of call task requirement parameters. Record the nodes that meet the task matching threshold and generate a list of valid partially contained nodes. Integrate the fully contained node list with the valid partially contained node list, and remove duplicate topology node identifiers; Each integrated topology node is labeled with its spatial inclusion type, which is divided into complete inclusion and effective partial inclusion. A set of nodes within the call scope is generated, which includes node identifiers and spatial inclusion types.

7. A geophysical exploration data management system integrating GIS, characterized in that, include: processor; A machine-readable storage medium for storing machine-executable instructions of the processor; The processor is configured to execute the geophysical exploration data management method incorporating GIS as described in any one of claims 1 to 6 by executing the machine-executable instructions.

8. A computer program product, characterized in that, The computer program product includes machine-executable instructions stored in a computer-readable storage medium. A processor of a geophysical exploration data management system integrated with GIS reads the machine-executable instructions from the computer-readable storage medium and executes the machine-executable instructions, causing the geophysical exploration data management system integrated with GIS to perform the geophysical exploration data management method integrated with GIS as described in any one of claims 1 to 6.

Images