Three-dimensional stratum voxel assignment method based on interface constraint and inverse distance weighted interpolation and related equipment

Abstract

The application discloses a three-dimensional stratum voxel assignment method based on interface constraint and inverse distance weighted interpolation and related equipment, which can be applied to the technical field of three-dimensional modeling. The application obtains effective voxels by discretizing a three-dimensional space, and divides the to-be-processed drilling data of a target research area into a modeling hole set and a verification hole set after stratum mapping and elevation conversion. Then, according to the modeling hole set, the interface elevation in the voxel grid model is determined by combining an inverse distance weighted interpolation algorithm, each effective voxel in the voxel grid model is determined by combining a double-constraint anisotropic inverse distance weighted interpolation, and the effective voxels corresponding to bad geological bodies are removed. Then, after three-dimensional dimension comparison and evaluation of the effective voxels according to the verification hole set, an effective voxel file carrying a target stratum number is output, so that automatic assignment of high-precision three-dimensional voxels to multilayer geological structures can be completed, and assignment result evaluation can be effectively and accurately completed.

Description

Technical Field

[0001] This application relates to the field of 3D modeling technology, and in particular to a 3D stratigraphic voxel assignment method and related equipment based on interface constraints and inverse distance weighted interpolation. Background Technology

[0002] In related technologies, 3D stratigraphic modeling is a core foundational task for engineering geological exploration, underground space development, and geotechnical engineering design. It can intuitively display the spatial distribution characteristics of underground strata, providing accurate geological parameter inputs for engineering design, and is of great significance for improving engineering design quality and construction safety. In 3D stratigraphic modeling, voxel models are widely used for stratigraphic spatial representation due to their advantages such as regular structure, ease of calculation, and visualization. Voxel models discretize 3D space into regular cubic units, each of which is assigned corresponding stratigraphic attributes, thereby achieving a digital representation of underground geological structures. However, how to accurately assign stratigraphic attributes to each voxel based on limited borehole data—the voxel stratigraphic assignment problem—has always been a key technical challenge in 3D stratigraphic modeling.

[0003] Currently, methods for assigning voxel values ​​to 3D stratigraphic bodies mainly include stratigraphic modeling methods based on Kriging interpolation, stratigraphic modeling methods based on inverse distance weighted (IDW) interpolation, bottom layer modeling methods based on multi-point statistics (MPS), and methods for modeling adverse geological bodies. These methods suffer from several drawbacks: a lack of interface constraint mechanisms may lead to poor rationality of the 3D voxel models; failure to consider the anisotropic characteristics of the stratigraphy may result in decreased accuracy in some areas; and insufficient ability to handle adverse geological conditions may prevent the 3D stratigraphic models from accurately reflecting the impact of adverse geological conditions on the surrounding strata. Furthermore, existing methods typically lack quantitative accuracy verification after stratigraphic assignment, making it difficult to assess the reliability and accuracy of the assignment results.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a three-dimensional stratigraphic voxel assignment method and related equipment based on interface constraints and inverse distance weighted interpolation, which can automatically assign high-precision three-dimensional voxels of multi-layered geological structures and effectively and accurately complete the evaluation process of the assignment results.

[0006] To achieve the above objectives, one aspect of this application proposes a three-dimensional formation voxel assignment method based on interface constraints and inverse distance weighted interpolation, the method comprising the following steps: The three-dimensional space of the target study area is discretized to obtain a voxel mesh model, which includes effective voxels below the ground surface and ineffective voxels above the ground surface. Acquire the borehole data to be processed in the target study area; After mapping the original formation numbers in the borehole data to be processed and performing elevation conversion on the depth values ​​in the borehole data to be processed based on the effective voxels in the voxel mesh model, the borehole data to be processed is divided into a modeling borehole set and a verification borehole set. Based on the set of modeling holes, the interface elevation in the voxel mesh model is determined by combining the inverse distance weighted interpolation algorithm, and all the effective voxels are divided into upper and lower regions based on the interface elevation. Based on the upper region and the lower region, the target stratum number of each effective voxel in the voxel grid model is determined by inverse distance weighted interpolation with dual constraint anisotropy. An elliptic model is constructed based on the adverse geological record information in the modeling borehole set, and the effective voxels corresponding to the elliptic model are removed. After performing a three-dimensional comparative evaluation of the effective voxels after the removal operation based on the verification well set, an effective voxel file carrying the target formation number is output.

[0007] In some embodiments, the step of mapping the original formation numbers in the borehole data to be processed includes: A stratigraphic mapping table is constructed based on the engineering geological conditions of the target study area; The original stratigraphic numbers in the borehole data to be processed are mapped according to the stratigraphic mapping table; wherein, the original stratigraphic numbers after stratigraphic mapping include the upper stratigraphic number, the lower stratigraphic number, and the number of unfavorable geological bodies.

[0008] In some embodiments, determining the interface elevation in the voxel mesh model based on the set of modeling holes, combined with an inverse distance weighted interpolation algorithm, includes: Calculate the Euclidean distance from the planar position of each effective voxel in the voxel mesh model to the corresponding borehole planar position in the modeling hole set; Calculate the first weight corresponding to each borehole based on the Euclidean distance; Based on the depth of the upper stratum bottom of each borehole in the modeling borehole set and the first weight, calculate the inverse distance weighted interpolation corresponding to the planar position of each effective voxel; The interface elevation at the planar position corresponding to the effective voxel is calculated based on the surface elevation value obtained by the inverse distance weighted interpolation and difference estimation.

[0009] In some embodiments, the inverse distance weighted interpolation is calculated using the following formula: ; In the formula, This represents the inverse distance weighted interpolation value corresponding to the k-th borehole in the modeling borehole set; K represents the total number of boreholes in the modeling borehole set; This represents the depth of the bottom of the upper stratum corresponding to the k-th borehole in the modeling borehole set; This represents the first weight corresponding to the k-th borehole in the modeling borehole set; The formula for calculating the first weight is as follows: ; In the formula, This represents the Euclidean distance from the planar position of the kth effective voxel to the planar position of the kth borehole in the modeling hole set; This represents a very small constant used to prevent division by zero.

[0010] In some embodiments, determining the target formation number of each effective voxel in the voxel grid model based on the upper region and the lower region, combined with inverse distance weighted interpolation under dual-constraint anisotropy, includes: Based on the center coordinates of each effective voxel, several adjacent modeling holes that meet the preset requirements are found from the modeling hole set using a KD tree as the holes to be processed. When the effective voxel corresponding to the borehole to be processed is located in the upper region, the stratum number of the borehole to be processed at the center elevation of the effective voxel is modified to the upper stratum number as the corrected stratum number. When the borehole to be processed corresponds to the effective voxel located in the lower region and the borehole to be processed returns to the upper stratum number at the center elevation of the effective voxel, the stratigraphic sequence of the borehole to be processed is searched downwards and back to the nearest lower stratum number as the corrected stratigraphic number. Calculate the anisotropic normalized distance for each of the boreholes to be processed; Calculate the second weight corresponding to each borehole to be processed based on the anisotropic normalized distance; The target stratigraphic number of the effective voxel is determined based on the corrected stratigraphic number and the second weight.

[0011] In some embodiments, the formula for calculating the anisotropic normalized distance is as follows: ; In the formula, Represents the anisotropic normalized distance; This indicates the horizontal distance between the effective voxel and the borehole to be treated; This represents the vertical distance between the center elevation of the effective voxel and the absolute elevation of the borehole to be treated. Indicates the radius of influence of the horizontal search; This indicates the radius of influence of the vertical search.

[0012] In some embodiments, the three-dimensional comparative evaluation of the effective voxels after the rejection operation based on the set of verification wells includes: Based on the set of verification wells, the effective voxels after the removal operation are subjected to interface depth error calculation, formation hit rate calculation, and dual constraint effectiveness verification.

[0013] To achieve the above objectives, another aspect of this application proposes a three-dimensional formation voxel assignment device based on interface constraints and inverse distance weighted interpolation, the device comprising: The first module is used to discretize the three-dimensional space of the target study area to obtain a voxel mesh model, which includes effective voxels below the ground surface and ineffective voxels above the ground surface. The second module is used to acquire borehole data to be processed in the target study area; The third module is used to perform formation mapping on the original formation numbers in the borehole data to be processed and to perform elevation conversion on the depth values ​​in the borehole data to be processed based on the effective voxels in the voxel grid model. After that, the borehole data to be processed is divided into a set of modeling holes and a set of verification holes. The fourth module is used to determine the interface elevation in the voxel mesh model based on the set of modeling holes and the inverse distance weighted interpolation algorithm, and to divide all the effective voxels into upper and lower regions based on the interface elevation. The fifth module is used to determine the target stratum number of each effective voxel in the voxel grid model based on the upper region and the lower region, combined with inverse distance weighted interpolation of dual-constrained anisotropy. The sixth module is used to construct an elliptic model based on the adverse geological record information in the set of modeling holes, and to remove the effective voxels corresponding to the elliptic model. The seventh module is used to perform a three-dimensional comparative evaluation of the effective voxels after the rejection operation based on the set of verification wells, and then output an effective voxel file carrying the target formation number.

[0014] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0016] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0017] The embodiments of this application include at least the following beneficial effects: This application provides a three-dimensional formation voxel assignment method and related equipment based on interface constraints and inverse distance weighted interpolation. This scheme obtains effective voxels in a voxel mesh model by discretizing the three-dimensional space of the target study area. Simultaneously, it maps the original formation numbers in the borehole data to be processed in the target study area to formation, and performs elevation conversion on the depth values ​​in the borehole data based on the effective voxels in the voxel mesh model. The borehole data is then divided into a modeling borehole set and a verification borehole set. Then, based on the modeling borehole set and combined with the inverse distance weighted interpolation algorithm, the interface height in the voxel mesh model is determined. The process involves dividing all effective voxels into upper and lower regions based on the interface elevation. Then, based on the upper and lower regions, and combined with inverse distance weighted interpolation for dual-constraint anisotropy, the target stratum number of each effective voxel in the voxel grid model is determined. An elliptic model is constructed based on the adverse geological record information in the modeling well set, and effective voxels corresponding to the elliptic model are removed. Then, based on the verification well set, a three-dimensional comparative evaluation of the removed effective voxels is performed, and an effective voxel file carrying the target stratum number is output. This allows for the automatic assignment of high-precision three-dimensional voxels for multi-layered geological structures and the effective and accurate evaluation of the assignment results. Attached Figure Description

[0018] Figure 1 This is a flowchart of a three-dimensional formation voxel assignment method based on interface constraints and inverse distance weighted interpolation provided in an embodiment of this application; Figure 2 This is an application flowchart of the three-dimensional stratigraphic voxel assignment method based on interface constraints and inverse distance weighted interpolation provided in the embodiments of this application; Figure 3 This is a schematic diagram of the interface interpolation principle provided in the embodiments of this application; Figure 4 This is a flowchart of the dual constraint logic judgment provided in the embodiments of this application; Figure 5 This is a diagram illustrating the effect of the anisotropic normalized distance metric provided in the embodiments of this application. Figure 6 This is a rendering of the isotropic Euclidean distance metric provided in the embodiments of this application; Figure 7 This is a schematic diagram of the modeling and removal of undesirable geological body ellipsoids provided in the embodiments of this application; Figure 8This is a schematic diagram of the structure of the three-dimensional formation voxel assignment device based on interface constraints and inverse distance weighted interpolation provided in the embodiments of this application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0020] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0021] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0023] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0024] A KD-tree (K-Dimensional Tree) is a binary tree data structure used for efficiently organizing and managing K-dimensional spatial data. It is widely used in scenarios such as nearest neighbor search and range queries. A KD-tree is an extension of a balanced binary tree, where each node represents a point in a K-dimensional space, and the space is recursively partitioned by a hyperplane.

[0025] In related technologies, current methods for assigning three-dimensional stratigraphic values ​​mainly include the following categories: The first category is stratigraphic modeling methods based on Kriging interpolation. Kriging is a classic method in geostatistics, describing spatial correlation through a variogram and achieving optimal linear estimation under unbiased conditions. However, when directly interpolating stratigraphic numbers in stratigraphic assignment, the interpolation results are prone to non-integer stratigraphic numbers because stratigraphic numbers are discrete categorical variables rather than continuous variables. This requires additional rounding and post-processing operations, and it is difficult to guarantee the spatial continuity and sequence rationality of the stratigraphy.

[0026] The second category is stratigraphic modeling methods based on inverse distance weighted (IDW) interpolation. Inverse distance weighted interpolation is a deterministic spatial interpolation method with a simple principle and high computational efficiency, making it widely used in geological modeling. Traditional IDW methods typically assign stratigraphic values ​​by directly weighting the stratigraphic numbers of the most recent boreholes. However, conventional IDW methods use isotropic distance metrics and do not consider the anisotropic characteristics of stratigraphic lines, which extend horizontally and change rapidly vertically, leading to erroneous assignments near stratigraphic interfaces. Furthermore, when critical stratigraphic interfaces exist, traditional IDW methods lack effective constraint mechanisms, easily resulting in overlapping and misalignment of upper and lower strata.

[0027] The third category is stratigraphic modeling methods based on multi-point statistics (MPS). MPS methods extract multi-point spatial patterns from training images, enabling the reproduction of complex geological structures. However, this method is highly dependent on the quality and representativeness of the training images and involves significant computational costs. In real-world engineering scenarios where borehole data is sparse, obtaining high-quality training images is difficult, limiting its practicality in the field of engineering geology.

[0028] The fourth category is modeling methods for adverse geological bodies. However, in actual engineering projects, adverse geological bodies such as karst caves, mined-out areas, and cavities often exist underground, and their spatial distribution has a significant impact on engineering safety. Most existing 3D stratigraphic modeling methods do not incorporate adverse geological bodies into the modeling process, or simply treat them as a stratigraphic type, failing to reasonably represent their 3D spatial morphology. Furthermore, cavities such as karst caves are usually distributed in an ellipsoidal shape, extending more horizontally than vertically, but currently there is a lack of a systematic method to integrate this geometric feature into the voxel assignment process.

[0029] However, existing methods for assigning voxels to three-dimensional formations have the following problems: (1) Lack of interface constraint mechanism. Existing interpolation methods such as IDW and Kriging usually directly interpolate or vote on stratigraphic numbers when assigning stratigraphic values, lacking explicit constraints on key stratigraphic boundaries. When there is a clear boundary between the upper strata (such as overburden, Quaternary loose strata) and the lower strata (such as bedrock, hard strata) in the stratigraphic structure, traditional methods are prone to stratigraphic interpenetration problems, such as the lower strata erroneously intruding into the upper region or the upper strata erroneously extending into the lower region, which seriously affects the geological rationality of the model.

[0030] (2) The anisotropic characteristics of the strata are not considered. The strata have significant anisotropic characteristics in space, with the horizontal extension range being much larger than the vertical variation scale. The traditional IDW method uses isotropic Euclidean distance as the basis for weight calculation, which fails to distinguish the difference between the horizontal and vertical influences, resulting in a decrease in the accuracy of the assignment in areas where the vertical strata change is drastic.

[0031] (3) Insufficient capacity to handle adverse geological bodies. Adverse geological bodies such as karst caves and mining subsidence areas are widely present in underground spaces, but existing stratigraphic modeling methods generally lack the ability to systematically model the three-dimensional spatial morphology of adverse geological bodies. Some methods only record adverse geological bodies as point data, failing to reasonably characterize their distribution range and geometric shape in three-dimensional space, resulting in the model being unable to accurately reflect the impact of adverse geological bodies on the surrounding strata.

[0032] (4) Lack of a systematic verification and evaluation system. After completing the formation assignment, the existing methods usually lack a quantitative accuracy verification step, making it difficult to evaluate the reliability and accuracy of the assignment results, which is not conducive to the engineering application of the model and the improvement and optimization of the method.

[0033] In view of this, this application provides a three-dimensional stratigraphic voxel assignment method and related equipment based on interface constraints and inverse distance weighted interpolation. This scheme achieves high-precision automatic three-dimensional voxel assignment for multi-layered geological structures by introducing a dual constraint mechanism of key stratigraphic interfaces, anisotropic distance weight design, ellipsoidal adverse geological body modeling and elimination technology. At the same time, it establishes a quantitative verification and evaluation system based on the leave-one-out method, thereby effectively and accurately completing the evaluation process of the assignment results.

[0034] The method for assigning three-dimensional stratigraphic voxels based on interface constraints and inverse distance weighted interpolation provided in this application relates to the field of three-dimensional modeling technology. This method can be applied to terminals, servers, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the method of this embodiment, but is not limited to the above forms.

[0035] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0036] The embodiments of this application will be described in detail below with reference to the accompanying drawings: Figure 1 This is an optional flowchart of a three-dimensional stratigraphic voxel assignment method based on interface constraints and inverse distance weighted interpolation provided in this application embodiment. Figure 1 The method may include, but is not limited to, steps S110 to S170: Step S110: Discretize the three-dimensional space of the target study area to obtain a voxel mesh model, wherein the voxel mesh model includes effective voxels below the ground surface and ineffective voxels above the ground surface; Step S120: Obtain the borehole data to be processed in the target study area; Step S130: Map the original formation numbers in the borehole data to be processed to the formation and perform elevation conversion on the depth values ​​in the borehole data to be processed according to the effective voxels in the voxel grid model. Then divide the borehole data to be processed into a set of modeling holes and a set of verification holes. Step S140: Based on the set of modeling holes, determine the interface elevation in the voxel mesh model using the inverse distance weighted interpolation algorithm, and divide all the effective voxels into upper and lower regions based on the interface elevation. Step S150: Based on the upper region and the lower region, determine the target stratum number of each effective voxel in the voxel grid model by combining the inverse distance weighted interpolation of the dual-constraint anisotropy; Step S160: Construct an elliptic model based on the adverse geological record information in the modeling borehole set, and remove the effective voxels corresponding to the elliptic model; Step S170: After performing a three-dimensional comparative evaluation of the effective voxels after the removal operation based on the verification well set, output the effective voxel file carrying the target formation number.

[0037] It is understandable that, such as Figure 2 As shown, the three-dimensional spatial information of the target study area in this embodiment can be input using a voxel mesh file (VTR). Specifically, this embodiment discretizes the three-dimensional space of the target study area into a regular straight-line voxel mesh model. Specifically, let... , , The three directions are respectively divided into , , The total number of voxels is 1. The center coordinates of each voxel unit are... The center coordinates can be obtained by the arithmetic mean of the coordinates of adjacent nodes. Simultaneously, surface attribute markers are established. For each voxel, if it is located below the ground surface, it is marked as 1, indicating that the voxel is a valid voxel; otherwise, it is marked as 0, indicating that the voxel is an invalid voxel and will not participate in subsequent assignment calculations.

[0038] It is understandable that, such as Figure 2 As shown, the borehole data to be processed in the target study area in this embodiment can be input via a borehole data file (CSV). After obtaining the borehole data to be processed, this embodiment constructs a stratigraphic mapping table based on the engineering geological conditions of the target study area, and then maps the original stratigraphic numbers in the borehole data to be processed according to the stratigraphic mapping table. Specifically, each record of the borehole data to be processed in this embodiment includes the borehole number and planar coordinates. Original stratigraphic number, top depth and bottom depth Since the original stratigraphic classification is usually quite detailed and contains multiple sublayers, it is necessary to merge the original stratigraphic numbers into a unified stratigraphic numbering system through a mapping table. Let the mapping function be... The unified stratigraphic numbering is as shown in Formula 1: Formula 1; Among them, multiple sub-layers of the upper strata are uniformly mapped to the upper strata number. Each stratigraphic level in the lower strata is mapped to a corresponding set of lower strata numbers. Unfavorable geological bodies (cavities) are mapped to unfavorable geological body numbers. .

[0039] Understandably, since the depth values ​​in the borehole data are relative to the borehole opening, they need to be converted to absolute elevation. First, determine the surface elevation at each borehole location: find the nearest voxel column to the borehole location in the voxel mesh model, and take the elevation from that voxel column. The highest voxel center elevation is used as the surface elevation of the orifice. The elevation transformation formula is shown in Formula 2: Formula 2; In the formula, Depth values ​​in conservative borehole records; This represents the corresponding absolute elevation value, which can be used as a known data point for interface interpolation.

[0040] In this embodiment, after mapping and elevation conversion, the borehole data to be processed is divided into a modeling borehole set and a verification borehole set. Verification boreholes should be selected from those located in the central part of the site and with relatively complete strata exposure, avoiding marginal boreholes or boreholes with severe strata gaps, to ensure the representativeness of the verification results.

[0041] It is understandable that, after obtaining the set of modeling holes, this embodiment uses an inverse distance weighted interpolation algorithm to determine the interface elevation in the voxel mesh model, and divides all effective voxels into upper and lower regions based on the interface elevation. Specifically, this embodiment can perform the following steps in determining the interface elevation: Calculate the Euclidean distance from the planar position of each effective voxel in the voxel mesh model to the corresponding borehole planar position in the modeling hole set; Calculate the first weight corresponding to each borehole based on the Euclidean distance; The inverse distance weighted interpolation corresponding to the planar position of each effective voxel is calculated based on the bottom depth of the upper stratum and the first weight of each borehole in the modeling borehole set; The interface elevation at the plane position of the corresponding effective voxel is calculated based on the surface elevation value obtained by inverse distance weighted interpolation and difference estimation.

[0042] This embodiment first extracts the bottom depth of the upper strata from the formation data of each modeling borehole. Then, the IDW method is used to interpolate the bottom depths of these discrete upper strata to the planar position of each effective voxel. Assume there are a total of... The modeling hole, the first The planar coordinates of the modeling holes are , No. The depth of the upper stratum bottom of each modeling hole is For planar position The effective voxel at the location, and the IDW interpolation formula at the lower boundary depth of the upper strata are shown in Formula 3: Formula 3; In the formula, This represents the inverse distance weighted interpolation value corresponding to the k-th borehole in the modeling borehole set; K represents the total number of boreholes in the modeling borehole set; This represents the depth of the bottom of the upper stratum corresponding to the k-th borehole in the modeling borehole set; This represents the first weight corresponding to the k-th borehole in the modeling borehole set; The formula for calculating the first weight is shown in Formula 4: Formula 4; In the formula, This represents the Euclidean distance from the planar position of the kth effective voxel to the planar position of the kth borehole in the modeling hole set; This represents the smallest constant used to prevent division by zero (taken as...). ).

[0043] Similarly, the surface elevation value obtained by IDW interpolation at the effective voxel plane position (x,y) corresponding to the k-th borehole using inverse distance weighted interpolation is: Therefore, the interface elevation at the planar position (x,y) of this effective voxel is... As shown in Formula 5: Formula 5; In this embodiment, the interface elevation is determined at the planar location of each effective voxel through the above interpolation. When the voxel center elevation At that time, the voxel is located in the upper region; when At that time, the voxel is located in the lower region. The principle by which the interface divides the three-dimensional space into upper and lower regions is as follows: Figure 3 As shown.

[0044] When there are multiple key interfaces (such as a partition structure with more than three layers), the stratigraphic assignment of multiple partitions can be achieved by interpolating multiple interfaces sequentially and setting multi-level constraints.

[0045] It is understood that, after completing the interface interpolation, this embodiment determines the target formation number of each effective voxel in the voxel grid model based on the upper and lower regions, combined with inverse distance weighted interpolation under dual-constraint anisotropy. The determination process in this embodiment can be achieved through the following steps: Based on the center coordinates of each effective voxel, several adjacent modeling holes that meet the preset requirements are found from the modeling hole set using the KD tree as the holes to be processed. When the effective voxel corresponding to the borehole to be processed is located in the upper region, the stratum number of the borehole to be processed at the center elevation of the effective voxel is modified to the upper stratum number as the corrected stratum number. When the effective voxel corresponding to the borehole to be processed is located in the lower region and the borehole to be processed returns to the upper stratum number at the center elevation of the effective voxel, the stratigraphic sequence of the borehole to be processed is searched downwards and back to the nearest lower stratum number as the corrected stratigraphic number. Calculate the anisotropic normalized distance for each borehole to be processed; The second weight corresponding to each borehole to be processed is calculated based on the anisotropic normalized distance. The target stratigraphic number of the effective voxels is determined based on the corrected stratigraphic number and the second weight.

[0046] Specifically, this embodiment introduces interface location constraints (first constraint) and stratigraphic type regression constraints (second constraint) on the basis of IDW weighted voting, and uses anisotropic distance metric instead of traditional isotropic Euclidean distance. For example... Figure 4 As shown, for each effective voxel First, use a KD-tree to find the nearest node in the plane. Each model hole is selected as a borehole to be processed. Then, the formation number corresponding to the center elevation of each borehole is queried, and the following double constraint logic is executed: First constraint: If the effective voxel is located in the upper region ( Regardless of the stratigraphic number returned by the borehole at the central elevation, the borehole number will be forcibly corrected to the upper stratigraphic number. As a revised stratigraphic designation, it ensures that the lower strata will not appear in the upper region.

[0047] Second constraint: If the effective voxel is located in the lower region ( However, the borehole to be processed returned to the upper strata number at that elevation. As the corrected stratigraphic number, the search proceeds downwards within the stratigraphic sequence of the borehole to be processed, back to the nearest lower stratigraphic number, to prevent the upper stratigraphic layers from encroaching on the lower region.

[0048] Then, the anisotropic normalized distance for each borehole to be processed is calculated. The formula for calculating the anisotropic normalized distance is shown in Formula 6: Formula 6; In the formula, Represents the anisotropic normalized distance; This indicates the horizontal distance between the effective voxel and the borehole to be treated; This represents the vertical distance between the center elevation of the effective voxel and the absolute elevation of the borehole to be treated. Indicates the radius of influence of the horizontal search; This indicates the radius of influence of the vertical search.

[0049] This embodiment uses a horizontal search to determine the radius of influence. Much larger than the vertical search influence radius The settings allow vertical distance to have a greater impact in the weighting calculation, which aligns with the geological characteristics of stratigraphic anisotropy. The effect of anisotropic distance measurement is as follows: Figure 5 The results shown are as follows, along with the effects of isotropic distance metrics. Figure 6 As shown.

[0050] Based on the anisotropic normalized distance calculated using Formula 6, the second weight corresponding to the i-th borehole to be processed can be calculated, as shown in Formula 7: Formula 7; In the formula, Indicates the distance power parameter; This represents a very small constant that prevents division by zero.

[0051] For each valid voxel, the formation numbers and their second weights of each neighboring borehole to be processed after constraint correction are collected, and the target formation number of the voxel is determined by the weighted voting method shown in Formula 8. : Formula 8; In the formula, Indicates an indicator function, This indicates the formation number of the i-th nearest neighbor borehole after double constraint correction.

[0052] It is understandable that undesirable geological formations such as karst caves and mined-out areas are widely present in actual geological bodies. This embodiment proposes using an ellipsoidal model to represent the three-dimensional spatial morphology of undesirable geological formations and removing them from the effective voxels.

[0053] For each segment of adverse geological body revealed by the borehole, the planar coordinates of that record are used. The horizontal projection of the ellipsoid center, with the midpoint of the top and bottom elevations. Construct a triaxial ellipsoid with the vertical position of the ellipsoid's center. The ellipsoid equation is shown in Equation 9: Formula 9; In the formula, This represents the horizontal radius of the ellipsoid. The length of the vertical semi-axis of the ellipsoid is expressed by formula 10: Formula 10; In the formula, Indicates the thickness of the adverse geological body revealed by the borehole. Indicates the vertical scaling factor. This represents the side length of the voxel. Formula 10 reflects the spatial morphological characteristic of adverse geological bodies where the horizontal extension is greater than the vertical extension.

[0054] For all effective voxels that satisfy Formula 9, the stratigraphic number of the effective voxel is marked as the number of the unfavorable geological body. At the same time, the effective voxels Setting the marker to 0 removes the effective voxel set, thus creating a cavity structure in the 3D model formed by the effective voxels. The principle of modeling and removing adverse geological body ellipsoids is as follows: Figure 7 As shown.

[0055] In this embodiment, after removing unfavorable geological bodies, the effective voxels after the removal operation are evaluated based on the reserved set of verification wells, including interface depth error calculation, formation hit rate calculation, and dual-constraint effectiveness verification. This embodiment uses a leave-one-out quantitative verification and evaluation system, comparing the model-predicted stratigraphic sequence at the reserved verification well locations with the measured stratigraphic sequence in three dimensions. Interface depth error: The absolute value of the difference between the predicted elevation and the measured elevation of the top interface of each stratum is compared, and the error is rated into three levels: excellent (<5m), good (<10m), and poor (≥10m). Stratigraphic accuracy: At the top elevation of each measured stratum, compare whether the stratigraphic type predicted by the model is consistent with the measured stratigraphic type, and calculate the overall accuracy. Verification of the effectiveness of the dual constraint mechanism: Statistical analysis was conducted to determine whether lower strata appeared above the boundary and whether upper strata appeared below the boundary, thus verifying the effectiveness of the dual constraint mechanism.

[0056] Specifically, when stratigraphic intersections appear in the verification results, the first step should be to check whether the interface interpolation results are reasonable. This can be addressed by adjusting the number of adjacent boreholes in the interface interpolation. Optimization can be performed. When the interface depth error of the verification hole is too large, the vertical search radius can be appropriately reduced. To enhance vertical resolution.

[0057] In some embodiments, the voxel mesh model file (VTR format) of this embodiment defines the three-dimensional spatial extent and discretization precision of the modeling region, including... , , The node coordinates and surface marker attributes are provided in three directions. The selection of voxel edge length should comprehensively consider both borehole spacing and formation variation scale: when the borehole spacing is small and formation variations are drastic, a smaller voxel edge length (e.g., 1m-3m) is preferable to improve resolution; when the borehole spacing is large, a larger voxel edge length (e.g., 5m-10m) can be used to control computational load. This embodiment uses a borehole stratification data file (CSV format). Each record should include the borehole number and borehole planar coordinates. The system requires five essential fields: stratigraphic number, top stratigraphic depth, and bottom stratigraphic depth. Before use, a stratigraphic mapping table must be established based on engineering geological conditions, merging the original substrata into a unified numbering system. The mapping table can be shown in Table 1. Table 1

[0058] The key parameters involved in this embodiment and their selection recommendations are shown in Table 2: Table 2

[0059] Among them, the horizontal search influence radius Radius of influence of vertical search The ratio of vertical distance to weight is a core parameter controlling the degree of anisotropy. The larger this ratio, the more significant the influence of vertical distance on the weight. For horizontally extending strata such as sedimentary strata, A value of 30-80 is recommended; for near-horizontal layered rock masses, a value of 15-30 is recommended. (Horizontal radius of the ellipsoid) The selection of the borehole spacing should be based on engineering experience and the development scale of the adverse geological body. When prior information is lacking, 1 / 5 to 1 / 3 of the borehole spacing can be taken as the initial value.

[0060] As can be seen from the above, this embodiment divides the three-dimensional voxel space into an upper and lower region by interpolating the key stratigraphic interface (first constraint), and performs stratigraphic type regression correction within the partition (second constraint), fundamentally eliminating the problem of stratigraphic interleaving disorder in traditional interpolation methods and ensuring the geological rationality of the assignment results; by using the anisotropic normalized distance metric method, the horizontal search radius is used in the IDW weight calculation. and vertical search radius The horizontal distance and vertical distance are normalized, so that the weight distribution conforms to the anisotropic geological law that strata extend far in the horizontal direction and change rapidly in the vertical direction, which improves the assignment accuracy near the stratum interface; the ellipsoid shape is controlled by the horizontal radius and the vertical scaling coefficient to reasonably characterize the three-dimensional spatial distribution of unfavorable geologic bodies such as karst caves and goafs, and they are removed from the effective voxels, so as to realize the linked processing of the stratum model and the unfavorable geologic bodies; and by organically integrating the IDW interpolation of key interfaces, the dual-constraint zonal assignment, the anisotropic distance weight calculation and the ellipsoid unfavorable geologic body removal into a complete automated voxel assignment process, the whole-chain processing from borehole data input to 3D stratum voxel model output is realized, with all links cooperating with each other — the interface interpolation results directly serve the zonal judgment of dual constraints, the anisotropic weights ensure the geological rationality of the assignment within each zone, and the ellipsoid removal further corrects the unfavorable geologic body regions after the assignment is completed; finally, through the quantitative verification and evaluation method for 3D stratum assignment based on the leave-one-out method, the assignment accuracy is systematically evaluated from three dimensions of interface depth error, stratum hit rate and dual constraint effectiveness, forming a closed-loop technical system integrating modeling and verification.

[0061] Reference is made to Figure 8 , and the embodiments of the present application further provide a 3D stratum voxel assignment device based on interface constraints and inverse distance weighted interpolation, the device comprising: a first module, configured to perform discretization processing on the three-dimensional space of the target research area to obtain a voxel grid model, wherein the voxel grid model includes effective voxels below the ground surface and invalid voxels above the ground surface; a second module, configured to obtain to-be-processed borehole data of the target research area; a third module, configured to perform stratum mapping on original stratum numbers in the to-be-processed borehole data, perform elevation conversion on depth values in the to-be-processed borehole data according to the effective voxels in the voxel grid model, and then divide the to-be-processed borehole data into a modeling borehole set and a verification borehole set; a fourth module, configured to determine the interface elevation in the voxel grid model in combination with an inverse distance weighted interpolation algorithm according to the modeling borehole set, and divide all the effective voxels into an upper region and a lower region according to the interface elevation; a fifth module, configured to determine the target stratum number of each of the effective voxels in the voxel grid model in combination with dual-constraint anisotropic inverse distance weighted interpolation according to the upper region and the lower region; a sixth module, configured to construct an ellipsoid model according to unfavorable geological record information in the modeling borehole set, and remove the effective voxels corresponding to the ellipsoid model; a seventh module, configured to perform three-dimension comparative evaluation on the effective voxels after the removal operation according to the verification borehole set, and then output an effective voxel file carrying the target stratum numbers.

[0062] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0063] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0064] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0065] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0066] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0067] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0068] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0069] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0070] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0071] This application provides a three-dimensional formation voxel assignment method and related equipment based on interface constraints and inverse distance weighted interpolation, which has the following beneficial effects: First, compared with the traditional IDW method, this embodiment introduces a dual constraint mechanism, effectively solving the problem of stratigraphic interleaving. The traditional IDW method directly performs weighted voting on stratigraphic numbers, which can easily lead to unreasonable results of upper and lower stratigraphic layers interleaving when borehole data is sparse or stratigraphic interfaces are highly undulating. This invention, through a strategy of first interpolating the interface and then assigning zone constraints, ensures the rationality of the stratigraphic sequence at the algorithmic level. Experimental results show that the dual constraint is completely effective, with no stratigraphic intersections on either side of the interface.

[0072] Secondly, compared with isotropic interpolation methods, the anisotropic weight design in this embodiment is more consistent with geological laws. Traditional methods treat the horizontal and vertical directions equally in distance calculation, failing to reflect the distinctly different variation characteristics of strata in these two directions. This embodiment introduces normalization of the horizontal and vertical search radii separately, significantly increasing the influence of vertical distance in the weighting and noticeably improving the accuracy of assignment near stratigraphic interfaces.

[0073] Third, compared with existing stratigraphic modeling methods, this embodiment is the first to deeply integrate ellipsoidal modeling of adverse geological bodies with voxel assignment. Existing methods usually treat adverse geological bodies only as point records or ordinary strata. This embodiment expands the limited information revealed by boreholes into a three-dimensional spatial morphology through the ellipsoid equation, so that the spatial influence range of adverse geological bodies can be reasonably represented. At the same time, the cavity structure is realistically reflected in the model through voxel culling operations.

[0074] Fourth, compared with Kriging and multipoint statistical methods, this embodiment has higher computational efficiency, fewer parameters, and stronger engineering applicability. Kriging requires constructing a variogram and solving a system of linear equations, while multipoint statistical methods require training images and substantial computational resources. This embodiment only requires setting a few intuitive physical parameters (search radius, distance power, ellipsoid size, etc.), and the calculation process is simple and efficient, making it suitable for practical engineering applications.

[0075] Fifth, this embodiment establishes a complete leave-one-out method verification and evaluation system, which quantitatively evaluates the accuracy of the assigned values ​​from three dimensions: interface depth error, formation hit rate, and effectiveness of dual constraints. This provides a basis for optimizing and adjusting method parameters and making decisions for engineering applications, and makes up for the lack of systematic verification in existing methods.

[0076] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0077] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0078] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0079] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0080] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0082] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0084] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0085] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for assigning three-dimensional stratigraphic voxels based on interface constraints and inverse distance weighted interpolation, characterized in that, The method includes the following steps: The three-dimensional space of the target study area is discretized to obtain a voxel mesh model, which includes effective voxels below the ground surface and ineffective voxels above the ground surface. Acquire the borehole data to be processed in the target study area; After mapping the original formation numbers in the borehole data to be processed and performing elevation conversion on the depth values ​​in the borehole data to be processed based on the effective voxels in the voxel mesh model, the borehole data to be processed is divided into a modeling borehole set and a verification borehole set. Based on the set of modeling holes, the interface elevation in the voxel mesh model is determined by combining the inverse distance weighted interpolation algorithm, and all the effective voxels are divided into upper and lower regions based on the interface elevation. Based on the upper region and the lower region, the target stratum number of each effective voxel in the voxel grid model is determined by inverse distance weighted interpolation with dual constraint anisotropy. An elliptic model is constructed based on the adverse geological record information in the modeling borehole set, and the effective voxels corresponding to the elliptic model are removed. After performing a three-dimensional comparative evaluation of the effective voxels after the removal operation based on the verification well set, an effective voxel file carrying the target formation number is output.

2. The method according to claim 1, characterized in that, The process of mapping the original formation numbers in the borehole data to be processed includes: A stratigraphic mapping table is constructed based on the engineering geological conditions of the target study area; The original stratigraphic numbers in the borehole data to be processed are mapped according to the stratigraphic mapping table; wherein, the original stratigraphic numbers after stratigraphic mapping include the upper stratigraphic number, the lower stratigraphic number, and the number of unfavorable geological bodies.

3. The method according to claim 1, characterized in that, The step of determining the interface elevation in the voxel mesh model based on the set of modeling holes and using an inverse distance weighted interpolation algorithm includes: Calculate the Euclidean distance from the planar position of each effective voxel in the voxel mesh model to the corresponding borehole planar position in the modeling hole set; Calculate the first weight corresponding to each borehole based on the Euclidean distance; Based on the depth of the upper stratum bottom of each borehole in the modeling borehole set and the first weight, calculate the inverse distance weighted interpolation corresponding to the planar position of each effective voxel; The interface elevation at the planar position corresponding to the effective voxel is calculated based on the surface elevation value obtained by the inverse distance weighted interpolation and difference estimation.

4. The method according to claim 3, characterized in that, The formula for calculating the inverse distance weighted interpolation is as follows: ； In the formula, This represents the inverse distance weighted interpolation value corresponding to the k-th borehole in the modeling borehole set; K represents the total number of boreholes in the modeling borehole set; This represents the depth of the bottom of the upper stratum corresponding to the k-th borehole in the modeling borehole set; This represents the first weight corresponding to the k-th borehole in the modeling borehole set; The formula for calculating the first weight is as follows: ； In the formula, This represents the Euclidean distance from the planar position of the kth effective voxel to the planar position of the kth borehole in the modeling hole set; This represents a very small constant used to prevent division by zero.

5. The method according to claim 1, characterized in that, The step of determining the target formation number of each effective voxel in the voxel grid model based on the upper region and the lower region, combined with inverse distance weighted interpolation under dual-constraint anisotropy, includes: Based on the center coordinates of each effective voxel, several adjacent modeling holes that meet the preset requirements are searched from the modeling hole set using a KD tree as the holes to be processed. When the effective voxel corresponding to the borehole to be processed is located in the upper region, the stratum number of the borehole to be processed at the center elevation of the effective voxel is modified to the upper stratum number as the corrected stratum number. When the borehole to be processed corresponds to the effective voxel located in the lower region and the borehole to be processed returns to the upper stratum number at the center elevation of the effective voxel, the stratigraphic sequence of the borehole to be processed is searched downwards and back to the nearest lower stratum number as the corrected stratigraphic number. Calculate the anisotropic normalized distance for each of the boreholes to be processed; Calculate the second weight corresponding to each borehole to be processed based on the anisotropic normalized distance; The target stratigraphic number of the effective voxel is determined based on the corrected stratigraphic number and the second weight.

6. The method according to claim 5, characterized in that, The formula for calculating the anisotropic normalized distance is as follows: ； In the formula, Represents the anisotropic normalized distance; This indicates the horizontal distance between the effective voxel and the borehole to be treated; This represents the vertical distance between the center elevation of the effective voxel and the absolute elevation of the borehole to be treated. Indicates the radius of influence of the horizontal search; This indicates the radius of influence of the vertical search.

7. The method according to claim 1, characterized in that, The three-dimensional comparative evaluation of the effective voxels after the rejection operation based on the set of verification holes includes: Based on the set of verification wells, the effective voxels after the removal operation are subjected to interface depth error calculation, formation hit rate calculation, and dual constraint effectiveness verification.

8. A three-dimensional formation voxel assignment device based on interface constraints and inverse distance weighted interpolation, characterized in that, The device includes: The first module is used to discretize the three-dimensional space of the target study area to obtain a voxel mesh model, which includes effective voxels below the ground surface and ineffective voxels above the ground surface. The second module is used to acquire borehole data to be processed in the target study area; The third module is used to perform formation mapping on the original formation numbers in the borehole data to be processed and to perform elevation conversion on the depth values ​​in the borehole data to be processed based on the effective voxels in the voxel grid model. After that, the borehole data to be processed is divided into a set of modeling boreholes and a set of verification boreholes. The fourth module is used to determine the interface elevation in the voxel mesh model based on the set of modeling holes and the inverse distance weighted interpolation algorithm, and to divide all the effective voxels into upper and lower regions based on the interface elevation. The fifth module is used to determine the target stratum number of each effective voxel in the voxel grid model based on the upper region and the lower region, combined with inverse distance weighted interpolation of dual-constrained anisotropy. The sixth module is used to construct an elliptic model based on the adverse geological record information in the set of modeling holes, and to remove the effective voxels corresponding to the elliptic model. The seventh module is used to perform a three-dimensional comparative evaluation of the effective voxels after the rejection operation based on the set of verification wells, and then output an effective voxel file carrying the target formation number.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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