Microfracture-containing digital core unsupported optimization reconstruction and 3D printing method and system

Abstract

The present application belongs to the technical field of oil and gas field development engineering, and discloses a method and system for support-free optimization reconstruction and 3D printing of a digital core containing micro-fractures. The method comprises the following steps: data preprocessing, layer-by-layer connected region determination, support-free dynamic optimization reconstruction, comparison and analysis of parameters of the digital core containing micro-fractures before and after processing, and 3D printing verification and manufacturing of an STL model of the digital core containing micro-fractures. The present application realizes support-free optimization reconstruction and entity manufacturing of a complex core model, reduces the demand for internal support of the model, reduces the interference of internal support residues on pore structure and fluid flow path, and provides a high-precision and repeatable entity model for microcosmic percolation experimental research.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field development engineering technology, and in particular relates to a method and system for unsupported optimization reconstruction and 3D printing of digital cores containing microfractures. Background Technology

[0002] In oil and gas field development, the microscopic pore structure of reservoir rocks has a significant impact on fluid storage, migration, and displacement processes. For tight sandstone, shale, carbonate rocks, and fractured reservoirs, the core often contains pores, pore throats, microfractures, and heterogeneous matrix structures of varying scales. These microstructures collectively determine the reservoir space morphology and fluid flow paths. Therefore, accurately obtaining and replicating the complex internal structure of microfractured cores is of great significance for studying reservoir micro-flow patterns, evaluating reservoir development effectiveness, and optimizing oil and gas field development strategies.

[0003] With the development of CT scanning, digital core modeling, and 3D printing technologies, replicating the internal pore structure of real rock cores using digital core models has become an important experimental research method. Existing digital core reconstruction methods include image texture synthesis-based reconstruction methods, training image and data template-based reconstruction methods, randomly grown digital core reconstruction methods, 3D digital core reconstruction methods based on generative adversarial networks or VQGANs, and digital core mesh mapping methods for finite element simulation. These methods primarily focus on the generation of digital core models, image reconstruction efficiency, image clarity, statistical distribution consistency, or numerical simulation accuracy, while rarely addressing the targeted optimization of internal suspended structures, residual internal supports, and fidelity of microcrack boundaries in reconstructed or segmented digital core models containing microcracks during the 3D printing process.

[0004] However, existing digital core 3D printing manufacturing technologies still have significant shortcomings when processing digital core models containing microcracks, mainly in the following aspects: Digital cores containing microfractures have complex structures, and some rock matrix areas lack underlying solid support in the printing direction, easily forming suspended matrix structures. Real cores typically contain numerous pores and fine spatial structures; the lack of underlying solid support in some rock matrix areas during printing easily leads to suspended structures during layer-by-layer printing. When the number of suspended structures is large or their distribution is complex, problems such as local collapse, structural deformation, and printing failure may occur during the printing process. For digital core models containing microfractures, the microfracture regions are often distributed in elongated, sheet-like, linear, or network-like shapes, and their adjacent rock matrix boundaries are even more complex, further increasing the difficulty of printing the model without support.

[0005] Traditional internal support methods are unsuitable for complex digital core structures. Conventional 3D printing typically addresses the issue of suspended forming by adding support structures, but the pores, throats, and microcracks within digital cores are small and complexly distributed, making it difficult to completely remove the internal support material after printing. Residual support material may occupy pore spaces or block local flow paths, thereby altering the original pore structure characteristics of the digital core and affecting the accuracy of subsequent experimental results.

[0006] Manual restoration methods are inefficient and inconsistent. For high-resolution digital core data, the original three-dimensional array usually contains a large number of voxel data. Manually checking and deleting suspended structures layer by layer is a huge workload, inefficient, and easily affected by the operator's experience, resulting in inconsistent processing results for different batches of models, ultimately affecting the model's ability to represent the original core structure.

[0007] Balancing printability and structural fidelity is challenging. If the original digital core structure is fully preserved, the model may contain numerous unstable, unprintable matrix regions. Conversely, excessive smoothing, filling, or modification of the model can significantly alter the original morphology of pore spaces and microcrack regions. Therefore, a method for optimizing and reconstructing digital cores for unsupported printing is needed, capable of automatically identifying unprintable structures and minimizing the impact on microcrack regions and their adjacent matrix boundaries. Summary of the Invention

[0008] To overcome the problems existing in related technologies, this invention provides a method and system for unsupported optimization and reconstruction of digital cores containing microfractures and for 3D printing. This addresses the issues of numerous suspended structures, difficulty in removing internal supports, low efficiency of manual processing, and the difficulty in balancing structural fidelity and printability in existing digital core models containing microfractures during 3D printing. The main purpose of this invention is to optimize and reconstruct the structure of digital core models containing microfractures for 3D printing, particularly suitable for preparing digital core models with complex pores, pore throats, microfractures, and heterogeneous rock matrix structures. This provides a solid model basis for reservoir microstructure characterization, physical simulation experiments, and micro-seepage experimental research.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: a method for unsupported optimization reconstruction and 3D printing of digital rock cores containing microcracks, comprising the following steps: S1. Read the digital core data containing microcracks that has been identified and segmented into three phases. The three phases include the ordinary pore region, the microcrack region, and the rock matrix region, and are represented by gray values ​​or label values ​​of 0, 1, and 2, respectively. Reshape the binary data into a three-dimensional array of a set size. S2. According to the set printing direction, process the three-dimensional array layer by layer starting from the first layer. Use the neighborhood algorithm to perform connected domain analysis on the rock matrix region of each layer to obtain the number of connected regions, labels and region coordinate range of the current layer of rock matrix. Establish the microcrack structure protection area according to the spatial distribution of the microcrack region. S3. Extract the coordinate range of the connected regions of the current layer rock matrix, and count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or digital core models containing microcracks. S4. Calculate the topological parameters of the digital core model with microcracks before and after optimization. The topological parameters include pore porosity, pore radius, pore shape factor, throat radius and coordination number to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. S5. Output the digital core model with microcracks before and after optimization as an STL file and import it into the slicing software. Use the suspended structure prompts of the slicing software to verify the internal support requirements, and perform 3D printing and post-processing on the optimized model.

[0010] In step S1, the bit depth setting of the digital core data containing microcracks includes 8-bit or 16-bit. The dimension of the three-dimensional array of the set size is determined according to the CT scan parameters, core sampling size and target printing accuracy, including voxel dimensions of 300×300×3000 or 450×450×1000. The three-dimensional array is used to perform layer-by-layer connected domain analysis, entity pixel overlap determination, microcrack structure protection area marking and mask updating in the same spatial coordinate system.

[0011] Furthermore, the three-phase identification and segmentation is completed by pre-image processing software, manual calibration method or digital core processing software. It receives and processes digital core data containing microcracks that has been marked with three phases, wherein the gray value or label value of the ordinary pore area is 0, the gray value or label value of the microcrack area is 1, and the gray value or label value of the rock matrix area is 2. The microfractured region is a spatial region in digital core data containing microfractures that has been marked as a microfractured phase. The microfractured region is in the form of a slender, sheet-like, linear, network-like, or irregularly extended shape. The ordinary pore region is a spatial region in digital core data containing microfractures that has been marked as an ordinary pore phase. The rock matrix region is a region in digital core data containing microfractures that has been marked as a solid phase.

[0012] In step S2, the neighborhood algorithm adopts the four-neighborhood algorithm and the eight-neighborhood algorithm; the neighborhood algorithm is used to merge adjacent rock matrix pixels in each layer into the same rock matrix connected region, so that the subsequent entity pixel overlap determination takes the connected region as the object; The microcrack protection area is obtained by expanding the neighborhood of the microcrack area or by marking the rock matrix area adjacent to the microcrack boundary; the microcrack structure protection area is used to limit the range of suspended matrix area removal during subsequent optimization and reconstruction.

[0013] In step S3, marking connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions includes: performing connected component labeling on the current layer of rock matrix region to obtain a label matrix. and tag collection Statistical label set Number of China-Africa background tags ;like If the current layer has only one continuous connected rock matrix region, the current layer data is saved and the overlapping of entity pixels in the current layer is skipped and the region is determined one by one; if Then, the number of overlapping entity pixels is counted for each connected region of the rock matrix.

[0014] Furthermore, the pixel overlap number is the number of pixel overlaps between the current layer rock matrix connected region and the previous layer rock matrix connected region at the same coordinate region position; when the overlap number of a certain rock matrix connected region at the corresponding position in the previous layer is less than a preset threshold, the connected region is initially marked as an isolated suspended matrix region; the entity pixel overlap determination is based on the support relationship of adjacent layers in the printing direction, distinguishing between the spatial region in the real pore structure and the suspended matrix region that lacks the support of the lower layer entity during the printing process; For the initially marked isolated suspended matrix region, determine whether it intersects with the microcrack structure protection region; if the isolated suspended matrix region intersects with the microcrack structure protection region, the region is retained; if the isolated suspended matrix region does not intersect with the microcrack structure protection region, it is regarded as a suspended matrix region to be removed, and the data attributes of the corresponding region are modified from rock matrix region to ordinary pore region through masking.

[0015] In step S4, the porosity is the ratio of the sum of the number of pixels in the ordinary pore region and the microcrack region of the current layer to the total number of pixels in the current layer; the pore radius and throat radius are calculated based on the equivalent circle radius of the pore or throat cross-sectional area; the pore shape factor is calculated based on the pore volume and surface area; the coordination number is calculated based on the number of throats connected to a single pore; the topology parameters are used to evaluate the degree of structural preservation of the pore space and microcrack space before and after optimization and reconstruction, and serve as a criterion for whether the optimization without internal support excessively alters the original digital core structure.

[0016] In step S5, the material used for 3D printing is transparent resin, and the printing layer thickness is 25μm. When slicing, no internal support structure is generated for the digital core model containing microcracks. External support or base support is set according to the external fixation and molding of the digital core model containing microcracks. After printing, the digital core model containing microcracks is placed in isopropanol for cleaning, and then subjected to a second ultraviolet curing treatment.

[0017] Another objective of this invention is to provide a system for unsupported optimization reconstruction and 3D printing of digital cores containing microfractures. This system implements the aforementioned method for unsupported optimization reconstruction and 3D printing of digital cores containing microfractures. The system includes: The data preprocessing module is used to read digital core data containing microfractures that have been identified and segmented into three phases. The three phases include ordinary pore region, microfracture region and rock matrix region, which are represented by gray values ​​or label values ​​of 0, 1 and 2 respectively, and the binary data is reshaped into a three-dimensional array of a set size. The layer-by-layer connected region determination module is used to process the three-dimensional array layer by layer from the first layer according to the set printing direction. It uses the neighborhood algorithm to perform connected region analysis on the rock matrix region of each layer to obtain the number, label and region coordinate range of the rock matrix connected regions in the current layer, and establishes the microcrack structure protection area according to the spatial distribution of the microcrack region. The unsupported dynamic optimization and reconstruction module is used to extract the coordinate range of the connected regions of the current layer rock matrix, count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or three-dimensional digital core models containing microcracks. The module for comparing and analyzing the parameters of digital cores with microfractures before and after processing is used to calculate the topological parameters of digital core models with microfractures before and after optimization. The topological parameters include at least pore porosity, pore radius, pore shape factor, throat radius and coordination number, to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. The 3D printing verification and manufacturing module for digital core STL models with microcracks is used to output the digital core models with microcracks before and after optimization as STL files and import them into slicing software. The module uses the suspended structure prompts of the slicing software to verify the internal support requirements and performs 3D printing and post-processing on the optimized model.

[0018] Furthermore, the aforementioned unsupported optimization reconstruction and 3D printing system for digital cores containing microfractures is mounted on a computer-readable storage medium. This computer-readable storage medium stores a computer program, which, when executed by a processor, enables the functionality of the unsupported optimization reconstruction and 3D printing system for digital cores containing microfractures. Combining all the above technical solutions, the beneficial effects of this invention are as follows: First, this invention acquires digital core data containing microfractures that has undergone three-phase identification and segmentation. The three phases include ordinary pore regions, microfracture regions, and rock matrix regions, represented by grayscale values ​​or label values ​​of 0, 1, and 2, respectively. The binary data is then parsed and reconstructed into a three-dimensional array of a set size. Connectivity analysis of the rock matrix is ​​performed layer by layer according to a set printing direction to obtain the number, label, and coordinate range of connected regions in each layer. Based on the spatial distribution of microfracture regions, neighboring rock matrix regions adjacent to microfractures are extended and marked to establish microfracture structure protection areas. By statistically analyzing the pixel overlap relationship of the current layer's connected regions at corresponding positions in the previous layer, suspended matrix regions lacking solid support during 3D printing are identified. A mask is then constructed to convert the data attributes of isolated suspended matrix regions not belonging to the microfracture structure protection areas into ordinary pore regions, generating an optimized digital core model containing microfractures. The degree of structural preservation before and after reconstruction is verified by comparing topological parameters such as porosity, pore radius, pore shape factor, throat radius, and coordination number. Finally, an STL model is output and 3D printed and post-processed. This invention differs from reconstruction methods that aim to generate digital cores through image synthesis, random growth, or neural networks. Instead, it focuses on the directional optimization of the printability of segmented digital core models containing microcracks. This enables unsupported optimized reconstruction and solid fabrication of complex core models, reducing the need for internal support and minimizing the interference of residual internal support on pore structure and fluid flow path. It provides a high-precision, repeatable solid model for microscopic seepage experimental research.

[0019] Secondly, this invention addresses the need for the physical fabrication of digital cores containing microfractures. It can convert digital core models that have already undergone three-phase identification and segmentation into physical models suitable for 3D printing without internal support, thereby improving the conversion capability of digital cores from numerical models to experimental samples. This invention can be used in scenarios such as microstructure characterization of oil and gas reservoirs, micro-permeability experiments, displacement experiments, rock physics simulation experiments, and teaching demonstrations, and has clear engineering application value.

[0020] Compared to directly printing the original digital core model or adding support structures inside the model, this invention reduces the internal suspended matrix area during the digital modeling stage through layer-by-layer connected domain analysis, entity pixel overlap determination, and mask reconstruction, thereby reducing the need for internal support from the source. This reduces problems such as residual internal support material, pore blockage, and post-processing difficulties, improving the structural consistency and repeatability of physical digital core samples used in seepage experiments and physical simulation experiments.

[0021] This invention also establishes a standardized pre-processing workflow for digital core 3D printing, applicable to digital core models with different lithologies, voxel sizes, and microfracture development characteristics. This invention reduces the pre-processing cost of complex digital core models, decreases the time spent on manual layer-by-layer retouching, improves batch production efficiency, and expands the application scope of high-precision photopolymerization 3D printing equipment in oil and gas reservoir experimental research.

[0022] Third, a preliminary search of existing patents related to digital cores reveals that current technologies mainly focus on digital core image reconstruction, texture synthesis, parallel reconstruction of training images, reconstruction using random growth methods, 3D reconstruction using generative adversarial networks or VQGANs, and finite element simulation of digital cores. The primary goal of these technologies is to improve the generation quality, reconstruction efficiency, statistical feature consistency, or simulation accuracy of digital core models. However, they do not propose optimized reconstruction methods without internal support for 3D printing, specifically for digital core models containing microcracks that have already been labeled with ordinary pores, microcracks, and the three phases of the rock matrix.

[0023] The technical solution of this invention is not simply to generate digital cores, nor is it a conventional 3D printing slicing or post-processing technique. Instead, it establishes a manufacturability-oriented structural optimization step between the digital core model and the physical 3D printing manufacturing process. This step resolves the contradiction between the suspended matrix structure inside the digital core containing microfractures and the fidelity of the microfracture boundaries through a combination of techniques including layer-by-layer rock matrix connectivity analysis, adjacent layer solid pixel overlap support determination, microfracture structure protection area constraint, and mask attribute updating.

[0024] Therefore, this invention, in the specific technical direction of pre-processing and optimized reconstruction of unsupported 3D printing of three-phase digital core models containing microcracks, possesses technical characteristics distinct from existing digital core reconstruction and conventional 3D printing support generation technologies, and can be considered a supplement and improvement to existing digital core physical manufacturing processes. Within the scope of the preliminary search, no identical combination of technologies has been found.

[0025] Fourth, the physical printing of digital cores containing microfractures has long faced a prominent contradiction: on the one hand, the ordinary pores, pore throats and microfracture structures inside the digital core need to be preserved as realistically as possible, otherwise it will affect the reliability of subsequent micro-permeability experiments and reservoir physics simulation experiments; on the other hand, complex pores and microfractures will cause a large number of local suspended areas in the rock matrix in the printing direction. If the original model is completely preserved, it may lead to internal support requirements or unstable molding problems.

[0026] Traditional solutions typically fall into two categories: one involves adding support structures during the slicing stage, but the internal space of digital cores is small and complex, making it difficult to completely remove internal supports after printing, and residual supports may clog pores and flow channels; the other involves manual retouching, smoothing, or filling of the model, but this method is inefficient, inconsistent, and prone to excessively altering microfracture boundaries and pore topology. Therefore, how to improve the printability of digital core models containing microfractures without introducing residual internal supports, while preserving as much of the original pore and microfracture structure as possible, has been a key problem that the field has been striving to solve.

[0027] This invention optimizes the orientation of segmented three-phase digital cores before printing, transforming the lack of underlying solid support into a determination of the overlap number of adjacent solid pixels. Furthermore, it introduces a microcrack structure protection region to avoid damaging the matrix boundary adjacent to the microcracks when simply removing suspended areas. This solution simultaneously addresses the requirements for printing without internal support and for faithfully reproducing the microcrack structure, providing an automated, repeatable, and parameterizable solution to the aforementioned long-standing technical contradictions.

[0028] Fifth, this invention overcomes, to a certain extent, the traditional biases regarding internal support and structural fidelity in the field of complex digital core 3D printing. For complex internal pore models, conventional 3D printing approaches typically assume that suspended structures should be automatically supported by slicing software; while for digital core models, researchers generally prefer to avoid modifying the original pore and microcrack structures to prevent affecting experimental results. This combination of approaches easily leads to a technological inertia: either accepting internal support and its residual risks, completely preserving the original structure and enduring printing difficulties, or relying on manual experience for localized repairs.

[0029] This invention does not follow the traditional approach of adding supports during the printing stage. Instead, it starts from the source of the digital model, incorporating the interlayer solid support relationships along the printing direction into the digital core structure optimization process. Furthermore, this invention does not indiscriminately delete suspended structures; instead, it limits the scope of removal by protecting the microcrack structure area, allowing the optimization and reconstruction to avoid the matrix boundary adjacent to the microcracks. This invention overcomes the inertia of processing complex internal suspended structures that can only be solved by internal supports and the inability to perform any structural optimization on the digital core model to maintain the microcrack morphology.

[0030] This invention overcomes the misconception that complex porous models must rely on internal supports for printing; it also overcomes the misconception that digital core models containing microcracks cannot be structurally optimized before printing to ensure structural fidelity; and thirdly, it overcomes the misconception that deleting ordinary suspended areas inevitably damages the microcrack structure. This invention combines entity pixel overlap determination with a microcrack structure protection area, enabling model optimization to both serve print manufacturability and preserve the microcrack structural characteristics as much as possible. Attached Figure Description

[0031] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the disclosure of this invention and, together with the description, serve to explain the principles of this disclosure; Figure 1 This is a flowchart of the unsupported optimization reconstruction and 3D printing method for digital rock cores with microcracks provided by the present invention; Figure 2 This is a schematic diagram comparing the facial gaps of the generated model before and after processing, provided by the present invention. Figure 3 This is a schematic diagram comparing the pore radii of the generated model before and after processing provided by the present invention; Figure 4 This is a schematic diagram comparing the pore shape factor of the generated model before and after processing, provided by the present invention. Figure 5 This is a schematic diagram comparing the throat radius of the generated model before and after processing provided by the present invention; Figure 6 This is a schematic diagram comparing the coordination number of the generated model before and after processing, provided by the present invention. Figure 7 This is a schematic diagram of the slicing software provided by the present invention for identifying suspended structures; wherein, (a) is the initial model diagram and (b) is the reconstructed model diagram; Figure 8 This is a comparative schematic diagram of seepage simulation experiments provided by the present invention; wherein, (a) is the original model diagram and (b) is the reconstructed model diagram; Figure 9 This is a schematic diagram of the physical model of the 3D printed digital rock core containing microcracks provided by the present invention. Detailed Implementation

[0032] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0033] The innovation of this invention lies in addressing the common problem of suspended structures in the 3D printing of digital cores containing microfractures. Instead of employing traditional internal physical support methods or regenerating the digital core structure, this invention optimizes the structure from the source of the segmented three-phase digital model. Through layer-by-layer connected domain analysis, pixel overlap determination, and mask reconstruction techniques, it automatically identifies and eliminates suspended matrix regions lacking solid support in the printing direction. Simultaneously, it establishes structural protection zones based on the spatial distribution characteristics of microfracture regions, minimizing the impact of optimization on the microfracture regions and their adjacent rock matrix boundaries. This method improves the printability of digital core models containing microfractures while preserving the original pore structure and microfracture spatial morphology as much as possible, providing a high-fidelity, internally unsupported solid model preparation path for microscopic seepage experiments and reservoir physical simulation studies.

[0034] Example 1.

[0035] This invention proposes a method for unsupported optimization reconstruction and 3D printing of digital core samples containing microcracks. This method targets digital core data where ordinary pores, microcracks, and rock matrix have already been identified and segmented. It utilizes layer-by-layer connected domain analysis, solid pixel overlap determination, microcrack structure protection regions, and mask reconstruction techniques to automatically identify and eliminate isolated, suspended matrix regions lacking support along the printing direction. This enables unsupported optimization reconstruction and solid fabrication of digital core models containing microcracks.

[0036] Specifically, a method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks includes reading digital core data containing microcracks that has been segmented by three-phase identification, with ordinary pores, microcracks, and rock matrix marked as 0, 1, and 2 respectively, and reshaping the binary data into a three-dimensional array of a specified size.

[0037] Subsequently, the process is carried out layer by layer along the set printing direction. The connected domain analysis of each layer of rock matrix is ​​performed based on the neighborhood algorithm to obtain the number, label and coordinate range of each connected region. At the same time, the exclusive structural protection area is delineated based on the spatial distribution of microcracks.

[0038] Next, unsupported dynamic optimization is performed: the coordinates of each matrix connected region in the current layer are extracted, the number of pixels overlapping with the corresponding position in the previous layer is counted, and the regions with an overlap number lower than the preset threshold and not within the microcrack protection range are identified as isolated suspended matrix. Their properties are changed to ordinary pores through a mask, and the optimized three-dimensional core model is output.

[0039] Then, the topological parameters such as porosity, pore throat radius, shape factor, and coordination number of the models before and after optimization were compared to verify the fidelity of the pore and matrix core structure. Finally, the optimized model was exported to STL format. After verification by slicing software that no internal support was required, 3D printing and post-processing were completed to achieve unsupported and precise manufacturing of microcracked rock cores.

[0040] like Figure 1 As shown, it specifically includes: S1. Read the digital core data containing microcracks that has been identified and segmented into three phases. The three phases include the ordinary pore region, the microcrack region, and the rock matrix region, and are represented by gray values ​​or label values ​​of 0, 1, and 2, respectively. Reshape the binary data into a three-dimensional array of a set size. S2. According to the set printing direction, process the three-dimensional array layer by layer starting from the first layer. Use the neighborhood algorithm to perform connected domain analysis on the rock matrix region of each layer to obtain the number of connected regions, labels and region coordinate range of the current layer of rock matrix. Establish the microcrack structure protection area according to the spatial distribution of the microcrack region. S3. Extract the coordinate range of the connected regions of the current layer rock matrix, and count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or digital core models containing microcracks. S4. Calculate the topological parameters of the digital core model with microcracks before and after optimization. The topological parameters include pore porosity, pore radius, pore shape factor, throat radius and coordination number to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. S5. Output the digital core model with microcracks before and after optimization as an STL file and import it into the slicing software. Use the suspended structure prompts of the slicing software to verify the internal support requirements, and perform 3D printing and post-processing on the optimized model.

[0041] For example, in step S1, the bit depth setting of the digital core data containing microfractures includes 8-bit or 16-bit, and the dimension of the three-dimensional array of the set size is determined according to CT scan parameters, core sampling size, and target printing precision, including but not limited to voxel dimensions of 300×300×3000 or 450×450×1000. The three-dimensional array is used to perform layer-by-layer connected component analysis, entity pixel overlap determination, microcrack structure protection area marking, and mask updating in the same spatial coordinate system.

[0042] Let the three-dimensional array (three-dimensional digital core array) be... ,in, Using spatial index coordinates, the three-phase data are represented as follows: ; In step S1, the three-phase identification and segmentation are completed by pre-image processing software, manual calibration method or digital core processing software. The present invention receives and processes digital core data containing microcracks that has been marked with three phases, wherein the gray value or label value of the ordinary pore area is 0, the gray value or label value of the microcrack area is 1, and the gray value or label value of the rock matrix area is 2.

[0043] In step S1, the microfracture region is a spatial region in the digital core data containing microfractures that has been marked as a microfracture phase. The microfracture region is elongated, sheet-like, linear, network-like, or irregularly extended. The ordinary pore region is a spatial region in the digital core data containing microfractures that has been marked as an ordinary pore phase. The rock matrix region is a region in the digital core data containing microfractures that has been marked as a solid phase.

[0044] In step S2, the neighborhood algorithm adopts the four-neighborhood algorithm and the eight-neighborhood algorithm. The neighborhood algorithm is used to merge the adjacent rock matrix pixels in each layer into the same rock matrix connected region, so that the subsequent entity pixel overlap determination is performed on the connected region as the object, rather than on the individual pixel as the object, thereby reducing point-by-point misjudgment and obtaining the region-level determination result corresponding to the printed suspended matrix structure.

[0045] If each pixel is judged individually, local noise points or thin-walled boundaries are easily misjudged as suspended structures. This invention obtains region-level labels by connecting domain marking, so that subsequent support determination is performed on the connected regions of the complete rock matrix, which improves the consistency between suspended matrix identification and model structure modification.

[0046] Let the first Binary image of layered rock matrix Its definition is: ; In the formula, Indicates the first Layer coordinates Binary identification of the rock matrix; This represents a three-dimensional array (a three-dimensional digital core array).

[0047] Let the neighborhood set be , Options 4 and 8 are acceptable. If there are two rock matrix points... and If there exists a path consisting of several rock matrix points, and any two adjacent points in the path satisfy a neighborhood relationship, then... and They belong to the same connected region of the same rock matrix. The result of layer connected component labeling can be represented as: ; ; ; In the formula, Indicates the first Layered rock matrix label matrix; Indicates the first The set of labels for non-background connected regions in the layer. Indicates the first The number of connected regions in the layered rock matrix. This is used to determine the number of connected regions in the current layer. Indicates the first Binary identification of layered rock matrix; For example, in step S2, the microcrack protection area is obtained by expanding the neighborhood of the microcrack area or marking the rock matrix area adjacent to the microcrack boundary; the microcrack structure protection area is used to limit the range of suspended matrix area removal in the subsequent optimization and reconstruction process, solving the problem that the ordinary suspended area removal method is prone to accidentally deleting the thin-walled matrix adjacent to the microcrack, resulting in the expansion of the microcrack width, distortion of the boundary morphology, or change of the microcrack connectivity.

[0048] The microcrack structure protection zone is used to address the problem of easily damaging microcrack boundaries during the removal of ordinary suspended matrix. Let the set of microcrack regions be F, and the set of rock matrix regions be M, then: ; ; set up For radius The neighborhood structural elements then protect the microcrack structure region. Represented as: ; In the formula: Represents the collection of microcrack regions One voxel point; Represents a collection of rock matrix regions One of the candidate voxel points; This represents a point centered at a voxel with a radius of . Neighborhood structural elements; Indicates the neighborhood expansion operator; The protection radius can be set according to the voxel size, microcrack width, printing layer thickness, and model fidelity requirements. This protected area allows optimized reconstruction to avoid microcracks near matrix boundaries when removing suspended matrix, reducing the risk of microcrack width expansion, boundary distortion, and changes in connectivity.

[0049] For example, in step S3, the unsupported dynamic optimization reconstruction further includes a connected region quantity determination step: performing connected region labeling on the current layer of rock matrix region to obtain a label matrix. and tag collection Statistical label set Number of China-Africa background tags ;like If only one connected rock matrix region exists in the current layer, the current layer data is saved and the overlapping of entity pixels in the current layer is skipped and the region-by-region determination is performed; if Then, the number of overlapping entity pixels is counted for each connected region of the rock matrix.

[0050] The technical function of this skipping mechanism is to reduce redundant calculations in large-scale digital core layer-by-layer processing while maintaining the focus on determining multi-connected regions. For example, in step S3, the pixel overlap number refers to the number of pixel overlaps between the current layer's connected rock matrix and the previous layer's connected rock matrix at the same coordinate region. When the overlap number of a certain connected rock matrix at the corresponding position in the previous layer is less than a preset threshold, the connected region is initially marked as an isolated suspended matrix region. The entity pixel overlap determination is based on the support relationship between adjacent layers in the printing direction, which can distinguish between spatial regions in the real pore structure and suspended matrix regions lacking lower-layer support during the printing process.

[0051] Let the first The first in the layer The connected regions of the rock matrix are Then the number of overlapping entity pixels at the corresponding position in the previous layer. Represented as: ; In the formula: This indicates an indicator function that takes the value 1 when the condition inside the parentheses is true, and 0 otherwise. Indicates the first Layer The number of overlapping entity pixels in the connected regions of the rock matrix. If ,but It was initially identified as an isolated, suspended matrix region. This is a preset threshold. A value of 1 can be selected, indicating that when the current connected region has no physical support point at the corresponding position in the previous layer, it is initially determined to be a suspended structure.

[0052] In step S3, for the initially marked isolated suspended matrix region, it is further determined whether it intersects with the microcrack structure protection region; if the isolated suspended matrix region intersects with the microcrack structure protection region, the region is retained; if the isolated suspended matrix region does not intersect with the microcrack structure protection region, it is regarded as a suspended matrix region to be removed, and the data attributes of the corresponding region are modified from rock matrix region to ordinary pore region through masking.

[0053] Collection of suspended matrix regions to be removed Represented as: ; Then a mask is constructed. : ; The properties of the 3D array are updated based on the mask to obtain the optimized 3D array. : ; By using the above method, the suspended matrix area to be removed is changed from the rock matrix area to the ordinary pore area, while the ordinary pore area, the microcrack area, and the adjacent rock matrix area within the microcrack structure protection area are retained.

[0054] For example, in step S4, the porosity is the ratio of the sum of the number of pixels in the ordinary pore region and the microcrack region of the current layer to the total number of pixels in the current layer; the pore radius and throat radius are calculated based on the equivalent circle radius of the pore or throat cross-sectional area; the pore shape factor is calculated based on the pore volume and surface area; the coordination number is calculated based on the number of throats connected to a single pore; the topology parameters are used to evaluate the degree of structural preservation of the pore space and microcrack space before and after optimization and reconstruction, and serve as a criterion for whether the optimization without internal support excessively alters the original digital core structure.

[0055] No. Layer porosity Represented as: ; In the formula, Indicates the first The sum of the number of pixels in the ordinary porous region and the microcrack region of the layer; Indicates the first Total number of pixels in the layer.

[0056] Pore ​​equivalent radius Represented as: ; In the formula, This represents the cross-sectional area of ​​a single pore region.

[0057] The pore shape factor G is expressed as: ; In the formula, Represents the three-dimensional volume of a single pore; This represents the three-dimensional surface area of ​​a single pore.

[0058] The throat radius rt is represented as: ; In the formula, This indicates the cross-sectional area of ​​the throat.

[0059] Coordination number Represented as: ; in, This indicates the coordination number of a single pore.

[0060] The parameters mentioned above are commonly used parameters in digital core structure evaluation. The innovation of this invention lies in using these parameters as structural fidelity constraints and verification indicators for unsupported optimization and reconstruction: if the overall distribution of porosity, pore radius, pore shape factor, throat radius and coordination number after optimization is close to that before optimization, it indicates that the method of this invention mainly changes the suspended matrix area that affects the printing process, without causing excessive modification to the overall pore topology of the digital core.

[0061] In step S5, the slicing software is PreForm slicing software, the 3D printing equipment is Form 4 printing equipment, the printing material is Formlabs Clear V5 transparent resin, and the printing layer thickness is 25μm. During slicing, no internal support structure is generated for the model; only external support or base support is set according to the external fixation and molding needs of the model. After printing, the model is placed in isopropanol for 30 minutes for cleaning, followed by a secondary ultraviolet curing treatment.

[0062] As demonstrated by the above embodiments, this invention achieves unsupported optimized manufacturing of digital core models containing microcracks. Through layer-by-layer connected domain analysis and pixel overlap determination, this invention automatically identifies suspended matrix regions lacking underlying solid support in the printing direction, and transforms them into ordinary porous regions through mask reconstruction. This reduces the need for internal support in the model and improves the printability of complex digital core models without internal support.

[0063] This invention reduces the interference of internal support materials on the pore structure. By optimizing the structure from the digital model source, it eliminates the need to add extensive support structures in the complex pore and microcrack regions within the core model. This reduces the impact of residual support material on pore space and fluid flow paths, improving the stability and repeatability of subsequent experiments.

[0064] This invention balances model printability and structural preservation. While identifying suspended matrix regions, it introduces a microcrack structure protection region, restricting the boundaries of the microcrack regions and their adjacent rock matrix to minimize alterations to the original microcrack morphology and adjacent matrix structure during the optimization and reconstruction process.

[0065] This invention improves model processing efficiency and standardization. It utilizes automated algorithms to replace manual layer-by-layer mapping and skips single-connected layers that do not require region-by-region evaluation by determining the number of connected regions. This enables rapid processing of high-resolution digital core data, reduces human error, and provides a technical means for the batch and standardized preparation of digital core models containing microfractures.

[0066] Unlike existing digital core reconstruction methods, this invention does not utilize texture synthesis, image training, random growth, or neural networks to regenerate digital cores. Instead, it focuses on optimizing the printability of pre-segmented digital cores containing microcracks during the 3D printing manufacturing process. The technical objectives, processing targets, and judgment criteria are all different.

[0067] Example 2.

[0068] This invention proposes a supportless optimization reconstruction and 3D printing system for digital cores containing microcracks, comprising: The data preprocessing module is used to read digital core data containing microfractures that have been identified and segmented into three phases. The three phases include ordinary pore region, microfracture region and rock matrix region, which are represented by gray values ​​or label values ​​of 0, 1 and 2 respectively, and the binary data is reshaped into a three-dimensional array of a set size. The layer-by-layer connected region determination module is used to process the three-dimensional array layer by layer from the first layer according to the set printing direction. It uses the neighborhood algorithm to perform connected region analysis on the rock matrix region of each layer to obtain the number, label and region coordinate range of the rock matrix connected regions in the current layer, and establishes the microcrack structure protection area according to the spatial distribution of the microcrack region. The unsupported dynamic optimization and reconstruction module is used to extract the coordinate range of the connected regions of the current layer rock matrix, count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or three-dimensional digital core models containing microcracks. The module for comparing and analyzing the parameters of digital cores with microfractures before and after processing is used to calculate the topological parameters of digital core models with microfractures before and after optimization. The topological parameters include at least pore porosity, pore radius, pore shape factor, throat radius and coordination number, to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. The 3D printing verification and manufacturing module for digital core STL models with microcracks is used to output the digital core models with microcracks before and after optimization as STL files and import them into slicing software. The module uses the suspended structure prompts of the slicing software to verify the internal support requirements and performs 3D printing and post-processing on the optimized model.

[0069] The unsupported optimization reconstruction and 3D printing method for digital cores containing microcracks provided in this invention includes the following steps: Step 1, Data Preprocessing: Read the digital core data containing microfractures that has been identified and segmented into three phases. The three phases include the ordinary pore region, the microfracture region, and the rock matrix region, which are represented by gray values ​​or label values ​​of 0, 1, and 2, respectively. The binary data is then reshaped into a three-dimensional array of a set size. Specifically, ordinary pore regions are defined as grayscale values ​​or label values ​​of 0, microcrack regions are defined as grayscale values ​​or label values ​​of 1, and rock matrix regions are defined as grayscale values ​​or label values ​​of 2. The above three-phase identification and segmentation can be performed by pre-processing image software, manual calibration, or digital core processing software. The method of this invention does not require a microcrack identification algorithm as a necessary step; instead, it uses digital core data containing microcracks that has already been labeled with three phases as input. In this embodiment, a 300×300×300 voxel dimension can be used for illustration, and a copy of the original data is created for subsequent comparison of parameters before and after processing.

[0070] Step 2, Layer-by-layer connected region determination: According to the set printing direction, the three-dimensional array is processed layer by layer starting from the first layer. The neighborhood algorithm is used to analyze the connected regions of the rock matrix region of each layer to obtain the number of connected regions, labels and region coordinate range of the rock matrix in the current layer. The microcrack structure protection area is established according to the spatial distribution of the microcrack region. For each slice of data, a neighborhood algorithm is used to perform connected component analysis on the rock matrix region, and each connected region is assigned a unique label. The neighborhood algorithm can be a four-neighbor algorithm or an eight-neighbor algorithm. The eight-neighbor algorithm includes determining the adjacency relationships of pixels in the vertical, horizontal, and diagonal directions. In this embodiment, an eight-neighborhood algorithm with 3×3 structuring elements is used to traverse the rock matrix pixels of the current layer, marking mutually contacting matrix pixels as the same connected region and assigning corresponding connected region labels. This process elevates the subsequent judgment object from a single pixel to a connected region of the rock matrix, which can reduce misjudgments caused by local noise or thin-walled boundaries.

[0071] Simultaneously, based on the spatial distribution characteristics of the microcrack regions, the boundaries of the microcrack regions and their adjacent rock matrix regions are marked to establish microcrack structure protection zones. These microcrack structure protection zones are used to limit the removal range of suspended areas during subsequent unsupported optimization and reconstruction processes, thereby minimizing changes to the original microcrack morphology and its adjacent matrix boundaries.

[0072] Step 3, Unsupported Dynamic Optimization and Reconstruction: Extract the coordinate range of the connected regions of the current layer rock matrix, and count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or a three-dimensional digital core model containing microcracks; The pixel overlap number refers to the number of pixels overlapping between the current layer rock matrix connected region and the previous layer rock matrix connected region at the same coordinate area. When the overlap number of a certain rock matrix connected region at the corresponding position in the previous layer is less than a preset threshold, the connected region is initially marked as an isolated suspended matrix region. The entity pixel overlap determination is based on the support relationship between adjacent layers in the printing direction, which can distinguish between the spatial region in the real pore structure and the suspended matrix region that lacks the support of the lower layer entity during the printing process. In this embodiment, the preset threshold can be set to 1. When the number of overlapping pixels of a certain connected region at the corresponding position in the previous layer is less than 1, it indicates that the region has no solid support point below and belongs to a suspended matrix region. In practical applications, the preset threshold can be adjusted according to the printing layer thickness, model size, resin material properties, and printing equipment accuracy. Before counting pixel overlap, this invention can also set a skipping mechanism. If it is determined that there is only one continuous connected region of rock matrix in the current layer, it can be directly determined that there is no suspended matrix region in that layer, the current layer data can be saved and the process can skip to the next layer. This skipping mechanism can reduce unnecessary repetitive calculations and improve the efficiency of large-scale digital core data processing; For the initially marked isolated suspended matrix regions, it is further determined whether they intersect with the microcrack structure protection region. If the isolated suspended matrix region intersects with the microcrack structure protection region, the region is retained. If the isolated suspended matrix region does not intersect with the microcrack structure protection region, it is regarded as a suspended matrix region to be removed, and the data attributes of the corresponding region are modified from rock matrix region to ordinary pore region through masking. Subsequently, a mask is constructed for the areas of suspended matrix to be removed. Constructing the mask involves creating a marker layer at the connected regions labeled as areas of suspended matrix to be removed, and then modifying the data attributes of the corresponding regions to ordinary porous regions in one step using the mask. For example, in binarized digital core data, the value of the corresponding region can be changed from 2 to 0, transforming the region from a solid phase of rock matrix to a porous phase. Save the modification results of the current layer and use them as the basis for the judgment of the next layer. Repeat the above steps until the last layer is processed. Finally, convert the processed 3D array back to binary data in memory order, and output it as a new raw file sequence according to the specified path and size to obtain the optimized digital core model with microcracks; Through the above steps, the present invention can automatically identify and process the suspended matrix area lacking support in the printing direction, while using the microcrack structure to protect the area and reduce the impact on the microcrack morphology and its adjacent matrix boundary, thereby realizing the unsupported optimized reconstruction of the digital core model containing microcracks.

[0073] Step 4, comparative analysis of digital core parameters with microfractures before and after processing: calculate the topological parameters of the digital core models with microfractures before and after optimization. The topological parameters include at least pore porosity, pore radius, pore shape factor, throat radius and coordination number to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. like Figures 2 to 6 As shown, the topological parameters of the model before and after optimization, such as porosity, pore radius, pore shape factor, throat radius, and coordination number, were calculated and compared using professional software. The comparison of these parameters demonstrates that the pore structure and rock matrix structure of the digital core were well preserved before and after optimization and reconstruction. The comparison of parameters before and after processing shows that the parameter curves of the reconstructed model are generally close to those of the initial model, and the main pore structure parameters are relatively similar. This indicates that the method mainly targets the suspended matrix area that affects 3D printing and does not significantly change the overall structure of the original digital core.

[0074] Step 5, 3D printing verification and manufacturing of digital core STL model with microcracks: Output the digital core model with microcracks before and after optimization as STL file and import it into slicing software. Use the suspended structure prompt of the slicing software to verify the internal support requirements, and perform 3D printing and post-processing on the optimized model. For comparative verification, the same initial digital core model containing microcracks can be processed in the following two ways: The first is the existing conventional method, which directly outputs the original three-phase digital core model as an STL and imports it into PreForm slicing software to check the internal suspension prompts and support requirements; the second is the method of this invention, which first performs layer-by-layer connected domain analysis, entity pixel overlap determination, microcrack structure protection area constraint and mask reconstruction, and then outputs the STL and imports it into PreForm slicing software to check the internal suspension prompts and support requirements.

[0075] like Figure 7 A schematic diagram of a suspended structure identified by slicing software; among which, Figure 7 Figure (a) is the initial model diagram. Figure 7 Figure (b) shows the reconstructed model. The initial model may contain a large number of suspended areas marked by the software, representing structures inside the model that require support during printing. In the model optimized and reconstructed using the method of this invention, the areas requiring support are significantly reduced or disappear, indicating that the optimized model can meet the requirements for printing without internal support. Figure 8 This is a comparative diagram of seepage simulation experiments; among them, Figure 8 Figure (a) in the diagram is the original model diagram. Figure 8 Figure (b) shows the reconstructed model. Seepage simulation experiments were conducted on both the initial digital core model and the optimized reconstructed digital core model to quantitatively test the model permeability. The test results show that the initial model permeability is 71.21 mD, and the optimized reconstructed model permeability is 71.35 mD. The two values ​​are close and there is no significant difference. This proves that the method of removing isolated suspended matrix regions only adjusts the local microstructure and does not significantly disturb the overall seepage capacity of the core, thus better preserving the original core's seepage characteristics.

[0076] During the printing process, the slicing precision can be set to 25μm. Transparent photosensitive resin can be used as the printing material to facilitate subsequent observation of the model's internal structure and related experiments. Printing parameters can be adjusted according to the type of printing equipment, resin material properties, model size, and molding precision requirements. After printing, the model is placed in isopropanol solvent for 30 minutes of ultrasonic cleaning to remove residual resin from the model surface and internal space; then it is subjected to a 30-minute UV secondary curing treatment at 40°C to improve the overall strength and dimensional stability of the model. like Figure 9 As shown, the final 3D printed physical model of the digital core with microfractures has a complete structure and does not require the setting of traditional support structures inside. This can reduce the impact of support residues on pore space and fluid flow path, and can be used for reservoir microstructure characterization, physical simulation experiments and micro-seepage experimental research.

[0077] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention and within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for unsupported optimized reconstruction and 3D printing of digital cores containing microcracks, characterized in that, The method includes the following steps: S1. Read the digital core data containing microcracks that has been identified and segmented into three phases. The three phases include the ordinary pore region, the microcrack region, and the rock matrix region, and are represented by gray values ​​or label values ​​of 0, 1, and 2, respectively. Reshape the binary data into a three-dimensional array of a set size. S2. According to the set printing direction, process the three-dimensional array layer by layer starting from the first layer. Use the neighborhood algorithm to perform connected domain analysis on the rock matrix region of each layer to obtain the number of connected regions, labels and region coordinate range of the current layer of rock matrix. Establish the microcrack structure protection area according to the spatial distribution of the microcrack region. S3. Extract the coordinate range of the connected regions of the current layer rock matrix, and count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer. Connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area are marked as isolated suspended matrix regions. A mask is constructed and the data attributes of the isolated suspended matrix regions are changed from rock matrix regions to ordinary pore regions to generate optimized digital core raw file sequences or digital core models containing microcracks. S4. Calculate the topological parameters of the digital core model with microcracks before and after optimization. The topological parameters include pore porosity, pore radius, pore shape factor, throat radius and coordination number to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. S5. Output the digital core model with microcracks before and after optimization as an STL file and import it into the slicing software. Use the suspended structure prompts of the slicing software to verify the internal support requirements, and perform 3D printing and post-processing on the optimized model.

2. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 1, characterized in that, In step S1, the bit depth setting of the digital core data containing microcracks includes 8-bit or 16-bit. The dimension of the three-dimensional array of the set size is determined according to the CT scan parameters, core sampling size and target printing accuracy, including voxel dimensions of 300×300×3000 or 450×450×1000. The three-dimensional array is used to perform layer-by-layer connected domain analysis, entity pixel overlap determination, microcrack structure protection area marking and mask updating in the same spatial coordinate system.

3. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 2, characterized in that, The three-phase identification and segmentation are completed by pre-image processing software, manual calibration method or digital core processing software. The system receives and processes digital core data containing microcracks that has been marked with three phases, where the gray value or label value of the ordinary pore area is 0, the gray value or label value of the microcrack area is 1, and the gray value or label value of the rock matrix area is 2. The microfractured region is a spatial region in digital core data containing microfractures that has been marked as a microfractured phase. The microfractured region is in the form of a slender, sheet-like, linear, network-like, or irregularly extended shape. The ordinary pore region is a spatial region in digital core data containing microfractures that has been marked as an ordinary pore phase. The rock matrix region is a region in digital core data containing microfractures that has been marked as a solid phase.

4. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 1, characterized in that, In step S2, the neighborhood algorithm adopts the four-neighborhood algorithm and the eight-neighborhood algorithm; the neighborhood algorithm is used to merge adjacent rock matrix pixels in each layer into the same rock matrix connected region, so that the subsequent entity pixel overlap determination takes the connected region as the object; The microcrack protection area is obtained by expanding the neighborhood of the microcrack area or by marking the rock matrix area adjacent to the microcrack boundary; the microcrack structure protection area is used to limit the range of suspended matrix area removal during subsequent optimization and reconstruction.

5. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 1, characterized in that, In step S3, marking connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions includes: performing connected component labeling on the current layer of rock matrix region to obtain a label matrix. and tag collection Statistical label set Number of China-Africa background tags ;like If the current layer has only one continuous connected rock matrix region, the current layer data is saved and the overlapping of entity pixels in the current layer is skipped and the region is determined one by one; if Then, the number of overlapping entity pixels is counted for each connected region of the rock matrix.

6. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 5, characterized in that, The pixel overlap number is the number of pixels overlapping between the connected regions of the current layer rock matrix and the connected regions of the previous layer rock matrix at the same coordinate region location. When the number of overlaps of a certain rock matrix connected region at the corresponding position in the upper layer is less than a preset threshold, the connected region is initially marked as an isolated suspended matrix region; the entity pixel overlap determination is based on the support relationship of adjacent layers in the printing direction to distinguish between the spatial region in the real pore structure and the suspended matrix region that lacks the support of the lower layer during the printing process. For the initially marked isolated suspended matrix region, determine whether it intersects with the microcrack structure protection region; If the isolated suspended matrix region intersects with the microcrack structure protection region, the region is retained; if the isolated suspended matrix region does not intersect with the microcrack structure protection region, it is treated as a suspended matrix region to be removed, and the data attributes of the corresponding region are modified from rock matrix region to ordinary pore region through a mask.

7. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 1, characterized in that, In step S4, the porosity is the ratio of the sum of the number of pixels in the ordinary pore region and the microcrack region of the current layer to the total number of pixels in the current layer; the pore radius and throat radius are calculated based on the equivalent circle radius of the pore or throat cross-sectional area; the pore shape factor is calculated based on the pore volume and surface area; the coordination number is calculated based on the number of throats connected to a single pore; the topology parameters are used to evaluate the degree of structural preservation of the pore space and microcrack space before and after optimization and reconstruction, and serve as a criterion for whether the optimization without internal support excessively alters the original digital core structure.

8. The method for unsupported optimization reconstruction and 3D printing of digital cores containing microcracks according to claim 1, characterized in that, In step S5, the material used for 3D printing is transparent resin, and the printing layer thickness is 25μm. When slicing, no internal support structure is generated for the digital core model containing microcracks. External support or base support is set according to the external fixation and molding of the digital core model containing microcracks. After printing, the digital core model containing microcracks is placed in isopropanol for cleaning, and then subjected to a second ultraviolet curing treatment.

9. A supportless optimization reconstruction and 3D printing system for digital rock cores containing microcracks, characterized in that, This system implements the unsupported optimized reconstruction and 3D printing method for digital cores with microfractures as described in any one of claims 1-8, and the system includes: The data preprocessing module is used to read digital core data containing microfractures that have been identified and segmented into three phases. The three phases include ordinary pore region, microfracture region and rock matrix region, which are represented by gray values ​​or label values ​​of 0, 1 and 2 respectively, and the binary data is reshaped into a three-dimensional array of a set size. The layer-by-layer connected region determination module is used to process the three-dimensional array layer by layer from the first layer according to the set printing direction. It uses the neighborhood algorithm to perform connected region analysis on the rock matrix region of each layer to obtain the number, label and region coordinate range of the rock matrix connected regions in the current layer, and establishes the microcrack structure protection area according to the spatial distribution of the microcrack region. The unsupported dynamic optimization and reconstruction module is used to extract the coordinate range of the connected regions of the current layer rock matrix, count the number of pixel overlaps of each connected region label in the current layer at the corresponding coordinate position in the previous layer; mark the connected regions with an overlap number less than a preset threshold and not belonging to the microcrack structure protection area as isolated suspended matrix regions, construct a mask and change the data attributes of the isolated suspended matrix regions from rock matrix regions to ordinary pore regions, and generate an optimized sequence of raw files or three-dimensional digital core models containing microcracks. The module for comparing and analyzing the parameters of digital cores with microfractures before and after processing is used to calculate the topological parameters of digital core models with microfractures before and after optimization. The topological parameters include at least pore porosity, pore radius, pore shape factor, throat radius and coordination number, to verify the degree of preservation of pore structure and rock matrix structure before and after optimization and reconstruction. The 3D printing verification and manufacturing module for digital core STL models with microcracks is used to output the digital core models with microcracks before and after optimization as STL files and import them into slicing software. The module uses the suspended structure prompts of the slicing software to verify the internal support requirements and performs 3D printing and post-processing on the optimized model.

10. The unsupported optimization reconstruction and 3D printing system for digital cores containing microfractures according to claim 9, characterized in that, The aforementioned unsupported optimization reconstruction and 3D printing system for digital cores with microcracks is mounted on a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, can realize the functions of the aforementioned unsupported optimization reconstruction and 3D printing system for digital cores with microcracks.

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