2105 results about "Porosity" patented technology

The invention provides an engineering construction defect automatic detection and classification method based on deep learning, and the method comprises the steps: obtaining a welding seam surface image through the shooting of an unmanned plane, and carrying out the denoising and illumination normalization processing of the welding seam surface image, and obtaining a standardized image; welding seam surface texture features are extracted from the standardized image, a convolutional neural network is adopted to analyze the spatial distribution characteristics of textures, and vectorization processing is carried out to obtain texture feature vectors; segmenting a weld surface corresponding to abnormal region distribution by adopting a region growing algorithm, and analyzing pore and weld discontinuity in combination with the texture feature vector to obtain a defect candidate region; performing threshold division on the sizes and the numbers of the defects according to the defect types and the feature vectors of the candidate regions to obtain a severity grading result of each type of defects; and severity features are extracted from a grading result, and a Bayesian network is adopted to fuse texture feature vectors and defect type labels to obtain a welding quality evaluation score.

The invention relates to the technical field of model construction, and discloses a neural network-based frozen soil unfrozen water content detection model construction method and system. The method comprises the following steps: carrying out segmented sampling test on a clay sample in a temperature interval of 0 DEG C to-20 DEG C to obtain a multi-dimensional original data set, and carrying out standardization and principal component analysis on the data set to obtain a standardized feature vector; and performing three-stage classification marking on the feature vectors to obtain a training data matrix. A deep neural network is adopted to carry out five-fold cross validation training, and a prediction model of three hidden layers is constructed. And performing correction calculation on model output according to soil mineral composition and porosity parameters, and finally identifying an abnormal value through root-mean-square error analysis and a three-time standard deviation principle to obtain a standardized prediction result. According to the method, the mapping relation between the thermal parameters and the unfrozen water content is established, correction is carried out in combination with the soil body characteristic parameters, and the technical problem that the prediction precision of the unfrozen water content is not high in the prior art can be solved.

The present disclosure relates to a method of using a metal specimen block having a porous region for a component. A method of coupling a metal sample block (200) to a component (202) may include additive manufacturing a metal sample block (200) having a first porous region (300A) having a first porosity and a second porous region (300B) having a second porosity different from the first porosity. A metal specimen block (200) is positioned in a specimen block opening (204) in a body (206) of the component (202). The metallic sample block (200) may be infiltrated with a braze material (310) to couple the metallic sample block (200) in a sample block opening (204) in the body (206). The one or more brazing materials (310) are infiltrated into at least one of the first porous region (300A) and the second porous region (300B) based at least on a characteristic of the first porosity and at least on a characteristic of the second porosity. The cured braze material (310) includes different segments having different physical properties based on different porosities and / or different braze materials.

A component includes a dense base region, a dense replacement region and an additively manufactured (AM) porous region between the dense base region and the dense replacement region. The porous region has a porosity between 2% to 50% open space volume to total volume of the AM porous region. The porous region can be printed onto the base region or the replacement region. A braze material couples the base region, the porous region and the replacement region together, and infiltrates into the porous region based at least on a characteristic of the porosity. The porous region reduces stress at a joint between the dense regions and can be customized to create different physical characteristic(s) than just those of the base and replacement regions.

A component includes a body and an additively manufactured (AM) metal coupon that includes at least one first porous region having a first porosity and may include any number of second porous regions having a second porosity different than the first porosity. A braze material couples the metal coupon in a coupon opening in the body. The braze material infiltrates into at least one of the first porous region based at least on a characteristic of the first porosity or any second porous region based at least on a characteristic of the second porosity. The different porosities can be customized to provide the first porous region and the second porous region with the braze material therein with different physical characteristic(s).

The invention belongs to the technical field of oil and gas production and development, and discloses a sand production pressure difference and sand production quantity quantitative prediction method suitable for a high-temperature and high-pressure sandstone reservoir, which comprises the following steps: calculating static rock mechanical parameters of a target well; predicting initial crustal stress; establishing a porosity and permeability dynamic evolution model; establishing a three-dimensional finite element model; establishing a seepage stress coupling transient nonlinear finite element equation; applying well bottom pressure drop to simulate production, and determining sand production pressure difference; and establishing a sand production rate prediction model, and quantitatively predicting the sand production rate. According to the method, factors such as pore permeability stress, temperature change and water content influencing rock strength are comprehensively considered, a three-dimensional finite element model is established, a seepage stress coupling finite element equation and solving steps are established based on a reservoir elastic-plastic consolidation theory, critical plastic strain is introduced to quantitatively characterize the sand production risk, a sand production prediction model is established, and the rock strength is predicted. And finally, quantitative and accurate calculation and scientific pressure control of the critical sand production pressure difference and the sand production amount are realized.

The invention relates to a metal sample block with a porous area for a component and the component with the metal sample block. A component (202) includes a body (206) and an additive manufactured (AM) metal sample block (200) that includes at least one first porous region (300A) having a first porosity and can include any number of second porous regions (300B) having a second porosity different from the first porosity. A braze material (310) couples the metallic sample block (200) in a sample block opening (204) in the body (206). The braze material (310) is infiltrated into at least one of the first porous region (300A) and any second porous region (300B) based at least on a characteristic of the first porosity and at least on a characteristic of the second porosity. Different porosities can be tailored to provide different physical characteristics for the first porous region (300A) and the second porous region (300B) having the braze material (310) therein.

The invention relates to the technical field of petroleum and natural gas engineering, and discloses an oil and gas reservoir optimized mining method based on multi-modal data, which comprises the following steps: constructing an oil and gas reservoir multi-modal data acquisition system, seismic wave field data, logging interpretation data, production dynamic data, micro-seismic monitoring data, underground temperature and pressure time sequence data and shaft structure parameter data are obtained through the acquisition system; and performing space-time alignment processing on the acquired multi-modal data, establishing a unified geological coordinate system and a time reference, and eliminating data isomerism caused by different acquisition frequencies and spatial resolutions. A six-dimensional heterogeneous data acquisition system covering a seismic wave field, well logging interpretation, production dynamics, micro-seismic monitoring, an underground temperature and pressure time sequence and shaft structure parameters is constructed, so that the depiction precision of a reservoir porosity field, a permeability field, a saturation field and a pressure field is essentially improved.

The invention provides a reservoir physical property parameter pre-stack seismic inversion method based on resistivity logging constraint. The method comprises the following steps: cutting observation data and depth; normalizing the seismic data, the resistivity data and the travel time to form network input; constructing a neural network framework, substituting the obtained porosity and saturation into an elastic rock physical model, and calculating to obtain an elastic parameter; the elastic parameters are substituted into a zoeppritz equation, and an underground reflection coefficient is obtained through calculation; generating a Ricker wavelet, and performing convolution calculation on the Ricker wavelet and the reflection coefficient to obtain predicted pre-stack seismic data; the porosity and the saturation are substituted into an Archie formula, and the predicted resistivity is obtained through calculation; constructing a target function; automatic differentiation is carried out, network parameters are updated, and then network output porosity and saturation are optimized. Reservoir parameter inversion driven by physical information is realized, and an intelligent scheme is provided for reservoir parameter prediction and evaluation in oil-gas exploration and development.

The invention discloses a preparation method of a ceramic membrane with efficient separation and catalysis functions as well as a product prepared by the preparation method and application of the ceramic membrane. The preparation method comprises the following steps: preparing a ceramic membrane support body by taking large-particle-size ceramic particles as a raw material, and preparing a transition layer by taking transition metal oxide nanofibers as a raw material by adopting a dip coating method; small-particle-size ceramic particles are used as raw materials to prepare a separation membrane layer by adopting a dip-coating method, and the ceramic membrane with a sandwich structure is formed through one-step co-firing. The transition layer with high porosity and specific surface area is formed by adopting the transition metal oxide nanofibers, so that the number of catalytic active sites and the permeation flux are improved; small-particle-size ceramic particles are adopted to form a separation membrane layer with uniform pore size distribution and a flat membrane surface, so that the separation efficiency of particulate matters and organic matters in water is improved, the accumulation of the particulate matters and the organic matters on the membrane surface is reduced, and meanwhile, the particulate matters and the organic matters in water are prevented from covering active sites of the catalytic ceramic membrane; therefore, the separation efficiency and the catalytic degradation efficiency of the ceramic membrane are synchronously improved.

The invention provides a hot dry rock terrestrial heat extraction method capable of efficiently adapting to complex heat storage conditions. The method comprises the steps that a heat-fluid-solid coupling relation in the terrestrial heat exploitation process is established, a dynamic porosity and permeability model is established based on the heat-fluid-solid coupling relation, and a terrestrial heat exploitation model is established based on the porosity and permeability model. According to the method, the heat extraction efficiency and the accumulated heat are remarkably improved, the heat competition effect between the production wells is reduced, the service life of the production wells is prolonged, the mining requirements under the complex geological conditions are met, the prediction precision of the heat-fluid-solid model is improved by dynamically adjusting the reservoir characteristics such as porosity and permeability, and the mining efficiency is improved. The problems of high thermal competition, inaccurate prediction and low mining efficiency in the prior art are solved, and a sustainable optimization scheme with high economical efficiency is provided for geothermal exploitation of the hot dry rock.

The invention discloses a negative carbon filling mining method for a gangue high-porosity material, and relates to the technical field of CO2 storage and filling mining, which comprises the following steps: spraying a rapid cementing material while blanking a gangue bulk material, forming a high-porosity filling body in a goaf, continuously injecting liquid CO2 into the closed high-porosity filling body through a pipeline, and filling the high-porosity filling body into a high-porosity filling body. The underground efficient sealing of CO2 is realized; the method is simple in design, the filling technology and CO2 storage are combined, efficient mining and filling are achieved, coal resource mining is not affected, the mine green mining and negative carbon filling construction process is promoted, a new concept of carbon storage is provided, wide application and research significance is achieved, and compared with a solid filling mining method, the method has the advantage that the method has a wide application prospect. And the gangue is fixed by using the rapid binding material to form a high-porosity material with bearing performance, so that the cost of a filling mining technology is reduced, and the original tamping process is simplified.

The invention provides a method for detecting the porosity of ores in a dump leaching process, and belongs to the technical field of detection of the porosity of the ores. The method comprises the following steps: taking a dump leaching ore body, screening, uniformly mixing, splitting, putting into a dump leaching column to obtain the volume of a sample subjected to splitting in the dump leaching column, then performing fine grinding, putting into the dump leaching column to obtain the volume of the sample subjected to fine grinding in the dump leaching column, and then performing image analysis on the sample subjected to fine grinding to obtain the pore volume among sample particles subjected to fine grinding. And finally, converting the three volumes to obtain the porosity of the heap-leached ore. Through screening treatment, the sample representativeness is effectively improved; the ore before superfine grinding and after superfine grinding is introduced into a dump leaching column, the sampling uniformity is controlled, and the accuracy and stability of data are improved through the in-pile process under the same test column; an image analysis algorithm is introduced, and meanwhile, a correction coefficient is introduced, so that small pores among particles are precisely measured and calculated. The method is simple in process and convenient to operate, and the ore porosity can be rapidly and accurately measured and calculated.

The invention relates to a shale gas multi-layer stacked reservoir dessert evaluation and separate layer fracturing decision-making method, and belongs to the technical field of oil-gas field development, and the method comprises the following steps: calculating porosity, adsorbed gas content, organic carbon content and vitrinite reflectance geological parameters; calculating brittleness index and fracture toughness engineering parameters; carrying out normalization processing and weight distribution by adopting a CRITIC weight method, constructing a geological-engineering comprehensive evaluation model, and dividing four types of sweet spot areas; through a mixed method of main parameter priority and abnormal value verification, preferentially analyzing interlayer gradients of high-weight parameters, and performing local fine verification on abnormal abrupt change of low-weight parameters based on a 3 sigma principle; and in combination with a rigid-flexible layering model, a fracturing layering strategy is dynamically decided, and the complexity of the fracture network is optimized. According to the method, the reservoir identification precision is improved through multi-parameter fusion evaluation, the fracturing efficiency is enhanced through dynamic hierarchical decision, the development cost is finally reduced, and technical support is provided for efficient development of shale gas.

The invention provides a method for detecting the porosity of in-situ dump-leached ore, and belongs to the technical field of ore porosity detection. The method comprises the following steps: taking an ore body on site, preparing a filling agent, performing vacuum gradient impregnation, curing, dissolving and separating the ore to obtain a pore model; melting and softening the pore model to obtain the pore volume in the ore, and finally obtaining the porosity of the ore; wherein nano SiO2 is added into the filler resin, and permeation of tiny pores is guaranteed based on the size effect and the interface optimization effect of a nano material; and through vacuum gradient impregnation, sufficient permeation of tiny pores is further ensured. According to the detection method, the limitation of a drainage method on ore pores containing water-soluble minerals is avoided; the problems that ore samples need to be collected and taken back to a laboratory to be detected in a mercury injection method, a gas adsorption method and the like, the ore body structure is damaged, and consumed time is long are solved. Detection can be carried out on site, ore permeability parameters are provided for the in-situ dump leaching process, and a real-time basis is provided for flow selection.

The invention relates to the technical field of honeycomb ceramic materials, in particular to a cordierite honeycomb ceramic material with low heat capacity and high specific surface area and a preparation method thereof. The pug comprises an inorganic solid component, an organic component and water, the inorganic solid component comprises narrow-particle-size-distribution spherical magnesium hydroxide, spherical aluminum hydroxide and spherical fused silicon dioxide; the particle size D50 of the narrow-particle-size-distribution spherical magnesium hydroxide powder is 0.1-2 microns, and the particle size D97 is smaller than or equal to 20 microns; the particle size D50 of the spherical aluminum hydroxide powder is 1-6 [mu] m, and the particle size D97 is less than or equal to 20 [mu] m; the particle size D50 of the spherical fused silica powder is 6-12 [mu] m, the particle size D97 is less than or equal to 20 [mu] m, and the sphericity is greater than or equal to 98%. The method is low in extrusion pressure, the obtained material is high in pore density, meanwhile, high porosity can be achieved without adding a pore-forming agent, and the ultra-thin wall is achieved; the composite material can be applied to various requirements of low heat capacity and high specific surface area.

The invention relates to a reservoir porosity and permeability prediction method based on a dynamic committee integration model, and the method comprises the following steps: obtaining an original data set which comprises shale content, porosity, permeability, GR, AC, CNL, DEN, RT, RXO, SP, CALC, CALI, depth and lithologic labels; performing data enhancement on the original data set; determining main control factors influencing the porosity and the permeability; constructing a dynamic committee integration model; inputting the main control factors into a dynamic committee integration model; and utilizing the trained dynamic committee integration model to respectively predict the porosity and the permeability. According to the method, the logging data is processed by adopting a machine learning method, reservoir parameters can be efficiently and accurately predicted, and favorable support can be provided for oil-gas exploration and development; the dynamic committee integrated model constructed by the invention can dynamically adjust the weight of each model according to different geological conditions and data features, can more flexibly adapt to the geological condition of a research area compared with a single model, and improves the prediction precision and generalization of the model.

The invention relates to the technical field of oil exploration, and discloses a rock mechanical parameter logging intelligent evaluation method considering continental facies shale fabric characteristics. The method comprises the following steps: 1, dividing shale lithofacies, identifying and determining the bedding development thickness of a sample through an optical microscope, determining a granularity experiment of the sample through granularity analysis, and forming mineral composition and bedding factor lithofacies division; 2, constructing a typical logging facies based on a rock electricity response relationship, and dividing the imaging logging facies of the research area according to natural gamma curves of conventional logging and imaging logging, core deposition structure characteristics and imaging logging image characteristics; 3, testing the longitudinal and transverse wave velocities and the porosity of different shale lithofacies, and calculating the dynamic elastic modulus and the Poisson's ratio. Through fine division and description, the method for accurately evaluating the bedding development condition, the particle size characteristics and the mineral components of the shale sample is provided, the testing time is short, the cost is low, and accurate evaluation of shale can be achieved.

The invention discloses a rock core porosity testing device and method, and relates to the technical field of rock porosity testing devices.The rock core porosity testing device comprises a high-temperature and high-pressure regulator, magnetic fluid particles are injected into a to-be-tested rock core sample under the cooperation of a rock core detection auxiliary assembly and a porosity dynamic detection assembly, and the porosity of the to-be-tested rock core sample is measured through the high-temperature and high-pressure regulator; a matrix type permanent magnet set is used for providing a basic magnetic field, fine adjustment is carried out through an electromagnetic coil control structure, controllable and flexible distribution of the magnetic fluid particles is promoted, then the neutron detector evaluates the porosity by detecting neutron signals in the rock core, the performance and reliability of the rock core porosity testing device in the actual use process are improved, and the test efficiency is improved. According to the invention, the accuracy of the test result is ensured, the core porosity test efficiency is improved, the X-ray scanning end forming multi-direction adjustment moves along the track of the guide rail, the core sample to be tested can be subjected to X-ray scanning from different angles, and the accuracy of the core porosity test is effectively improved.

The invention relates to the field of digital core modeling, in particular to a stomatal basalt three-dimensional digital core reconstruction method, which comprises the following steps: extracting target characteristic parameters from CT (Computed Tomography) scanning gray volume data of a stomatal basalt sample, the target characteristic parameters comprising porosity, cluster number, cluster size statistics, spatial uniformity index and simplified compactness; generating an initial three-dimensional digital core model according to the target characteristic parameters; carrying out iterative optimization on the initial three-dimensional digital core model by utilizing a self-adaptive Markov chain-Monte Carlo algorithm so as to enable cluster features of the optimized three-dimensional digital core model to approach target feature parameters; and performing curvature smoothing post-processing on the optimized three-dimensional digital core model to obtain the pore basalt three-dimensional digital core model. The model not only is highly matched with real pore basalt in the aspect of macroscopic statistical characteristics, but also shows natural and smooth curved surface characteristics in the aspect of microscopic pore boundary morphology, and provides a reliable digital basis for subsequent rock physical property analysis.

The invention discloses a mining-induced fractured rock mass flow state transition characterization method based on a grouting filling rate. The method comprises the following steps: defining a nonlinear seepage factor; the quantitative change rule of the porosity of the fractured rock mass along with the filling rate in the grouting process is calculated; correcting the nonlinear seepage factor to obtain a corrected nonlinear seepage factor; performing derivation integration on the corrected nonlinear seepage factors, constructing a judgment index model of the flow state transition of the mining-induced fractured rock mass based on the grouting filling rate, and obtaining nonlinear seepage characteristics of fluid; constructing a mining-induced fractured rock mass flow state transition judgment index based on the grouting filling rate according to the nonlinear seepage characteristics of the fluid; and judging the flow state transition of the mining-induced fractured rock mass in the grouting process according to data measured in engineering practice based on the mining-induced fractured rock mass flow state transition judgment index. According to the method, the flow state transition can be accurately identified in the grouting process, so that reasonable grouting parameters are determined, the grouting engineering design is guided, and the grouting effect is ensured.

The invention discloses a drilling construction intelligent decision support and risk early warning method, device and equipment, and the method comprises the steps: collecting drilling sound wave response data, carrying out harmonic analysis to recognize a reservoir resonance node, and constructing a reservoir energy conduction network; a fluctuation propagation path is tracked based on an energy conduction network, and a construction risk area is identified through stress wave spectrum features; porosity and permeability data are extracted for phase difference analysis, a seepage-construction mismatch factor is generated, and a construction optimization window is actively generated; constructing a geological potential energy gradient field to determine an overflow influence range, and performing tensor coupling on multi-dimensional risk factors to generate a three-dimensional construction decision matrix; an optimal construction scheme is generated through energy minimization and risk-efficiency dynamic balance processing; construction parameter response changes are monitored in real time, abnormal parameter combination symptoms are recognized, a grading risk early warning instruction is generated, and intelligent decision support and risk early warning of drilling construction are achieved.

Example computer-implemented methods, media, and systems for identification and characterization of geologic features in carbonate reservoir are disclosed. One example computer-implemented method includes obtaining multiple core sample images of a carbonate reservoir. The multiple core sample images are labeled using multiple feature classes, where the multiple feature classes include at least one of a vug or fracture. Multiple image patches are generated using the labeled plurality of core sample images. A machine learning model is applied to the multiple image patches to identify one or more vugs or fractures in the multiple core sample images. At least one of porosity or permeability of the carbonate reservoir is predicted using the identified one or more vugs or fractures in the multiple core sample images.

The invention belongs to the technical field of low-temperature co-fired ceramics, and particularly relates to a high-density and high-strength LTCC (Low Temperature Co-fired Ceramic) raw ceramic chip as well as a preparation method and application thereof. The preparation method comprises the steps that stacking phase powder and filling phase powder in raw materials are fully mixed and then subjected to tape casting, the equivalent particle size ratio of the stacking phase powder to the filling phase powder is 1: (0.4-0.8), and the volume ratio of the stacking phase powder to the filling phase powder is 1: (0.15-0.45). The high-density and high-strength LTCC raw ceramic chip is used for preparing a low-temperature co-fired ceramic substrate. According to the technical scheme provided by the invention, the raw ceramic chip raw materials can be tightly arranged after being fully mixed through the inorganic powder with different particle sizes and matching the dosage ratio of the inorganic powder to the raw ceramic chip raw materials, and low porosity in the sintered substrate is realized on the basis of not changing the substrate raw material composition or crystal whiskers; and therefore, the bending strength is improved, and other properties are not influenced.

The invention relates to a preparation method of a multi-porosity gradient multi-layer dry method thick electrode, which comprises the following steps of: stirring and mixing raw materials under the condition that the temperature is less than or equal to 18 DEG C to obtain a premix; quickly shearing the premix and raising the temperature to be less than or equal to 120 DEG C to obtain fiberized powder; the powder is subjected to one-time double-roller hot pressing to form a film continuously, the formed film continuously passes through double rollers and hot pressing to be thinned and then is rolled, multiple layers of films are obtained, and each layer of film has different porosity; the multiple layers of diaphragms with different porosities and the current collector are subjected to continuous double-sided lamination through double-roller hot pressing; the temperature of the double rollers is controlled to be smaller than or equal to 180 DEG C, the pressure of the double rollers is controlled to be 10-200 T, the laminating speed is controlled to be 1-10 m / min, the gap of the double rollers is controlled to be smaller than or equal to 1000 microns, and the multi-layer dry-method thick electrode which is composed of multiple layers of membranes is obtained after rolling, the compaction density of each layer of membrane is different, and the material proportion of each layer of membrane is the same; the method has the advantages that only the compaction density of the pole piece needs to be regulated and controlled, the material ratio does not need to be adjusted, and the interface property is more stable after multiple times of film forming.

The invention discloses a buried hill core porosity calculation method based on a high-precision repair CT image, and the method comprises the steps: S1, obtaining a micron CT three-dimensional gray image of a buried hill fracture reservoir plunger sample in a research region, and obtaining a three-dimensional digital core model of the buried hill fracture reservoir plunger sample based on the micron CT three-dimensional gray image; s2, obtaining nanometer CT three-dimensional grayscale images of the sub-samples at different positions; s3, establishing a buried hill fractured reservoir core image database under different resolutions, learning and training the image through a residual network model to obtain a high-precision repaired micron CT image, and simulating and calculating the porosity through threshold segmentation; and S4, determining the actually measured porosity of the buried hill crack sample through an indoor experiment, and comparing the actually measured porosity with the simulated calculation porosity. According to the method, the pixel boundary contact information of the micron CT image is recovered through the deep residual network model, the restoration quality of the image is improved, and the simulated porosity is closer to an actual value.

The invention discloses a high-pressure die-casting part mechanical property prediction method, device, equipment and medium, and relates to the field of die-casting material performance prediction.The method comprises the steps that a finite element model data file and a porosity result data file are extracted based on a die flow simulation analysis result of a target die-casting part, constructing a finite element mesh model for receiving porosity data; performing porosity data mapping based on the extracted data file and the constructed finite element mesh model, and constructing a finite element simulation mesh model with porosity characteristics; establishing a representative volume element model and carrying out homogenization treatment to obtain a mechanical property parameter card with a porosity material; on the basis of the finite element simulation grid model and the mechanical property parameter card, finite element simulation analysis of the anisotropic mechanical behavior casting with the porosity characteristic is conducted on the target die-casting part to obtain the mechanical property, rapid response can be conducted on the mechanical property of the die-casting part, and the prediction efficiency of the mechanical property of the die-casting part is improved.

Disclosed in the present invention is a rock porosity prediction method based on the inversion of few-shot while-drilling data. While-drilling parameters of a drilling rig during a laboratory or on-site drilling process are collected, wherein the while-drilling parameters comprise parameters such as torque M, thrust force F, rotation speed N, penetration rate V, drill pipe amplitude A and vibration acceleration a; different types of while-drilling parameter data which have been subjected to multiple instances of denoising processing are inputted into a BP-GA model for outlier removal, data augmentation and iterative calculation, so as to form a new while-drilling data set; and while-drilling parameter time-frequency domain feature maps of rocks having different porosities are inputted into a VG-CNN prediction model, an inversion model between while-drilling parameter time-frequency domain features and the porosities is obtained by means of training and learning, and finally inversion prediction is performed on the rock porosities on the basis of on-site real-time while-drilling parameters. The present method enables fast, accurate and quantitative inversion and prediction of rock porosities on the basis of a small amount of borehole while-drilling data.

The invention discloses a sampling device and method for detecting the oil content of oil sand ore based on hyperspectrum, and relates to the technical field of oil sand ore sampling. Comprising a mounting base, a drilling barrel and a drill bit, the mounting base, the drilling barrel and the drill bit are sequentially in threaded connection in the direction from top to bottom, the mounting base is rotationally connected with a connecting piece located in the drilling barrel, and the lower side of the connecting piece is in threaded connection with a middle barrel; a guide assembly for reducing the moving resistance of the oil sand sample is arranged on the connecting piece; the guide assembly comprises two inner half cylinders which are symmetrically distributed and a sample containing cylinder. An oil sand sample entering the space between the two inner half cylinders is gradually wrapped by the sample containing cylinder, and the oil sand sample is isolated from the inner half cylinders, so that the oil sand sample does not make direct contact with the inner half cylinders, friction resistance borne by the oil sand sample in the process of moving into the inner half cylinders is reduced, interference to the porosity of the oil sand sample and the rock structure is reduced, and the oil sand sample detection accuracy is improved. And the detection error of the oil content is reduced.

The invention relates to the technical field of geological sequestration, in particular to a method and a system for predicting breakthrough pressure of a CO2 geological sequestration mudstone cover layer. The prediction method comprises the following steps: acquiring a mercury injection curve of the CO2 geological sequestration mudstone cover layer; obtaining a calibrated mercury injection curve by using the mercury injection curve; based on the calibrated mercury injection curve, a relation curve of the porosity and the mercury injection pressure is obtained; obtaining a predicted value of the breakthrough pressure through the relation curve; and predicting the breakthrough pressure of the CO2 geological sequestration mudstone cover layer according to the predicted value. On the basis of deep research and wide coverage of characteristics of various mudstone samples, a scientific and reasonable prediction model is established, and low-cost, high-aging and high-precision prediction of the breakthrough pressure of the mudstone cover layer is realized.