10 results about "Coal rank" patented technology

The application discloses an aerobic-anaerobic bacteria combined coal pretreatment biological gas production device, which comprises a gas blowing system, a bacterial population pre-culturing system, an aerobic-anaerobic biological combined pretreatment and gas production system and a gas-liquid two-phase collection and monitoring system. The application also discloses a gas production method of the gas production device. The application takes coal as a substrate, and under suitable conditions, carries out culture and optimization of a methanogenic bacterial population, and simulates indoor biological gas production effects under different coal rank, bacterial type, combined pretreatment mode, treatment time and metabolic environment conditions. The application adopts an integrated combined processor to combine aerobic bacteria and anaerobic bacteria for pretreating coal, so that coal-based biological gas production can be safely and efficiently carried out, and the application has important environmental benefits and broad application prospect.

The invention discloses a comprehensive evaluation method for a deep coal bed gas reservoir, and the method comprises the following specific steps: S100, classifying gas wells according to the effects of produced wells in a research area, and dividing the gas wells into three types of gas wells I, II and III; s200, in combination with gas well classification standards, carrying out classification evaluation on three types of gas wells I, II and III, including coal rock type, coal rank, coal body structure, coal seam thickness, coal seam physical property, coal seam gas-bearing property, coal seam roof and floor research and the like; and S300, establishing a coal rock reservoir comprehensive evaluation classification standard table according to classification evaluation, evaluating the reservoir quality of the undeveloped target area of the research area, and guiding coal bed gas development. By establishing the comprehensive evaluation method for the deep coal-bed gas reservoir, the method has good guiding significance for efficient development of the deep coal-bed gas, the actual reservoir characteristics of the deep coal-bed gas can be reflected, the requirement for the quality of the geological comprehensive evaluation reservoir is met, a favorable area is preferably selected for comprehensive evaluation of the deep coal-bed gas reservoir, and efficient development is achieved.

The present application provides a kind of coal tar macromolecular network model construction method based on HRTEM and XPS, belongs to chemical molecular reaction kinetics technical field, including S1: processing coal tar macromolecular sample HRTEM image data;S2: determine the element composition and functional group composition of coal tar macromolecular sample;S3: set the basic unit structure of coal tar macromolecular network model, and calculate the proportion of different unit structure;S4: construct the aromatic layer sheet of carbon skeleton unit in coal tar macromolecular network model;S5: set the bridge bond of carbon skeleton unit, finally obtain the complete carbon skeleton unit in coal tar macromolecular network model;S6: revise the edge of carbon skeleton unit, hydrogenation is added to carbon skeleton unit and the coal tar macromolecular network model is optimized.It can finely construct coal tar macromolecular network, restore the real composition of coal tar molecule to the greatest extent, ensure that subsequent calculation structure is more real, suitable for constructing macromolecular network model for coal tar obtained under different coal rank and different working conditions.

The invention discloses a coal reservoir permeability test optimization method and system, and the method comprises the steps: carrying out the clustering analysis of coal samples of different coal orders through a K-means clustering and random forest algorithm, and constructing a permeability test database containing the permeability of different coal orders, the fracture pressure, the pore characteristics and other parameters; on the basis of a CT scanning result of the coal sample, physical characteristics such as a pore structure and fracture distribution of the lump coal are analyzed, a representative position is selected for sample preparation, and a fracture pressure interval of the sample is pre-judged according to a database; intelligently adjusting a pressurization strategy according to the pre-judgment interval, and switching to slow gradient pressurization when the pressure is close to the fracture pressure of the coal sample; and according to the measured data points, abnormal points and invalid data points in a fracture area are automatically identified and eliminated based on a random forest algorithm, representative data points are optimally selected in a permeability test stable section and a characteristic inflection point interval, and finally data constraint and fitting correction are performed through a P50 probability method. The method can improve the efficiency and accuracy of the laboratory coal permeability test.

The invention relates to the technical field of oil and gas well development, in particular to a coal rock CT image noise reduction effect evaluation method and system based on multi-index fusion. Fusing a frequency division signal-to-noise ratio, structural similarity, an edge retention index, a signal-to-noise ratio, a mean square error and image entropy to construct a multi-index fusion evaluation model, and determining noise reduction scores of different types of filters with optimal noise reduction parameter configuration according to the multi-index fusion evaluation model; and determining an optimal noise reduction filter of the coal rock CT images of the same coal rank type according to the noise reduction score. According to the invention, by constructing a frequency division signal-to-noise ratio, noise suppression and microstructure protection are adaptively balanced in different frequency domains; and in combination with indexes such as an edge retention index, structural similarity and image entropy, multi-dimensional comprehensive evaluation is realized. The method can effectively improve objectivity and quantificaiton of noise reduction effect evaluation, and provides technical support for high-fidelity digital core modeling and coal bed gas reservoir fine representation.

Provided is a method for easily estimating the surface tension of coal. A method for estimating a surface tension of coal includes: subjecting a surface tension, a physical property value representing a coal rank, and a total inert content of each of different brands of coal to multiple regression analysis to determine in advance a regression equation including the surface tension of coal as an objective variable and the physical property value and the total inert content as explanatory variables; and measuring the physical property value and the total inert content of a coal of which the surface tension is to be estimated, and calculating the surface tension of the coal by using the measured physical property value and the measured total inert content, and the regression equation.

The present application provides a kind of coal seam gas content prediction method, it is related to coalbed gas exploration and development technical field.The present application includes the following steps: first, select coal sample, by vitrinite random reflectance automatic determination image analysis method, obtain the maximum vitrinite reflectance R o,max Then, isothermal gas adsorption experiment is carried out to each coal sample, and the Langmuir volume V L And Langmuir pressure P L According to the maximum vitrinite reflectance R o,max Sample is divided into anthracite sample group, bituminous sample group and sub-bituminous sample group according to coal rank;Finally, the calculation formula of coal seam gas content change with depth under different coal rank is established, and the actual gas emission of coal mine is used to test, realize the calculation of coal seam gas content change with depth, the present application is simple and convenient, low in cost, can obtain the coal seam gas content of different coal mines, has good application effect and wide applicability.

The invention discloses a coal quality firmness coefficient quantification research method based on microscopic molecular structure characteristics, and relates to the technical field of coal mine safety engineering. The method comprises the following steps: collecting blocky coal samples of different coal orders, and measuring a firmness coefficient by using a drop hammer crushing method through pretreatment; measuring the infrared structural characteristics of the further ground coal sample by using a Fourier transform infrared spectrometer to obtain a spectrogram, dividing into four wave bands, and calculating the area proportion of functional groups; measuring the aperture of the coal sample, performing correlation fitting on the parameters and the firmness coefficient, determining the influence weight, constructing a correlation equation, and performing quantitative research on the coal quality firmness coefficient according to the correlation equation. According to the method, a relation equation among the firmness coefficient, the chemical structure characteristics and the pore structure characteristics is established on the basis of testing and analyzing means and methods of the microcosmic chemical structure characteristics, the pore structure characteristics and the firmness coefficient of the coal body, a microcosmic perspective is provided for coal and gas outburst mechanism research, and the method has practical guiding significance for safe production of mines.

The application discloses a kind of middle-high coal rank coalbed gas favorable area prediction method, belong to oil and gas exploration and development technical field.The application first finds out the corresponding Lang's volume value when the lower limit value of middle coal rank vitrinite reflectance Ro according to the relationship between Lang's volume and vitrinite reflectance;Then the relationship between coal seam thickness (D), buried depth (H), overburden thickness (G) and gas content is established respectively, with the Lang's volume value when vitrinite reflectance Ro is 0.7% as the lower limit standard, to establish the intersection between coal seam thickness (D), buried depth (H), overburden thickness (G) and the Lang's volume value when vitrinite reflectance Ro lower limit value;Finally, the intersection value between the above three elements is determined as the standard, and the coalbed gas in a region is plotted with three elements, and the three-element superposition area is the favorable development area of coalbed gas.

The invention discloses a coal firmness coefficient quantification research method, system, equipment and medium, and relates to the technical field of coal mine safety engineering. The method comprises the following steps: collecting blocky coal samples of different coal orders, pretreating the blocky coal samples, and measuring a firmness coefficient by using a drop hammer crushing method; carrying out X-ray photoelectron spectroscopy test and solid nuclear magnetic resonance test, and combining software analysis to obtain carbon structure related data; and carrying out linear fitting analysis on the firmness coefficient and carbon structure related data, calculating an influence weight, and constructing a multiple linear regression equation to realize quantitative research on the coal quality firmness coefficient. According to the method, a relation equation of the firmness coefficient and the carbon skeleton structure characteristics is established through a coal body microcosmic carbon skeleton structure characteristic and firmness coefficient test analysis means method, a microcosmic view angle is provided for coal and gas outburst mechanism research, and the method has practical guiding significance for safety production of mines.