Digital rock debris library construction method and device based on pressed sample and multispectrum combination

Abstract

The embodiment of the invention provides a digital rock debris library construction method and device based on pressed sample and multispectrum combination, and the method comprises the steps: preparing rock debris into a transparent pressed sample which can be stored permanently, and cooperatively utilizing a plurality of lossless spectrum and morphology analysis technologies. According to the method, high-fidelity and low-cost digital acquisition of physical structures and chemical components of rock debris is realized, the constructed integrated three-dimensional model fusing minerals, elements and pore structures greatly enriches the dimensionality and analyzability of geological data, and the method has the advantages that the analysis cost of a single sample and the equipment investment threshold are remarkably reduced; the large-scale and structured digital archiving and efficient retrieval of massive rock debris samples become reality, and a reliable and easily-called data basis is provided for continuous geological evaluation of an oil field, fine representation of a reservoir and optimization of an engineering scheme.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of oil and gas exploration technology, and in particular to a method for constructing a digital cuttings library based on the combined use of compressed samples and multispectral analysis. Background Technology

[0002] Traditional rock cuttings management methods face significant limitations. Physical storage makes rock cuttings samples susceptible to weathering and physical metamorphism, preventing long-term reuse. Early digital methods, due to insufficient resolution or limited information dimensions, fail to obtain comprehensive mineral and structural information. Equipment with high-precision microscopic analysis capabilities is difficult to promote in large-scale oilfield applications due to high purchase and operating costs and low detection efficiency. For a long time, the industry has lacked a digital solution that can achieve long-term non-destructive preservation of rock cuttings at low cost, while simultaneously acquiring multi-dimensional information such as mineral composition, elemental distribution, and microstructure.

[0003] Therefore, a better solution is urgently needed. Summary of the Invention

[0004] In view of this, embodiments of this specification provide a method for constructing a digital cuttings library based on the combined use of pressed samples and multispectral analysis. One or more embodiments of this specification also relate to an apparatus for constructing a digital cuttings library based on the combined use of pressed samples and multispectral analysis, a computing device, a computer-readable storage medium, and a computer program, to address the technical deficiencies existing in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a method for constructing a digital cuttings library based on the combined use of compressed samples and multispectral analysis is provided, comprising:

[0006] Rock fragments were mixed with transparent epoxy resin and then subjected to vacuum degassing and high-pressure curing to form pressed samples. X-ray diffraction analysis, X-ray fluorescence surface scanning and structured light three-dimensional scanning were performed on the pressed samples to obtain mineral composition data, elemental distribution data and three-dimensional morphology data, respectively. By fusing mineral composition data, elemental distribution data, and three-dimensional morphology data, an integrated three-dimensional digital model containing information on minerals, elements, and pore structure is generated. The integrated 3D digital model is associated with the corresponding well depth and coordinate information and stored in the database.

[0007] In one possible implementation, mixing rock chips with transparent epoxy resin includes mixing rock chip particles with a particle size of 2-5 mm with transparent epoxy resin in a 1:3 ratio.

[0008] In one possible implementation, vacuum degassing and high-pressure curing are performed in a vacuum environment followed by degassing at 80 degrees Celsius and 20 MPa to form a transparent solid pressed sample with a hardness higher than Mohs 6.

[0009] In one possible implementation, X-ray diffraction analysis of the pressed sample includes: using a copper target X-ray source to scan the pressed sample within a scanning angle range of 5 to 70 degrees to obtain quantitative mineral composition data.

[0010] In one possible implementation, X-ray fluorescence surface scanning of the pressed sample includes scanning the surface of the pressed sample in steps of 0.5 mm to obtain distribution data of multiple elements.

[0011] In one possible implementation, structured light 3D scanning of the pressed sample includes: scanning the surface of the pressed sample at a resolution of 50 micrometers to obtain 3D topographic data containing information on pores and cracks, and extracting the topological network of cracks with a length greater than 200 micrometers.

[0012] In one possible implementation, fusing mineral composition data, elemental distribution data, and three-dimensional morphology data to generate an integrated three-dimensional digital model includes: generating a mineral distribution matrix based on the mineral composition data, generating an elemental distribution matrix based on the elemental distribution data, extracting a pore network based on the three-dimensional morphology data, and generating a three-dimensional vector model based on the mineral distribution matrix, elemental distribution matrix, and pore network.

[0013] According to a second aspect of the embodiments of this specification, a digital rock debris library construction device based on the combined use of compressed samples and multispectral analysis is provided, comprising: The sample pressing module is configured to mix rock fragments with transparent epoxy resin and then perform vacuum degassing and high-pressure curing to form pressed samples. The data scanning module is configured to perform X-ray diffraction analysis, X-ray fluorescence surface scanning and structured light three-dimensional scanning on the pressed sample to obtain mineral composition data, elemental distribution data and three-dimensional morphology data, respectively. The digital model module is configured to fuse mineral composition data, elemental distribution data, and three-dimensional morphology data to generate an integrated three-dimensional digital model containing mineral, elemental, and pore structure information. The data storage module is configured to associate the integrated 3D digital model with the corresponding well depth and coordinate information and store it in the database.

[0014] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-described method for constructing a digital rock debris library based on the combination of compressed samples and multispectral analysis.

[0015] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the above-described method for constructing a digital rock debris library based on the combination of pressed samples and multispectral analysis.

[0016] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the above-described method for constructing a digital rock debris library based on the combination of compressed samples and multispectral analysis.

[0017] This specification provides a method and apparatus for constructing a digital rock cuttings library based on the combined use of pressed samples and multispectral analysis. The method involves preparing rock cuttings into permanently preserved transparent pressed samples and synergistically utilizing various non-destructive spectral and morphological analysis techniques. This achieves high-fidelity, low-cost digital acquisition of the physical structure and chemical composition of rock cuttings. The constructed integrated three-dimensional model, incorporating mineral, elemental, and pore structure data, significantly enriches the dimensionality and resolvability of geological data. This method not only significantly reduces the cost of single-sample analysis and the equipment investment threshold but also makes large-scale, structured digital archiving and efficient retrieval of massive rock cuttings samples a reality. It provides a reliable and easily accessible data foundation for continuous geological evaluation of oilfields, fine reservoir characterization, and engineering scheme optimization. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for constructing a digital rock debris library based on the combined use of compressed samples and multispectral analysis, as provided in one embodiment of this specification. Figure 2 This is a schematic diagram of a digital rock debris library construction device based on the combined use of compressed samples and multispectral analysis, provided in one embodiment of this specification. Figure 3 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0019] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0020] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0021] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0022] This specification provides a method for constructing a digital rock debris library based on the combined use of compressed samples and multispectral imaging. It also relates to an apparatus for constructing a digital rock debris library based on the combined use of compressed samples and multispectral imaging, a computing device, and a computer-readable storage medium, which will be described in detail in the following embodiments.

[0023] See Figure 1 , Figure 1 A flowchart is shown of a method for constructing a digital rock debris library based on the combination of compressed samples and multispectral analysis according to an embodiment of this specification, specifically including the following steps.

[0024] Step 101: Mix rock chips with transparent epoxy resin and then perform vacuum degassing and high-pressure curing to form a pressed sample; Step 102: Perform X-ray diffraction analysis, X-ray fluorescence surface scanning, and structured light three-dimensional scanning on the pressed sample to obtain mineral composition data, elemental distribution data, and three-dimensional morphology data, respectively. Step 103: Merge the mineral composition data, elemental distribution data, and three-dimensional morphology data to generate an integrated three-dimensional digital model containing mineral, elemental, and pore structure information; Step 104: Associate the integrated 3D digital model with the corresponding well depth and coordinate information, and store it in the database.

[0025] Rock cuttings can refer to rock fragments generated during oil and gas drilling. Transparent epoxy resin can refer to an optically transparent, high-hardness, two-component polymer material, such as a mixture of EPON 828 resin and a specific curing agent. Vacuum degassing and high-pressure curing treatment refers to the process of removing air bubbles from the mixture under negative pressure, followed by complete cross-linking and curing of the resin under set temperature and pressure conditions. Pressed sample refers to a transparent solid sheet formed after the aforementioned process, internally encapsulating and fixing the original rock cutting particles. X-ray diffraction analysis refers to a non-destructive testing technique that uses X-rays to irradiate a sample and analyzes the diffraction pattern to determine the types and relative contents of mineral crystals in the sample. Mineral composition data refers to the results obtained through X-ray diffraction analysis that describe the types and quantitative percentages of each mineral phase (such as quartz, feldspar, and clay minerals) in the sample. X-ray fluorescence surface scanning refers to a non-destructive testing technique that uses X-rays to excite the characteristic fluorescence of elements on the sample surface and obtains two-dimensional distribution information of multiple elements through point-by-point scanning. Elemental distribution data can refer to a data map or matrix obtained through X-ray fluorescence surface scanning, describing the spatial variation of the content of specific elements (such as silicon, calcium, and aluminum) on the sample surface. Structured light 3D scanning refers to an optical measurement technique that reconstructs the 3D morphology of a sample surface by projecting a specific grating pattern onto it and capturing its deformation. 3D morphology data can refer to a 3D point cloud or mesh model obtained through structured light 3D scanning, containing the microscopic undulations, pore and crack geometry, and their locations on the sample surface. An integrated 3D digital model refers to a digital vector model that integrates multi-source information such as minerals, chemical elements, and pore structure, and can be uniformly displayed and queried in 3D space. Well depth and coordinate information refers to the drilling depth and geographic coordinates of the cuttings sample, which are key metadata related to the geological background.

[0026] The present invention will be further described below through a detailed embodiment: In this embodiment, it is necessary to digitize the cuttings samples obtained from different depths of an oil and gas well in order to construct a digital cuttings library for the well.

[0027] First, the pressed sample preparation step is performed. Rock cuttings samples from a specific depth (e.g., a well depth of 2500 meters) are taken, washed, and dried to remove mud and moisture. Then, the treated, dried rock cuttings are mixed with a two-component transparent epoxy resin (e.g., a mixture of EPON 828 resin and curing agent TPHDA) in a specific ratio. This mixture is placed in a vacuum chamber for degassing to eliminate air bubbles introduced by stirring. Afterward, the degassed mixture is injected into a circular mold of a specific size and transferred to a high-temperature, high-pressure reactor. Under set temperature and pressure conditions (e.g., 80 degrees Celsius and 20 MPa), the mixture undergoes a curing reaction, ultimately forming a transparent solid sheet approximately 25 mm in diameter and 5 mm thick—the pressed sample. This sample completely encapsulates the structure of the original rock cuttings within a rigid resin matrix.

[0028] Next, the prepared compressed samples were subjected to multispectral analysis. The samples were sequentially placed under three nondestructive testing devices for measurement.

[0029] The first step is to perform X-ray diffraction analysis. The sample is placed on the sample stage of the X-ray diffractometer. The equipment uses a copper target X-ray source, which, under specific voltage and current conditions, irradiates the sample surface with X-rays at continuously varying angles (e.g., from 5 degrees to 70 degrees). The detector collects the diffraction signals and generates a diffraction pattern. By matching and fitting the obtained diffraction pattern with a standard mineral database, the content of each mineral in the sample can be quantitatively calculated, for example, quartz content is 45%, and total clay mineral content is 30%. These results constitute mineral composition data.

[0030] The second step involves X-ray fluorescence surface scanning. The same pressed sample is moved to an X-ray fluorescence spectrometer. The equipment is equipped with a fine moving platform and an X-ray focusing probe. A fixed scanning step size (e.g., 0.5 mm) is set, and the probe scans the sample surface point by point. At each scanning point, X-rays excite the element at that point to produce characteristic X-ray fluorescence. The spectrometer analyzes the fluorescence energy spectrum to determine the content of various elements (such as Si, Ca, Al, Fe, etc.) at that point. Finally, the data from all scanning points are integrated to generate an elemental distribution map reflecting the two-dimensional distribution of each element on the sample surface, i.e., elemental distribution data.

[0031] The third step involves structured light 3D scanning. The sample is placed within the working area of ​​the structured light 3D scanner. The scanner projects a series of coded grating stripe patterns onto the sample surface, and a high-resolution camera simultaneously captures images of the stripes that are deformed by the sample surface morphology (such as pores, cracks, and particle protrusions). Through phase measurement and 3D reconstruction algorithms, the system calculates the 3D coordinates of each point on the sample surface, constructing a high-resolution (e.g., 50-micrometer dot pitch) 3D surface morphology model. This model clearly displays the microstructural features of the sample surface, such as pore opening, crack length, and orientation, constituting 3D morphology data.

[0032] Then, multi-source data fusion modeling is performed. The aforementioned three steps yielded three different types of data: minerals, elements, and morphology. Since all detections were based on the same compressed sample, and spatial alignment of the data was ensured through positioning markers, the data processing system first decoupled and mapped the overall mineral content information obtained from X-ray diffraction analysis onto each voxel in three-dimensional space according to a certain spatial distribution model (such as combining elemental distribution trends), generating a three-dimensional mineral distribution matrix. Simultaneously, the two-dimensional elemental distribution map obtained from X-ray fluorescence surface scanning was extended into a three-dimensional elemental distribution matrix through interpolation and extrapolation algorithms. Next, from the high-precision surface model obtained from structured light three-dimensional scanning, the spatial network structure of pores and fractures and their topological parameters were identified and extracted through image processing and geometric analysis algorithms. Finally, the three sets of data—mineral distribution matrix, elemental distribution matrix, and pore network structure—were fused and correlated in a unified three-dimensional coordinate system to generate an integrated three-dimensional digital rock cutting model that incorporates mineral phases, chemical element abundances, and pore / fracture geometric structure information.

[0033] Finally, a digital cuttings library is constructed. Metadata tags are added to the previously generated integrated 3D digital model, including the well name, well depth (2500 meters), geographic coordinates, and sample preparation and testing time for the cuttings sample. Then, the digital model with complete metadata is imported into a dedicated distributed cloud database. This database is indexed, allowing users to quickly retrieve and access data based on various criteria such as well depth, coordinates, mineral type, and elemental content range. At this point, a cuttings sample from a specific depth point has completed its transformation from a physical entity into a high-fidelity digital asset.

[0034] By repeatedly executing the aforementioned method to process all the cuttings samples to be analyzed in the well, a digital cuttings database covering the entire wellbore and containing rich geological information can be systematically constructed.

[0035] The beneficial effects provided by this embodiment include at least the following: by preparing physical rock cuttings into permanently preserved compressed samples and combining them with three non-destructive testing techniques—X-ray diffraction, X-ray fluorescence, and structured light—comprehensive and simultaneous acquisition of information on the minerals, elements, and pore structure of the rock cuttings is achieved. The integrated three-dimensional digital model generated by this method provides richer information dimensions and stronger spatial correlations than single techniques or destructive analysis. Linking the digital results with geological information and storing them in a database enables the long-term, non-destructive preservation and efficient reuse of rock cutting data, providing a high-value data foundation for subsequent geological research, reservoir evaluation, and engineering decision-making. This overcomes the shortcomings of traditional physical rock cutting libraries, such as easy weathering and limited information, as well as the high cost and difficulty in large-scale application of high-end scanning electron microscopy solutions.

[0036] In one possible implementation, mixing rock chips with transparent epoxy resin includes mixing rock chip particles with a particle size of 2-5 mm with transparent epoxy resin in a 1:3 ratio.

[0037] Among them, rock fragments with a particle size of 2-5 mm can refer to rock debris whose maximum size is within the range of 2 mm to 5 mm after screening. The 1:3 ratio can refer to the ratio of the mass or volume of rock fragments to the mass or volume of transparent epoxy resin in the mixing process being 1:3.

[0038] Continuing with the aforementioned embodiments, a key control parameter was added during the pretreatment of the raw rock fragments sample in the pressed sample preparation step. Specifically, after washing and drying, the rock fragments were sieved using a standard sieve, selecting particles with a diameter between 2 mm and 5 mm as raw materials. This particle size range was chosen to balance several requirements: the particles were large enough to retain representative mineral symbiotic structures and microcracks; at the same time, the particles were small enough to facilitate thorough mixing with the resin and to ensure a smooth distribution in the final sheet-like pressed sample, guaranteeing applicability for subsequent surface scanning detection. Then, a certain mass of the sieved rock fragments (e.g., 10 g) was accurately weighed, and a corresponding mass of transparent epoxy resin premix (e.g., 30 g) was weighed at a 1:3 mass ratio. Both were placed in a container and thoroughly stirred to ensure that the surface of each rock fragment particle was coated with resin, forming a homogeneous mixture. This fixed mixing ratio is optimized to ensure that the rock fragments are completely impregnated and encapsulated by the resin, and have sufficient transparency and mechanical strength after curing to facilitate observation, while also preventing the resin matrix from being too thick and excessively affecting the intensity and accuracy of X-ray diffraction and fluorescence signals.

[0039] The beneficial effects of this embodiment, based on the foregoing embodiments, are further defined as follows: by controlling the particle size of the rock fragments and the mixing ratio with the resin, the preparation process of the pressed sample is optimized. A suitable particle size ensures the effective preservation of original geological structural features (such as intermineral contact relationships and microcracks); a precise mixing ratio ensures that the sample has good optical transparency and physical strength while minimizing the interference of the resin matrix on subsequent non-destructive spectral analysis, thus laying a solid physical foundation for obtaining high-quality, high-fidelity multi-source detection data.

[0040] In one possible implementation, vacuum degassing and high-pressure curing are performed in a vacuum environment followed by degassing at 80 degrees Celsius and 20 MPa to form a transparent solid pressed sample with a hardness higher than Mohs 6.

[0041] The conditions of 80 degrees Celsius and 20 MPa refer to the specific temperature and pressure values ​​used in the curing process. A hardness higher than Mohs 6 means that the cured sample's resistance to scratches exceeds the standard of orthoclase (Mohs hardness 6), indicating that it has high surface hardness and wear resistance.

[0042] Continuing with the aforementioned embodiments, after the rock chips and epoxy resin are mixed uniformly in a specific ratio, the crucial curing and molding stage begins. First, the mixture is transferred to a vacuum chamber, and the pressure inside the chamber is evacuated to a vacuum of -0.1 MPa (i.e., below atmospheric pressure) and maintained for approximately 10 minutes. During this process, tiny air bubbles adsorbed within the mixture and on the surface of the rock chip particles are effectively removed under negative pressure. This is crucial for obtaining a transparent solid with no internal defects and optical uniformity. After degassing, the mixture is carefully injected into a cylindrical mold of predetermined dimensions while maintaining a vacuum or inert atmosphere.

[0043] The mold containing the mixture is then placed into an autoclave or flat vulcanizing machine equipped with heating and pressurization functions. The curing process parameters are set as follows: temperature 80 degrees Celsius, pressure applied to the mold 20 MPa. Under these conditions, the temperature and pressure are maintained for approximately 2 hours. The heating and pressurization process promotes a rapid and complete cross-linking and curing reaction of the epoxy resin. The temperature of 80 degrees Celsius ensures a sufficient reaction rate while avoiding the potential impact of excessively high temperatures on certain heat-sensitive minerals (such as some clay minerals) in the rock fragments. The high pressure of 20 MPa forces the resin to tightly encapsulate the rock fragment particles and further eliminates any remaining microbubbles, while simultaneously resulting in a dense structure in the cured sample.

[0044] After the aforementioned processing, the final demolded sample is the target pressed sample. This sample is transparent or translucent, with the encapsulated rock fragments clearly visible. Testing shows its surface hardness reaches at least 6.5 on the Mohs scale, exhibiting excellent scratch resistance. This ensures that the sample's observation surface is not easily scratched during subsequent handling, placement on the testing instrument's sample stage, and surface scanning, thus maintaining the original morphology of the testing area over a long period.

[0045] The beneficial effects of this embodiment, based on the aforementioned embodiments, are further defined as follows: by employing specific process conditions of vacuum degassing combined with 80°C / 20 MPa high-pressure curing, high optical quality and mechanical strength of the pressed sample are ensured. This process eliminates the interference of air bubbles on observation and detection signals, and the resulting hard surface effectively protects the original microstructure of the sample, enabling it to withstand the physical contact and operation of subsequent multiple non-destructive testing processes. This allows for long-term, multiple reuse of a single sample, greatly improving the practicality and economy of the method.

[0046] In one possible implementation, X-ray diffraction analysis of the pressed sample includes: using a copper target X-ray source to scan the pressed sample within a scanning angle range of 5 to 70 degrees to obtain quantitative mineral composition data.

[0047] Among them, the copper target X-ray source can refer to an X-ray tube that uses metallic copper as the anode target material, and the characteristic X-ray wavelength (Cu Kα) it produces is about 0.154 nanometers. The scanning angle range of 5 degrees to 70 degrees can refer to the scanning start angle and end angle (2θ angle) of the detector in the X-ray diffractometer relative to the incident X-ray beam.

[0048] Continuing with the aforementioned embodiments, when performing multispectral analysis on the prepared pressed samples, X-ray diffraction analysis is the primary step, and its parameter settings are crucial for accurate mineral identification and quantification. The pressed sample is placed stably in the center of the sample stage of the X-ray diffractometer. The instrument uses a copper target X-ray tube as the radiation source, and the operating voltage and current are set, for example, to 40 kV and 40 mA, respectively, to generate stable Cu Kα rays.

[0049] The scanning program was set to continuous scanning mode, with a scanning angle range from 5 degrees to 70 degrees. This range covers the main diffraction peak positions of most common rock-forming minerals (such as quartz, feldspar, calcite, and clay minerals). During the scanning process, the detector moved at a fixed angular velocity (e.g., 2 degrees per minute), synchronously recording the intensity of diffracted X-rays at different angles, and finally plotting an X-ray diffraction pattern with the diffraction angle (2θ) as the abscissa and the diffraction intensity as the ordinate.

[0050] After obtaining the raw spectra, they are processed using specialized analysis software. The software first performs preprocessing such as smoothing and background removal. Then, it uses a built-in mineral crystal structure database (such as the ICDD PDF-4+ database) to search and match diffraction peaks in the spectra, identifying all mineral phases contained in the sample. Next, a full-spectrum fitting technique (such as Rietveld refinement) is used to calculate the best fit between the crystal structure model of the mineral phase and the experimental spectra, quantitatively determining the weight percentage of each identified mineral in the sample. The error of this quantitative result is typically within ±2%. This specific information on mineral types and contents constitutes the quantitative mineral composition data required for subsequent data fusion.

[0051] The beneficial effect of this embodiment, based on the aforementioned embodiments, lies in the following: by specifying the use of a copper target X-ray source and conducting X-ray diffraction scanning within the range of 5-70 degrees, it ensures that the detection scheme can efficiently and accurately cover the main mineral types of interest in oil and gas exploration, and achieve reliable quantitative analysis. This provides an accurate mineralogical basis for digital rock cuttings models and is a key data source for lithological identification, provenance analysis, and reservoir evaluation.

[0052] In one possible implementation, X-ray fluorescence surface scanning of the pressed sample includes scanning the surface of the pressed sample in steps of 0.5 mm to obtain distribution data of multiple elements.

[0053] The 0.5 mm step size refers to the distance between the centers of two adjacent measurement points when the X-ray fluorescence spectrometer probe performs point-by-point measurements on the sample surface.

[0054] Continuing with the aforementioned embodiments, after completing the X-ray diffraction analysis, the same suppressed sample was transferred to an X-ray fluorescence spectrometer for elemental distribution scanning. The sample was fixed on a programmable two-dimensional moving platform. The instrument is equipped with a focusing X-ray tube and an energy-dispersive detector.

[0055] To achieve a balance between scanning resolution and efficiency, a scanning step size of 0.5 mm was set. This means the probe forms a regular grid of dots on the sample surface, with each dot having a side length of 0.5 mm. The scanning software controls the moving platform, allowing the probe to move precisely and sequentially directly above each grid dot. At each measurement point, the probe emits an X-ray beam that irradiates a tiny region (approximately 1 mm in diameter) on the sample surface, exciting the atoms within that region. The excited atoms release X-ray fluorescence with the characteristic energy of the element, which is received by the detector and forms an energy spectrum.

[0056] The system automatically analyzes the energy spectrum acquired at each measurement point, identifies the element types corresponding to the spectral peaks (typically detecting multiple elements from sodium to uranium), and calculates the relative abundance or intensity of that element at that point. By traversing all preset grid points, the system ultimately obtains multiple two-dimensional distribution maps, each corresponding to one element. Each pixel value in the map represents the abundance information of that element at that pixel location (corresponding to a scan point). This dataset constitutes the elemental distribution data, which visually reveals the spatial heterogeneity of different elements (such as Si for quartz, Ca for calcite, and Al for clay minerals) on the sample surface.

[0057] The beneficial effect of this embodiment, based on the aforementioned embodiments, is that by setting a scanning step size of 0.5 mm, high spatial resolution imaging of the elemental distribution on the surface of the pressed sample is achieved. This fine-scale elemental distribution map can not only help verify and refine the inference of mineral distribution, but also reveal information such as mineral zoning and diagenesis, greatly enriching the geochemical dimension of the digital rock fragment model and providing strong support for refined geological interpretation.

[0058] In one possible implementation, structured light 3D scanning of the pressed sample includes: scanning the surface of the pressed sample at a resolution of 50 micrometers to obtain 3D topographic data containing information on pores and cracks, and extracting the topological network of cracks with a length greater than 200 micrometers.

[0059] Here, 50 micrometers resolution can refer to the minimum distance between two points on the sample surface that a structured light 3D scanner can distinguish, or the average spacing between adjacent points in point cloud data. Cracks longer than 200 micrometers can refer to linear depressions identified as continuous in the sample surface morphology with an opening length exceeding 200 micrometers. Topological networks can refer to the graphical structure describing the spatial connectivity of pores or cracks, including nodes (such as pore volumes, crack intersections) and edges (such as throats, crack segments) and their connections.

[0060] Continuing with the aforementioned embodiments, in the final stage of multispectral imaging, a structured light 3D scanner is used to perform high-precision morphological measurements on the surface of the pressed sample. The scanner parameters are set to achieve a spatial resolution of 50 micrometers. This means that the reconstructed 3D model can clearly reproduce surface features larger than 50 micrometers.

[0061] The scanning process is automated. The instrument projects multiple sets of grating patterns with different phases onto the sample surface, which are simultaneously captured by a high-resolution camera. By solving the phase information, the system calculates the three-dimensional coordinates (X, Y, Z) of each measured point on the sample surface, generating dense point cloud data. Subsequently, the point cloud data is converted into a triangular mesh model, i.e., three-dimensional topographic data. This model realistically reproduces the microscopic undulations of the sample surface, including the protrusions of individual mineral grains, the boundaries between grains, and, more importantly, the opening morphology of various pores and cracks.

[0062] After obtaining the 3D mesh model, specialized image processing and geometric analysis algorithms are used to process the model. The algorithm first automatically identifies and segments pore and fracture regions based on surface curvature variations and depth information. Then, it analyzes the identified fracture features, calculating parameters such as the direction, length, and average aperture of each fracture. The system sets a length threshold (e.g., 200 micrometers), including only fractures exceeding this threshold in the subsequent topology network construction. For these valid fractures, the algorithm tracks their spatial extension trajectory, identifies fracture intersections and branch points, abstracts this information into nodes and connecting edges, and ultimately constructs a topology network describing the spatial connectivity of the fracture system. This set of data, containing high-precision surface morphology and fracture topology networks, is a key input for analyzing reservoir permeability and rock mechanical properties.

[0063] The beneficial effects of this embodiment, based on the aforementioned embodiments, are further defined as follows: by employing a 50-micron high-resolution morphology scan, it is possible to accurately capture micron-level pore and fracture features that significantly influence seepage and mechanical properties. Specifically, by automatically extracting fracture topology networks with lengths greater than 200 microns through an algorithm, complex surface geometric information is transformed into structured parameters usable for numerical simulation. This provides a directly accessible key data interface for subsequent engineering applications such as reservoir seepage simulation and fracturing capability evaluation, thereby enhancing the practical value of the digital cuttings library.

[0064] In one possible implementation, fusing mineral composition data, elemental distribution data, and three-dimensional morphology data to generate an integrated three-dimensional digital model includes: generating a mineral distribution matrix based on the mineral composition data, generating an elemental distribution matrix based on the elemental distribution data, extracting a pore network based on the three-dimensional morphology data, and generating a three-dimensional vector model based on the mineral distribution matrix, elemental distribution matrix, and pore network.

[0065] Among these, a mineral distribution matrix can refer to a three-dimensional array where each cell (voxel) stores the content or identification information of one or more minerals at that spatial location. An elemental distribution matrix can refer to a three-dimensional array where each cell stores the content information of one or more chemical elements at that spatial location. A pore network can refer to a simplified geometric model extracted from three-dimensional topographic data, consisting of pore spaces and connecting throats, representing seepage channels. A three-dimensional vector model can refer to a computer graphics representation that uses geometric primitives such as points, lines, and surfaces and their attributes to define three-dimensional objects; here, it specifically refers to a three-dimensional digital rock cutting model that integrates multi-attribute information.

[0066] Continuing with the aforementioned embodiments, after acquiring mineral composition data from X-ray diffraction, elemental distribution data from X-ray fluorescence surface scanning, and three-dimensional morphology data from structured light scanning, the core data fusion and modeling step is entered.

[0067] Because the three sets of data come from different sources and have different formats, spatial registration is first performed to ensure that they describe the same region of the same physical sample. The system uses positioning marks that are pre-made on the pressed sample or automatically identified during scanning to unify the three sets of data into the same three-dimensional Cartesian coordinate system.

[0068] Next, data transformation and generation are performed: 1. Generating a Mineral Distribution Matrix: X-ray diffraction provides quantitative results of the overall mineral composition of the sample, rather than a direct three-dimensional distribution. The system employs a spatial allocation algorithm based on elemental distribution constraints. The algorithm uses high-resolution elemental distribution data (e.g., distribution maps of elements such as Si, Ca, Al, and Fe) as prior knowledge, because different elemental contents are correlated with specific minerals (e.g., high-Si regions may correspond to quartz). The algorithm assigns the overall mineral content to each voxel of a high-resolution three-dimensional mesh at the same scale as the three-dimensional morphology model, according to the spatial weights provided by these elemental distributions, thereby generating a mineral distribution matrix where each voxel contains the type and estimated content of the main mineral at that location.

[0069] 2. Generating an elemental distribution matrix: X-ray fluorescence surface scanning provides a two-dimensional elemental distribution map. The system generates a three-dimensional elemental distribution matrix by appropriately extrapolating the two-dimensional scan data along a direction perpendicular to the scan plane (considering the assumptions of sample thickness and uniformity of elemental distribution) and filling it into a three-dimensional grid.

[0070] 3. Pore Network Extraction: As described above (corresponding to step 6), the spatial geometric structure of pores and cracks is extracted from the high-resolution 3D topographic data (triangular mesh model) using algorithms such as image segmentation and median transformation. This structure is then simplified into a network model consisting of interconnected spheres (representing pores) and cylinders (representing throats), i.e., the pore network. This network includes topological parameters such as pore size, throat radius, and connectivity.

[0071] Finally, fusion and model generation are performed. The mineral distribution matrix, element distribution matrix, and pore network model obtained in the above three steps are integrated. In the 3D visualization engine, the pore network model is used as the geometric skeleton, and mineral and element information is "attached" or "mapped" as attribute data to the corresponding spatial locations (or corresponding 3D mesh voxels) of the network model. This ultimately generates a 3D vector model that supports interactive operations. Users can arbitrarily cross-cut on this model, simultaneously query the mineral composition and elemental content at any point, and visualize the possible seepage paths of pore fluids. This model is the integrated 3D digital rock cuttings model, the core data asset of the digital rock cuttings library.

[0072] This embodiment, building upon the aforementioned embodiments, further defines a beneficial effect by clarifying a specific technical path for effectively fusing multi-source heterogeneous data into a unified three-dimensional model. By spatializing the overall mineral information, three-dimensionalizing the two-dimensional elemental information, and extracting structural networks from the morphology, it ultimately achieves a precise correlation and integrated expression of mineral phases, geochemical composition, and pore structure in three-dimensional space. This deeply integrated model transcends the limitations of a single information dimension, providing geologists and engineers with a powerful digital carrier capable of comprehensive analysis, numerical simulation, and collaborative decision-making, truly realizing seamless integration of geological information and engineering applications.

[0073] Corresponding to the above method embodiments, this specification also provides embodiments of a digital rock debris library construction device based on the combined use of pressed samples and multispectral analysis. Figure 2 This specification illustrates a schematic diagram of a digital rock debris library construction device based on the combined use of compressed samples and multispectral analysis, according to one embodiment of this specification. Figure 2 As shown, the device includes: The sample pressing module 201 is configured to mix rock fragments with transparent epoxy resin and then perform vacuum degassing and high-pressure curing to form a pressed sample. The data scanning module 202 is configured to perform X-ray diffraction analysis, X-ray fluorescence surface scanning and structured light three-dimensional scanning on the pressed sample to obtain mineral composition data, elemental distribution data and three-dimensional morphology data, respectively. The digital model module 203 is configured to fuse mineral composition data, elemental distribution data and three-dimensional morphology data to generate an integrated three-dimensional digital model containing mineral, elemental and pore structure information. The data storage module 204 is configured to associate the integrated three-dimensional digital model with the corresponding well depth and coordinate information and store it in the database.

[0074] In one possible implementation, mixing rock chips with transparent epoxy resin includes mixing rock chip particles with a particle size of 2-5 mm with transparent epoxy resin in a 1:3 ratio.

[0075] In one possible implementation, vacuum degassing and high-pressure curing are performed in a vacuum environment followed by degassing at 80 degrees Celsius and 20 MPa to form a transparent solid pressed sample with a hardness higher than Mohs 6.

[0076] In one possible implementation, X-ray diffraction analysis of the pressed sample includes: using a copper target X-ray source to scan the pressed sample within a scanning angle range of 5 to 70 degrees to obtain quantitative mineral composition data.

[0077] In one possible implementation, X-ray fluorescence surface scanning of the pressed sample includes scanning the surface of the pressed sample in steps of 0.5 mm to obtain distribution data of multiple elements.

[0078] In one possible implementation, structured light 3D scanning of the pressed sample includes: scanning the surface of the pressed sample at a resolution of 50 micrometers to obtain 3D topographic data containing information on pores and cracks, and extracting the topological network of cracks with a length greater than 200 micrometers.

[0079] In one possible implementation, fusing mineral composition data, elemental distribution data, and three-dimensional morphology data to generate an integrated three-dimensional digital model includes: generating a mineral distribution matrix based on the mineral composition data, generating an elemental distribution matrix based on the elemental distribution data, extracting a pore network based on the three-dimensional morphology data, and generating a three-dimensional vector model based on the mineral distribution matrix, elemental distribution matrix, and pore network.

[0080] The above is a schematic scheme of a digital cuttings library construction device based on the combined use of pressed samples and multispectral imaging in this embodiment. It should be noted that the technical solution of this digital cuttings library construction device based on the combined use of pressed samples and multispectral imaging belongs to the same concept as the aforementioned digital cuttings library construction method based on the combined use of pressed samples and multispectral imaging. Details not described in detail in the technical solution of the digital cuttings library construction device based on the combined use of pressed samples and multispectral imaging can be found in the description of the aforementioned digital cuttings library construction method based on the combined use of pressed samples and multispectral imaging.

[0081] Figure 3 A structural block diagram of a computing device 300 according to one embodiment of this specification is shown. The components of the computing device 300 include, but are not limited to, a memory 310 and a processor 320. The processor 320 is connected to the memory 310 via a bus 330, and a database 350 is used to store data.

[0082] The computing device 300 also includes an access device 340, which enables the computing device 300 to communicate via one or more networks 360. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 340 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0083] In one embodiment of this specification, the aforementioned components of the computing device 300 and Figure 3 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 3 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0084] The computing device 300 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 300 can also be a mobile or stationary server.

[0085] The processor 320 executes computer-executable instructions, which, when executed by the processor, implement the steps of the above-described method for constructing a digital cuttings library based on the combined use of pressed samples and multispectral imaging. The above is a schematic representation of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above-described method for constructing a digital cuttings library based on the combined use of pressed samples and multispectral imaging belong to the same concept. Details not described in detail in the technical solution of the computing device can be found in the description of the technical solution of the above-described method for constructing a digital cuttings library based on the combined use of pressed samples and multispectral imaging.

[0086] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described method for constructing a digital rock debris library based on the combination of compressed samples and multispectral analysis.

[0087] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium belongs to the same concept as the technical solution of the above-described method for constructing a digital rock debris library based on the combined use of pressed samples and multispectral imaging. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the above-described method for constructing a digital rock debris library based on the combined use of pressed samples and multispectral imaging.

[0088] An embodiment of this specification also provides a computer program, wherein when the computer program is executed in a computer, it causes the computer to perform the steps of the above-described method for constructing a digital rock debris library based on the combination of compressed samples and multispectral analysis.

[0089] The above is an illustrative scheme of a computer program according to this embodiment. It should be noted that the technical solution of this computer program belongs to the same concept as the above-described method for constructing a digital rock debris library based on the combined use of compressed samples and multispectral imaging. For details not described in detail in the technical solution of the computer program, please refer to the description of the above-described method for constructing a digital rock debris library based on the combined use of compressed samples and multispectral imaging.

[0090] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0091] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0092] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0093] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0094] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A method for constructing a digital rock debris library based on the combined use of compressed samples and multispectral analysis, characterized in that, include: Rock fragments were mixed with transparent epoxy resin and then subjected to vacuum degassing and high-pressure curing to form pressed samples. X-ray diffraction analysis, X-ray fluorescence surface scanning and structured light three-dimensional scanning were performed on the pressed sample to obtain mineral composition data, elemental distribution data and three-dimensional morphology data, respectively. The mineral composition data, the element distribution data, and the three-dimensional morphology data are fused to generate an integrated three-dimensional digital model containing mineral, element, and pore structure information. The integrated three-dimensional digital model is associated with the corresponding well depth and coordinate information and stored in the database.

2. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, Mixing rock chips with transparent epoxy resin includes mixing rock chip particles with a particle size of 2-5 mm with the transparent epoxy resin at a ratio of 1:

3.

3. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, The vacuum degassing and high-pressure curing process involves degassing in a vacuum environment and then performing the process at 80 degrees Celsius and 20 MPa to form a transparent solid pressed sample with a hardness higher than Mohs 6.

4. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, The X-ray diffraction analysis of the pressed sample includes: using a copper target X-ray source, scanning the pressed sample within a scanning angle range of 5 degrees to 70 degrees to obtain quantitative mineral composition data.

5. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, The X-ray fluorescence surface scanning of the pressed sample includes scanning the surface of the pressed sample in steps of 0.5 mm to obtain the distribution data of multiple elements.

6. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, The structured light three-dimensional scanning of the pressed sample includes: scanning the surface of the pressed sample at a resolution of 50 micrometers to obtain three-dimensional morphological data containing information on pores and cracks, and extracting the topological network of cracks with a length greater than 200 micrometers.

7. The method for constructing a digital rock debris library based on compressed samples and multispectral analysis according to claim 1, characterized in that, The process of fusing the mineral composition data, the elemental distribution data, and the three-dimensional morphology data to generate an integrated three-dimensional digital model includes: generating a mineral distribution matrix based on the mineral composition data, generating an elemental distribution matrix based on the elemental distribution data, extracting a pore network based on the three-dimensional morphology data, and generating a three-dimensional vector model based on the mineral distribution matrix, the elemental distribution matrix, and the pore network.

8. A device for constructing a digital rock debris library based on compressed samples and multispectral analysis, characterized in that, include: The sample pressing module is configured to mix rock fragments with transparent epoxy resin and then perform vacuum degassing and high-pressure curing to form pressed samples. The data scanning module is configured to perform X-ray diffraction analysis, X-ray fluorescence surface scanning and structured light three-dimensional scanning on the pressed sample to obtain mineral composition data, elemental distribution data and three-dimensional morphology data, respectively. The digital model module is configured to fuse the mineral composition data, the element distribution data, and the three-dimensional morphology data to generate an integrated three-dimensional digital model containing mineral, element, and pore structure information. The data storage module is configured to associate the integrated three-dimensional digital model with the corresponding well depth and coordinate information, and store it in the database.

9. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the digital rock debris library construction method based on the combined use of compressed samples and multispectral analysis as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the digital rock debris library construction method based on the combined use of pressed samples and multispectral analysis as described in any one of claims 1 to 7.

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