Abstract: The present disclosure provides a method for determining effective storage capacity of a gas storage reconstructed from a water-flooded volatile oil reservoir. The method includes: determining an oil reservoir water flooding recovery ratio; determining crude oil production extracted only due to a water flooding effect in an oil reservoir development process; determining an oil-bearing pore volume of a flooded zone of a reservoir influenced due to the water flooding effect and an oil-bearing pore volume of a pure oil zone of a reservoir not influenced due to the water flooding effect corresponding to its original state before an oil reservoir is put into development when the gas storage is reconstructed from the oil reservoir; determining an effective pore volume for gas storage; and computing the effective storage capacity of the gas storage reconstructed from the water-flooded volatile oil reservoir.

Abstract: A preparation method of coffee cherry tea is provided, including following steps: taking ripe and full fresh coffee berries, washing, draining and peeling the fresh coffee berries to obtain coffee peels; drying the coffee peels immediately until a moisture content is in a range of 20% to 30% to obtain dried coffee peels; fermenting the dried coffee peels for a range of 2 days to 3 days to obtain fermentation products; and baking the fermentation products for a range of 3 minutes to 4 minutes under a temperature in a range of 100 Celsius degree (° C.) to 180° C. to obtain the coffee cherry tea. The coffee cherry tea obtained by the preparation method has a mellow and sweet taste, which effectively solves the problem of sour and astringent taste of the existing coffee cherry tea.

Abstract: A method and system for detecting an amount of shale oil based on an occurrence state, wherein an occurrence-state-based shale oil quantification model is established in accordance with a kerogen swelled amount, an amount of kerogen absorbed oil, an amount of free oil in an organic pore, an amount of adsorbed oil by an inorganic mineral and an amount of free oil in an inorganic pore, and detects an amount of shale oil is detected in accordance with the occurrence-state-based shale oil quantification model, such that the accuracy of the evaluation of shale oil mobility is improved.

Abstract: A heterogeneous image registration method includes: performing edge detection on collected images, in combination with a curvature scale space strategy to extract contour curved segments in an edge image. Implementing a feature point detection strategy based on global and local curvature detecting feature points in the contour curved segments, and obtaining the nearest minimum local curvature of the feature points pointing to starting and end points of the contour, respectively. Calculating the number of neighborhood sampling points and neighborhood auxiliary feature points of neighborhoods on both edges of each of the feature points according to the nearest minimum local curvature. Using neighborhood auxiliary feature points and feature points to form a feature triangle, calculating an angle bisector vector and a main direction corresponding to the feature point in the feature triangle.

Abstract: The present invention relates to a method and system for quantitatively evaluating surface roughness of an organic pore of kerogen in shale. The method includes: making a shale sample; applying a circle of silver-painted conductive tape on the edge of the shale sample to obtain a processed sample; conducting image scanning on the processed sample to obtain a scanned image; determining a kerogen area according to the scanned image; determining an organic pore area according to the kerogen area; carrying out gridding treatment on the organic pore area to obtain multiple grid cells; adopting double integral calculation on each of the grid cells to obtain the areas of the multiple grid cells; summing each of the areas to obtain the surface area of the organic pore; and evaluating surface roughness of the organic pore according to the surface area of the pore.

Abstract: The present disclosure provides a method for quantitative evaluation on a sensitivity of a shale oil and gas reservoir to injected fluids. The method includes the following steps: (I) preparation of rock samples; (II) quantitative evaluation on sensitivities of a shale porosity and a bedding fracture permeability to an injected fluid; and (III) quantitative evaluation on a sensitivity of a shale matrix permeability to an injected fluid. A method for comprehensive evaluation on a sensitivity of a shale oil and gas reservoir to injected fluids is innovatively provided based on the nuclear magnetic resonance testing technology with two basic physical property parameters: porosity and permeability. The method realizes quantitative evaluation on sensitivities of pores of different sizes and matrix of shale and a bedding fracture permeability to injected fluids, and realizes quantitative and accurate evaluation on a sensitivity of a shale oil and gas reservoir to injected fluids.

Abstract: The present invention provides a high-precision identification method and system for substations, including building a Mask RCNN objection recognition network model based on convolutional neural networks; inputting acquired image information of a object into the Mask RCNN object recognition network model for preliminary recognition and outputting a recognition result of the object; using an information entropy to create a semantic decision tree and correcting the recognition result of the object according to a principle of relative correlation between different objects and outputting a final recognition decision result; reading the recognition decision result to obtain a true type of the object to be recognized. The present invention greatly improves the accuracy of image recognition of substations, and has a positive role in the research and development of automatic inspection equipment for inspection robots.

Abstract: A system is provided for detecting the mass of oil in an inorganic mineral of shale. The system operates by performing an extraction test on a first shale sample by using chloroform to obtain a total content of shale oil in the shale; enriching kerogen from the second shale sample to obtain dry kerogen; and performing an extraction test on oven-dried kerogen by using chloroform to determine the mass of extracted kerogen. The system also operates by determining the mass of the oil in the organic matter of the shale sample and the mass of the oil in an inorganic mineral of the shale; establishing a model for predicting a ratio of the mass of the oil in the inorganic mineral of the shale to the mass of the oil in the organic matter; and using the prediction model to determine the mass of oil in an inorganic mineral.

Abstract: The present disclosure provide a method for identifying power equipment targets based on human-level concept learning, including: creating a dataset of power equipment images, and annotating power equipment in power equipment images; training neural network and Bayesian network with the annotated dataset and respectively acquire identification results and conditional probabilities; calculating probabilities of unions with the conditional probabilities; and filtering the identification result corresponding to the highest probability of the union as identification result of the dataset of the power equipment images and complete the identification of the power equipment. The present disclosure combines Mask R-CNN and probabilistic graphical model. The bottom layer uses Mask R-CNN, and the top layer uses Bayesian network to train in identifying power equipment images, so that a small amount of data samples can achieve good recognition, which improved the performance of Mask R-CNN model.

Abstract: The present invention provides a high-precision identification method and system for substations, including building a Mask RCNN objection recognition network model based on convolutional neural networks; inputting acquired image information of a object into the Mask RCNN object recognition network model for preliminary recognition and outputting a recognition result of the object; using an information entropy to create a semantic decision tree and correcting the recognition result of the object according to a principle of relative correlation between different objects and outputting a final recognition decision result; reading the recognition decision result to obtain a true type of the object to be recognized.

Abstract: A heterogeneous image registration method includes: performing edge detection on collected images, in combination with a curvature scale space strategy to extract contour curved segments in an edge image. Implementing a feature point detection strategy based on global and local curvature detecting feature points in the contour curved segments, and obtaining the nearest minimum local curvature of the feature points pointing to starting and end points of the contour, respectively. Calculating the number of neighborhood sampling points and neighborhood auxiliary feature points of neighborhoods on both edges of each of the feature points according to the nearest minimum local curvature. Using neighborhood auxiliary feature points and feature points to form a feature triangle, calculating an angle bisector vector and a main direction corresponding to the feature point in the feature triangle.

Abstract: A method for identifying mineral pore types in mud shale includes: determining an inorganic mineral pore image and a kerogen region image of a mud shale Scanning Electron Microscopy (SEM) gray-scale image; performing an expansion operation on the inorganic mineral pore image to obtain an expanded inorganic mineral pore image; comparing the inorganic mineral pore image with the expanded inorganic mineral pore image, and determining an extra region in the expanded inorganic mineral pore image as an expansion region; collecting statistics about the number of pixel points of a siliceous mineral, a calcareous mineral, and a clay mineral; calculating the proportion of each mineral according to the number of pixel points of the minerals; drawing a mineral pore triangular image chart according to the proportions of minerals; and determining the mineral type corresponding to the pores in the inorganic mineral pore image according to the mineral pore triangular image chart.

Abstract: The present disclosure provide a method for identifying power equipment targets based on human-level concept learning, including: creating a dataset of power equipment images, and annotating power equipment in power equipment images; training neural network and Bayesian network with the annotated dataset and respectively acquire identification results and conditional probabilities; calculating probabilities of unions with the conditional probabilities; and filtering the identification result corresponding to the highest probability of the union as identification result of the dataset of the power equipment images and complete the identification of the power equipment. The present disclosure combines Mask R-CNN and probabilistic graphical model. The bottom layer uses Mask R-CNN, and the top layer uses Bayesian network to train in identifying power equipment images, so that a small amount of data samples can achieve good recognition, which improved the performance of Mask R-CNN model.

Abstract: The present invention relates to a method and system for quantitatively evaluating surface roughness of an organic pore of kerogen in shale. The method includes: making a shale sample; applying a circle of silver-painted conductive tape on the edge of the shale sample to obtain a processed sample; conducting image scanning on the processed sample to obtain a scanned image; determining a kerogen area according to the scanned image; determining an organic pore area according to the kerogen area; carrying out gridding treatment on the organic pore area to obtain multiple grid cells; adopting double integral calculation on each of the grid cells to obtain the areas of the multiple grid cells; summing each of the areas to obtain the surface area of the organic pore; and evaluating surface roughness of the organic pore according to the surface area of the pore.

Abstract: A method and system for detecting an amount of shale oil based on an occurrence state, wherein an occurrence-state-based shale oil quantification model is established in accordance with a kerogen swelled amount, an amount of kerogen absorbed oil, an amount of free oil in an organic pore, an amount of adsorbed oil by an inorganic mineral and an amount of free oil in an inorganic pore, and detects an amount of shale oil is detected in accordance with the occurrence-state-based shale oil quantification model, such that the accuracy of the evaluation of shale oil mobility is improved.

Abstract: A system is provided for detecting the mass of oil in an inorganic mineral of shale. The system operates by performing an extraction test on a first shale sample by using chloroform to obtain a total content of shale oil in the shale; enriching kerogen from the second shale sample to obtain dry kerogen; and performing an extraction test on oven-dried kerogen by using chloroform to determine the mass of extracted kerogen. The system also operates by determining the mass of the oil in the organic matter of the shale sample and the mass of the oil in an inorganic mineral of the shale; establishing a model for predicting a ratio of the mass of the oil in the inorganic mineral of the shale to the mass of the oil in the organic matter; and using the prediction model to determine the mass of oil in an inorganic mineral.

Abstract: A method and system for quantitatively evaluating kerogen swelling oil in shale is provided. The method includes: establishing different types of kerogen molecular models, and loading each of the kerogen molecular models into a graphene slit-type pore composed of a lamellar structure; performing energy minimization (EM), relaxation and annealing to obtain a kerogen slit-type pore; loading a shale oil molecule into the kerogen slit-type pore to obtain an initial model of swelling and adsorption of shale oil in kerogen; assigning a value to a force field of the shale oil molecule and the kerogen molecule in the swelling and adsorption model to obtain a density of the kerogen and the shale oil; plotting a density curve of the kerogen and the shale oil; calculating kerogen swelling oil mass; determining per-unit kerogen swelling oil mass; and determining the kerogen swelling oil mass in different evolution stages.

Abstract: A method for identifying mineral pore types in mud shale includes: determining an inorganic mineral pore image and a kerogen region image of a mud shale Scanning Electron Microscopy (SEM) grayscale image; performing an expansion operation on the inorganic mineral pore image to obtain an expanded inorganic mineral pore image; comparing the inorganic mineral pore image with the expanded inorganic mineral pore image, and determining an extra region in the expanded inorganic mineral pore image as an expansion region; collecting statistics about the number of pixel points of a siliceous mineral, a calcareous mineral, and a clay mineral; calculating the proportion of each mineral according to the number of pixel points of the minerals; drawing a mineral pore triangular image chart according to the proportions of minerals; and determining the mineral type corresponding to the pores in the inorganic mineral pore image according to the mineral pore triangular image chart.

Abstract: A peripheral component interconnect express (PCIe) storage system includes N storage devices. Each storage device includes at least one processor, a switch, and at least one storage unit. The switch includes at least two uplink ports and at least two downlink ports. The at least two uplink ports include at least one first uplink port and a second uplink port, and each processor is coupled to the at least one first uplink port. The at least two downlink ports include at least one first downlink port and a second downlink port, and the at least one storage unit is coupled to the at least one first downlink port. A second downlink port of an ith storage device is coupled to a second uplink port of an (i+1)th storage device. A second downlink port of an Nth storage device is coupled to a second uplink port of a first storage device.

Abstract: A peripheral component interconnect express (PCIe) storage system includes N storage devices. Each storage device includes at least one processor, a switch, and at least one storage unit. The switch includes at least two uplink ports and at least two downlink ports. The at least two uplink ports include at least one first uplink port and a second uplink port, and each processor is coupled to the at least one first uplink port. The at least two downlink ports include at least one first downlink port and a second downlink port, and the at least one storage unit is coupled to the at least one first downlink port. A second downlink port of an ith storage device is coupled to a second uplink port of an (i+1)th storage device. A second downlink port of an Nth storage device is coupled to a second uplink port of a first storage device.