55 results about "Mineralogical composition" patented technology

The invention relates to a digital intelligent regulation and control preparation method and system for a high-solid-waste low-carbon high-performance grouting material, and solves the problems that a traditional preparation technology lacks an autonomous and controllable digital intelligent regulation and control system and is weak in adaptability to fluctuation of raw materials, and the method comprises the following steps: obtaining XRF chemical components and XRD mineral composition data of industrial solid waste raw materials; constructing a material gene database; based on the database, screening a proportioning scheme by using a performance prediction model, and predicting workability, strength development and shrinkage performance; inputting a prediction result as a fitness function into a multi-objective optimization algorithm, and outputting an optimal material gene combination; a batching scheme is generated based on the optimal combination, and a stirring process is started after technological parameters are preset; collecting data through a real-time monitoring system, and comparing the data with the digital twin model; and based on a comparison result, automatically adjusting material proportioning parameters. The high-solid-waste, low-carbon and high-performance grouting material has the advantages that accurate design and regulation of the high-solid-waste, low-carbon and high-performance grouting material are achieved, material performance is improved, and carbon emission and cost are reduced.

The invention belongs to the technical field of vanadium enrichment mechanisms of phosphorus vanadium ores, and discloses a research method of a vanadium enrichment mechanism in a diagenetic stage of phosphorus vanadium ores, which comprises the following steps: S1, sample collection and treatment; s2, rock ore identification and mineral composition analysis; s3, analyzing the occurrence state and microcell morphology of vanadium; s4, performing geochemical analysis on the whole rock; s5, in-situ microcell geochemical analysis is carried out; s6, phosphorus nodule analysis; s7, comprehensive analysis and mineralization model establishment; according to the method, mineralogy, total rock geochemistry, micro-area surface scanning and other multi-scale and multi-means research methods are comprehensively utilized, and the vanadium occurrence state, the ore-forming fluid evolution and the phosphorus-vanadium coupling relation are finely described; in-situ microcell geochemical analysis is introduced into phosphorus nodule analysis, the internal structure, the growth sequence and element distribution of the phosphorus nodule are directly revealed, obvious frontier and systematicness are achieved, and reliable theoretical support is provided for accurate exploration of vanadium ore resources and green and efficient dressing and smelting process research and development.

The invention relates to the technical field of road engineering, in particular to a detection method for evaluating cohesion characteristics of river-crossing shield tunnel waste slag improved soil for roadbed filling, which comprises the following steps: preparing a solidified soil sample; calculating coupling parameters; obtaining a static cohesion force and a dynamic cohesion force; obtaining a water stability coefficient; based on the collected roadbed filling characteristic parameters, the static cohesion, the dynamic cohesion and the water stability coefficient, constructing a dynamic resilience modulus correlation model; grading the cohesion characteristics of the solidified shield soil according to the coupling parameters and the dynamic rebound modulus; detecting actual values of the coupling parameters and the dynamic resilience modulus of the to-be-evaluated solidified soil, and determining the grade of the to-be-evaluated solidified soil; according to the cohesion characteristic detection method, the characteristics of shield tunnel soil particles, mineral composition and roadbed filling scenes are fitted, actual working conditions are simulated, and the solidification effect is quantified, so that a scientific basis is provided for engineering application of shield tunnel soil solidification improved roadbed, and the problems in the background technology are effectively solved.

The invention provides a coal gangue-based soil conditioner preparation method and system, and the method comprises the steps: collecting coal gangue soil sample data, extracting mineral composition characteristics, carrying out the classification processing of mineral types through employing a grouping algorithm, and obtaining a mineral diversity level index which reflects the richness and distribution balance of the mineral types; obtaining the active site distribution density value, inputting the active site distribution density value into an organic acid concentration adjustment calculation model, and investigating a chemical reaction mode between the organic acid and minerals through an interactive mode analysis method to obtain an optimized organic acid concentration adjustment scheme; and according to the finally determined evaluation index, verifying the validity of the pollutant fixation treatment formula data by adopting an adsorption performance verification method to obtain a verification result, and if the verification result meets a preset adsorption standard, outputting a preparation scheme of the coal gangue-based soil conditioner.

The invention discloses a rock slice image classification method based on domain self-adaption, and the method comprises the steps: collecting rock slice image data, the method comprises the following steps: acquiring a rock slice image, performing multi-scale data preprocessing and geological field data enhancement, extracting multi-level visual features of the rock slice image by utilizing a pre-trained DINOv3 model, performing field specialized adaptation on general visual features through a geological field adaptive Adapter module, and enhancing rock slice discriminative feature representation by adopting a double-path attention mechanism. Constructing a progressive hierarchical classification head to realize coarse-to-fine rock classification; and designing a multi-stage progressive training strategy to optimize the overall performance of the model. According to the method, mineral composition and structural features of the rock slices under different scales can be accurately captured, and multi-scale features and an attention mechanism are fully utilized, so that accurate classification of the rock slices is realized, and the accuracy and reliability of rock slice identification are remarkably improved.

This invention relates to the field of cement building materials technology, specifically disclosing a method for improving the strength of silicate clinker based on mineral and crystal composition analysis. The method involves collecting 3-day and 28-day compressive strength test data of silicate clinker and quantitatively analyzing the mineral and crystal composition data using XRD. A mineral composition and strength zoning statistical method is employed to obtain appropriate C3S or C2S content to maintain a relatively good overall level of 3-day and 28-day compressive strength of the clinker. Then, a stepwise multiple linear regression analysis is used to establish the relationship between the 3-day and 28-day compressive strength of the clinker, clinker liter weight, f-CaO, the content of other chemical components, and the mineral composition and crystal content of the clinker. Specific analytical methods are used to determine optimization measures, further optimizing and improving the clinker strength. Using the above method, the 3-day and 28-day compressive strength of silicate clinker can be improved simultaneously.

The application discloses a rock component modeling method based on image recognition and belongs to the technical field of numerical simulation tests, and comprises the following steps: S1, image gray processing and coordinate mapping; S2, gray statistics and threshold backstepping; S3, data import and model correspondence; and S4, mineral grouping and attribute assignment steps. The application can accurately acquire the mineral composition information of granite by fusing XRD test results and digital image processing technology, and can construct a modeling system in accordance with the actual rock microcrystal grain morphology and distribution characteristics in the discrete element software, so that the accuracy and the calculation efficiency of the numerical model can be effectively improved, and the visualization capability of the rock crack propagation process can be enhanced.

The mineralogical, chemical, magnetic, and physical properties of a rock can be used to determine the amount of hydrogen that was generated during rock alteration and the remaining amount of hydrogen generation potential. The methodologies evaluate the hydrogen generation potential of geological samples and identify natural hydrogen source rocks. The mineralogy, elemental composition, iron content and oxidation state, and other properties of a geological sample may be determined. From the determined mineralogy and other properties of the geological sample, the amount of hydrogen which the geological sample may have generated may be quantified. This method can determine the maturity of hydrogen source rocks, the potential volume of hydrogen that can be generated in other parts of a given geologic province with higher degrees of hydrogen source rock maturity, and quantify the potential remaining volume of hydrogen that can be still be generated via secondary enhanced hydrogen stimulation processes.

A method is described for characterizing near-wellbore lithology, mineralogy, and heterogeneity, including receiving azimuthal gamma ray data from a horizontal well; calculating a difference between an up-sector gamma ray signal and a down-sector gamma ray signal and normalizing the difference by an average gamma ray value to generate a gamma ray difference value; using the gamma ray difference value to identify heterogeneous intervals along the horizontal well to generate a heterogeneity index; and using the heterogeneity index for at least one of geomechanical analysis of wellbore stability, drilling performance analysis, fracturing decisions, and production performance diagnosis. The method is executed by a computer system.

This invention relates to the field of oil and gas field enhancement and stimulation technology, and discloses a method for screening coupling agents for acid fracturing in carbonate rocks based on interfacial film formation to regulate acid-rock reactions. The method first conducts basic physical property tests on different types of coupling agents to evaluate their wettability and spreading ability on carbonate rock surfaces; then, it characterizes the adsorption and film-forming behavior of the coupling agents on the rock surface; it evaluates the compatibility of the coupling agents with different fracturing fluid systems; it analyzes the influence of coupling agent concentration and stirring conditions on the acid-rock reaction rate through acid-rock reaction experiments, and establishes an evaluation index for acid-rock reaction rate control; finally, it conducts reservoir adaptability evaluation under different temperature, mineral composition, and porosity conditions, and comprehensively screens out target coupling agents suitable for acid fracturing operations in carbonate rocks. This invention establishes a systematic coupling agent screening process, which can effectively reduce the acid-rock reaction rate, increase the acid interaction distance, and thus improve the acid fracturing stimulation effect of carbonate reservoirs.

The invention belongs to the technical field of shale oil and gas development, and discloses a shale oil-gas-bearing potential multi-parameter collaborative evaluation method. The method integrates six experimental technologies of nitrogen adsorption, carbon dioxide adsorption, carbon and oxygen isotope, rock pyrolysis and XRD total rock / clay analysis, and comprises the core steps of obtaining multi-dimensional data such as a pore structure, mineral composition, organic matter characteristics, an isotope ratio and the like after standardized pretreatment of a shale sample, and performing parameter correction, weight distribution and collaborative modeling to obtain a shale sample. And quantifying the oil-gas potential index and grading. The method solves the problem that traditional single parameter evaluation is insufficient in accuracy, data are comprehensive and reliable, and key technical support is provided for shale oil and gas exploration and development and reservoir evaluation.

This invention describes a method of conducting formation evaluation and in particular inferring formation mineralogy when the formation is complex, and when the set of available downhole measurements is limited in information content or quality. One or more embodiments of the method can use a core mineralogy database to generate effective mineral assemblage that captures the natural systematic correlations between series of minerals.

An efficient beneficiation method for niobium ore, relating to the technical field of beneficiation. The method comprises: crushing raw niobium ore and performing low-intensity magnetic separation to remove highly magnetic iron ore, performing desliming treatment on low-intensity magnetic tailings, and then performing high-intensity magnetic separation to obtain high-intensity magnetic concentrate and high-intensity magnetic tailings; performing desiliconization reverse flotation on the high-intensity magnetic concentrate to obtain desiliconized tailings; performing dewatering, reagent removal, and desliming on the desiliconized tailings, and then performing niobium flotation I to obtain niobium concentrate I; performing niobium flotation II on the high-intensity magnetic tailings to obtain niobium concentrate II; and performing dewatering and reagent removal on the niobium concentrate II, and then performing upgrading flotation III to obtain niobium concentrate III. On the basis of the mineralogical characteristics of niobium ore, magnetic separation is first performed for classification, and different flotation methods are respectively applied to magnetic niobium‑containing minerals and non‑magnetic niobium‑containing minerals for enrichment of niobium minerals, which not only improves the overall recovery efficiency of niobium ore, but also increases the niobium concentrate grade and reduces reagent consumption.

The application discloses a hydrogen loss prediction method for an underground hydrogen storage library, and relates to the underground hydrogen storage field.The method comprises the following steps: obtaining time-varying flux of dynamic gas charging and discharging of the underground hydrogen storage library, and establishing a balance physical model of the underground hydrogen storage library; according to a dissolution trend of different minerals under a hydrogen gas, fluid and rock chemical reaction system, a dissolution kinetics model of the different minerals is established; then, the time-varying flux of dynamic gas charging and discharging of the underground hydrogen storage library is combined with the balance physical model and the dissolution kinetics model to solve, so that the change conditions of mineral composition, solution composition and gas composition in the underground hydrogen storage library are obtained, and the hydrogen storage condition of the underground hydrogen storage library is predicted.The application fully considers the complex physical and chemical interaction between hydrogen and reservoir media in the dynamic charging and discharging process of the underground hydrogen storage library, realizes the prediction of hydrogen loss, and improves the efficiency of safe and stable operation of the underground hydrogen storage library.

This invention discloses a lattice distortion-induced M1-C3S ultra-high early strength clinker and its preparation method, belonging to the field of cement material technology. The clinker comprises the following mineral components: C3S, C2S, C3A, C4AF, and f-CaO, with the remainder being mixed mineral components. The clinker is prepared from calcareous raw materials, silica-alumina raw materials, and a mineralizing agent, wherein the mineralizing agent is at least one selected from calcium slag, yellow phosphorus slag, phosphogypsum, bauxite, and fluorite waste. This invention, through synergistic regulation of the mineralizing agent composition and cooling regime, based on the principle of ion-doped lattice distortion, introduces a composite mineralizing agent containing trace elements P, Ti, and F into the raw meal. Combined with a water-cooling rapid cooling process, the high-temperature lattice distortion state is frozen to room temperature, promoting the large-scale generation of highly active M1-C3S. The clinker prepared by this invention has a high total C3S content, a high proportion of M1-type C3S, and a low free calcium content, achieving a synergistic unity of early strength and high later strength.

The invention discloses an X-ray diffraction composition analysis system and method based on machine learning by utilizing domain knowledge. The machine learning-based X-ray diffraction composition analysis method using domain knowledge comprises: a step of receiving an input of X-ray diffraction data of a mineral; a step in which the input X-ray diffraction data is normalized and pre-processed for each data sample; a step of generating a clustering model by using the preprocessed X-ray diffraction data; generating a mineral composition analysis model by using the preprocessed X-ray diffraction data; receiving the input of new X-ray diffraction data, performing preprocessing, and classifying the preprocessed new X-ray diffraction data into conventional composition data or abnormal composition data by using the clustering model; and a step of estimating the mineral composition of new X-ray diffraction data classified as conventional composition data by analysis using the mineral composition analysis model.

The application discloses an intelligent shield muck improvement system based on machine learning, and relates to the technical field of shield tunnel construction.The system comprises a muck area division module, a reverse stability analysis module and a strategy generation module.The muck area division module collects muck macroscopic distribution data through three-dimensional laser scanning, obtains microscopic characteristics such as average particle size and clay mineral composition by combining technologies such as microscopic imaging and XRD, and divides the muck into improvement units with similar physical properties by using K-means clustering.Meanwhile, a machine learning regression model is combined to construct the feasibility index of each improvement unit, and the improvement units are marked as three levels of green, yellow and red to intuitively present the improvement difficulty.The reverse stability analysis module collects transportation and stacking data, accurately identifies disturbance risks caused by water migration and path overlap between improvement units, and the strategy generation module generates a priority improvement sequence according to the improvement level and the disturbance level, and matches a differentiated strategy.

The invention provides a deep sea rare earth sediment foundation preparation method based on supergravity centrifugal physical simulation. The deep sea rare earth sediment foundation preparation method comprises the steps of similarity ratio design, solid phase formula design, initial layered filling in a model box, pore solution preparation, supergravity centrifugal accelerated consolidation and similarity evaluation of a model sample and a deep sea original sample. According to the technical scheme, deep sea stress and temperature boundaries can be reproduced at the same time in a laboratory scale, and the consolidation steady-state time is greatly shortened; the solid phase formula aligns the original sample mineral composition and the rare earth element REE spectrum, and pore water chemical alignment actually measures the seawater main ion strength and pH / Eh value; stable batch preparation can be achieved without open sea sampling, the cost and risk of going out of sea, salvaging and transporting are remarkably reduced, indoor low-cost large-scale preparation of deep sea rare earth sediment sea water samples is achieved, and large-scale indoor mechanics, seepage and process evaluation tests are supported; physical property / chemical / microcosmic / mechanical quantitative thresholds are provided, consistency acceptance and engineering application are facilitated, and batch-to-batch consistency and controllability are high.

The invention particularly relates to a modeling and frequency response calculation method based on acoustic impedance characteristics of submarine sediments. The method comprises the following steps: firstly, acquiring basic physical parameters such as mineral composition, porosity, solid particle volume modulus, pore fluid volume modulus and density of the sediments; then carrying out weighted average on the multi-mineral components, and calculating to obtain an equivalent bulk modulus of the solid skeleton; further determining a low-frequency limit volume modulus and a high-frequency limit volume modulus by combining a Biot theory and a fluid-solid coupling acoustic model; on the basis, a frequency-dependent effective volume modulus expression is constructed, and the equivalent acoustic impedance under different frequencies is calculated according to the frequency-dependent effective volume modulus expression. According to the method, the influence of the multi-mineral composition of the sediment and the property of the pore fluid can be considered at the same time, and the frequency dependence characteristic is introduced, so that accurate modeling of the equivalent acoustic impedance of the seabed sediment is realized, and the method has the advantages of high theoretical accuracy, wide application range and high engineering realizability.

A simulated lunar soil inspection method for construction research. The method comprises: determining a particle size distribution parameter of a simulated lunar soil sample, and calculating a particle size distribution parameter similarity between the simulated lunar soil sample and real lunar soil; determining a mineral composition parameter of the simulated lunar soil sample, and calculating a mineral composition parameter similarity between the simulated lunar soil sample and the real lunar soil; determining a particle shape parameter of the simulated lunar soil sample, and calculating a particle shape parameter similarity between the simulated lunar soil sample and the real lunar soil; determining a density parameter of the simulated lunar soil sample, and calculating a density parameter similarity between the simulated lunar soil sample and the real lunar soil; and when the particle size distribution parameter similarity, the mineral composition parameter similarity, the particle shape parameter similarity and the density parameter similarity all exceed corresponding thresholds, the simulated lunar soil sample passing the inspection.

The invention discloses a method for determining the content of organic sulfur in hydrocarbon source rock, and belongs to the technical field of oil-gas exploration and development. According to the method, the organic sulfur content in the hydrocarbon source rock organic matter is calculated by adopting a method of combining total rock X-ray diffraction analysis and total sulfur analysis. The method comprises the following steps: firstly, obtaining an X-ray diffraction pattern based on a total rock X-ray diffraction test, carrying out phase analysis to obtain mineral composition in a hydrocarbon source rock powder sample, then quantitatively analyzing the mass percent of the sulfur-containing mineral in the hydrocarbon source rock powder sample according to a characteristic peak in the sulfur-containing mineral in the X-ray diffraction pattern, and further obtaining the inorganic sulfur content of the hydrocarbon source rock powder sample. Meanwhile, the total sulfur content of the hydrocarbon source rock powder sample is obtained through an element analysis experiment, and the difference value of the total sulfur content and the inorganic sulfur content in the sample serves as the organic sulfur content. According to the analysis method, kerogen does not need to be prepared, chemical reagents are not used in the whole process, the experiment process is shortened, operation is easy, safety and convenience are achieved, test data are stable and reliable, and repeatability is high.

The present application relates to the technical field of shale mechanical property prediction, and discloses a shale mechanical property prediction method based on a shared decision tree multi-task gradient boosting machine, comprising the following steps: S1, taking sample data under different block and different storage conditions as data sources, wherein total organic carbon content TOC, sampling depth, mineral composition, temperature and pressure are taken as characteristic data, and the elastic modulus, Poisson's ratio and compressive strength of shale are taken as label data; and the characteristic and label data are randomly divided into a training set, a validation set and a test set in a ratio of 0.7:0.2:0.1. Compared with the traditional experimental measurement method, the shale mechanical property prediction method based on the shared decision tree multi-task gradient boosting machine effectively captures the nonlinear relationship between the multi-source characteristics such as mineral composition, confining pressure and temperature and the shale mechanical property under the premise of reducing the measurement cost, and finally has high fitting precision and improves the prediction speed.

The invention discloses a dense rock starting pressure gradient rapid discrimination method based on a DLVO theory. The method comprises the following steps: carrying out an X-ray diffraction experiment to obtain rock sample mineral composition; carrying out a rock core high-pressure mercury injection experiment to obtain rock sample pore throat radius and distribution thereof; carrying out a nuclear magnetic resonance experiment to obtain rock sample pore throat radius and distribution thereof; distinguishing pore and throat radiuses and distribution thereof through nuclear magnetic resonance measurement data in combination with high-pressure mercury injection, and carrying out core full-scale pore and throat distribution characterization; based on the DLVO theory, calculating according to X-ray diffraction experiment data to obtain a curve of rock sample separation pressure changing along with water film thickness; and rapidly judging whether the starting pressure gradient exists or not according to the calculated water film thickness by combining the pore volume distribution obtained by high-pressure mercury injection and nuclear magnetic resonance experiment data. The starting pressure gradient existence judgment method is rapid and reliable, and can provide support for efficient development of oil reservoirs.

An automated sampling system configured to determine the modal mineralogy of a slurry stream in real-time, the system comprising: a sampling collection and preparation unit configured to separate a slurry sample into a first sample fraction comprising particles having a first size in a first range and a second sample fraction comprising particles having a second size in a second different range; a robotic optical microscopy unit configured to obtain optical image data from the first sample fraction and the second sample fraction; and a modal mineralogy analyser configured to analyse the optical image data using a Machine Learning ("ML") algorithm in order to determine the modal mineralogy of the slurry sample.

The application discloses a natural structure surface non-uniformity quantitative characterization method and relates to the technical field of geotechnical engineering. First, the structure surface image is standardized collected, and a single structure surface image is taken as an analysis object. Based on preset mineral color characteristics, pixel in the image is matched and determined by class, so that various minerals are identified and spatial distribution information of the minerals is extracted. Then, a multi-index comprehensive evaluation system is constructed, and quantitative characterization of mineral composition of the structure surface and spatial non-uniform distribution characteristics is realized. Compared with the limitation of traditional mineralogical analysis method which only focuses on mineral composition, the method can characterize the spatial distribution characteristics of the minerals on the structure surface, realize overall description of mineral distribution form and aggregation characteristics, realize mineral region extraction and parameter calculation based on image recognition, relatively simplify the test process, and has higher analysis efficiency. The method is suitable for rapid quantitative analysis of the structure surface sample in engineering and has good engineering application value.

The present application relates to the technical field of soil new pollutant treatment, and particularly relates to a soil microplastic migration evaluation method, comprising the following steps: saturated quartz sand porous medium microplastic migration simulation based on a migration model, wherein the migration model comprises a blocking model and a ripening model; and non-saturated zone variable mineral component porous medium microplastic migration simulation.The present application comprehensively considers microplastic migration under different soil conditions by simulating saturated and non-saturated zones, accurately evaluates migration, provides a scientific basis for subsequent treatment, and uses the blocking and ripening models to fit microplastic migration behavior for scientific evaluation and guidance for targeted treatment measures; in the present application, the non-saturated zone considers the influence of mineral composition by setting different experimental columns, accurately evaluates the migration risk of microplastics in different soils; finally, the evaluation method system constructed in the present application provides a scientific method for soil microplastic treatment, and targeted measures can be taken to reduce pollution risk.

The present application relates to the technical field of reservoir dam leakage detection, and particularly relates to a dam leakage quantitative identification method based on a multivariate mixed model. The present application is based on natural water chemical information to establish and analyze a multivariate mixed model, and further verifies the model by combining isotope composition. In addition, by combining the mineralogical composition differences of water-permeable rock layers and soil and filling materials at different positions, the source position and proportion of dam body leakage can be qualitatively and quantitatively identified, so that the causes and paths of the leakage phenomenon can be more accurately quantitatively identified.

A method for determining a porosity log of a log type for a hydrocarbon reservoir, including: obtaining an input core image, a formation bulk log of the log type, and a formation fluid log of the log type for the reservoir; determining, using a segmentation model and the input core image, a segmented core image to delineate a distribution along the reservoir; determining, using the segmented core image, a volumetric log for the reservoir; determining, using the volumetric log and a variable rock matrix value of the log type, a rock matrix log of the log type by assigning the variable rock matrix value of the log type to a lithology or mineralogy; and determining, using the rock matrix log, the formation bulk log of the log type, and the formation fluid log of the log type, the porosity log of the log type for the reservoir.

The invention discloses a method for measuring the porosity of ore, which belongs to the technical field of mineral processing and metallurgical engineering, and comprises the following steps: adopting a crushing process consistent with the industry, combining with multi-stage screening, and controlling samples of various size fractions to synchronously and naturally fall to the same point for coning at the same time length, so as to simulate the particle size distribution and natural repose angle state of real dump leaching; enabling the measured environment to fit an industrial ore stacking state; the method comprises the following steps: measuring a mineral composition mass fraction mi by combining automatic mineralogical analysis, and calculating a theoretical density rho theory through weighted summation, thereby avoiding deviation of a porosity calculation basis caused by estimating a theoretical volume by using an average density; a dense ore grinding sample is prepared, the pore correction coefficient K is calculated through epoxy resin impregnation for correction, the problem that the measurement accuracy is influenced due to the fact that a primary pore structure is damaged in the fine grinding sample grinding process is avoided, and then more accurate ore porosity measurement data are obtained.