China University of Petroleum

Weihai Hualing Opto-electronics Co., Ltd

Shandong University

Qingdao University of Technology

Ieit Systems Co., Ltd.

Kai Zhang

Jun Yao

Hai Sun

Yongfei Yang

Lei Zhang

Xia Yan

Xiaofeng Sun

Wuchang Qi

Jie Li

Wei Wang

Li Jiang

Yonghui Lin

Rongxin Song

Lei Liu

Fei Yao

Weiwei Cui

Junrong Liu

Shujing Liu

Fei Luo

Yuanbo Wang

Dongyan Fan

Zhongzheng Wang

Fugui Liu

Huaqing Zhang

Zifeng Sun

Feng Jia

Zaigui Zhang

Tao Qu

Xinglu Wang

Huaisen Song

Qingqing Jiao

Wenhui Song

Liang Zhou

Mingfeng Sun

Qian Sang

Shuaishi Fu

Bozhao Xu

Guojing Xin

Liming Zhang

Yuda Kan

Laishun Yang

Piyang Liu

Cuiping Wang

Pengtong Wang

Disclosed are a communication method and related components. In this solution, two network stacks are firstly established, and all connection relationships between a client and each server node and between processes of any two server nodes are then divided, so as to obtain two kinds of connection relationships, wherein the two kinds of connection relationships are respectively constructed on the basis of the two network stacks, and the number of one of the two kinds of connection relationships is related to the number of QPs.

Communication method and related components

Provided is a method for shale gas production prediction, including: acquiring real shale gas production data, and determining a target production decline curve model according to the real shale gas production data; setting a time step for production prediction, and obtaining a linear production decline curve by performing production prediction by using the target production decline curve model based on the time step; determining target shale gas production residuals according to the linear production decline curve and the real shale gas production data, inputting the target shale gas production residuals to a long short-term memory, and obtaining a residual prediction result by performing production prediction according to the long short-term memory and the time step; and determining a target production prediction result of shale gas well to be subjected to production prediction based on the linear production decline curve and the residual prediction result.

Method for shale gas production prediction, device, and storage medium

A differentiated real-time injection-production optimization adjustment method of an intelligent injection-production linkage device belongs to the field of oil reservoir injection-production technologies. The method includes: initializing networks; building an injection-production environment model; by an agent, reading an initial state of an injection-production environment; writing a file by an injection-production policy network; obtaining state data of the moment t+1; reading a next state and an economic net present value within the time step; assigning the next state to the current state until a to-be-optimized production period is completed; by batch training on the model, updating a parameter of the environment agent model; updating a parameter of the action evaluation network and a parameter of the injection-production policy network; repeating the above steps until an optimal model is obtained; based on the stored optimal model, linking the intelligent injection-production device to obtain state information of the oil reservoir.

Differentiated real-time injection-production optimization adjustment method of intelligent injection-production linkage device

A system for real-time optimization and adjustment of smart oilfield injection production includes a closed rectangular reservoir simulation box, a reservoir 3D-printed physical model, a simulation production horizontal wellbore system, a simulation injection horizontal wellbore system, a fluid supply system, a fluid collection system, a power fluid system and a computer data collection and control system. The reservoir 3D-printed physical model is in the closed rectangular reservoir simulation box. The simulation production horizontal wellbore system and the simulation injection horizontal wellbore system are in the reservoir 3D-printed physical model. The fluid supply system injects a displacement fluid into the simulation injection horizontal wellbore system in the reservoir 3D-printed physical model to flow to the simulation production horizontal wellbore system. The computer data collection and control system adjusts injection and production volumes of different well sections of the simulation injection horizontal wellbore system and the simulation production horizontal wellbore system.

Simulation experimental system and method for real-time optimization and adjustment of smart oilfield injection production

A vaneless contra-rotating compressor with multiple contra-rotating interfaces and application of the vaneless contra-rotating compressor is provided, which includes at least two vaneless contra-rotating interfaces. For each of the at least two contra-rotating interfaces, the contra-rotating interface corresponds to two of vaneless contra-rotating rotors. A rotating direction of an upstream rotor of the two vaneless contra-rotating rotors and a rotating direction of a downstream rotor of the two vaneless contra-rotating rotors are opposite. Rectifier stator vanes are not provided among all the rotors to supply sufficient inlet negative pre-swirl for the downstream rotors through the upstream rotors. Only the outlet guide vanes of the last stage, of the vaneless contra-rotating rotors are provided. The number of stages and the number of vaneless contra-rotating interfaces may be set flexibly according to the actual pressurization requirements.

Vaneless contra-rotating compressor with multiple contra-rotating interfaces

Disclosed a method for predicting permeability of a multi-mineral phase digital core based on deep learning. In the present disclosure, a three-dimensional digital core is constructed and a pore structure is randomly generated; after a plurality of multi-mineral digital core images is acquired by performing image segmentation on the three-dimensional digital core, permeability corresponding to each of the multi-mineral digital core images is acquired by simulation using multi-physics field simulation software and a multi-mineral digital core data set is constructed based on the plurality of multi-mineral digital core images and the permeability corresponding to each of the multi-mineral digital core images; an SE-ResNet18 convolutional neural network is constructed and trained with the multi-mineral digital core data set; and an image of a multi-mineral core to be predicted is input into the trained SE-ResNet18 convolutional neural network to determine the permeability of the multi-mineral core.

Method for predicting permeability of multi-mineral phase digital core based on deep learning

Disclosed are a thickness detection device, method and system, a storage medium and a processor. The thickness detection device includes: a detection unit, including a plurality of thickness detection chips, wherein the thickness detection chips are sequentially arranged at least in a second direction; and a common unit, arranged opposite and spaced from the detection unit in a first direction, wherein distances between at least two positions of a first surface of the common unit and the detection unit are different, the second direction is perpendicular to the first direction and a moving direction of an object to be detected, and the first surface is a surface of the common unit which is close to the measurement unit.

Thickness detection device, method and system

The present disclosure provides a method and system for constructing a digital rock, and relates to the technical field of digital rocks. According to the method, a three-dimensional (3D) digital rock image that can reflect real rock information is obtained using an image scanning technology, and the image is preprocessed to obtain a digital rock training image for training a generative adversarial network (GAN). The trained GAN is stored to obtain a digital rock construction model. The stored digital rock construction model can be directly used to quickly construct a target digital rock image. This not only greatly reduces computational costs, but also reduces costs and time consumption for obtaining high-resolution sample images. In addition, the constructed target digital rock image can also reflect real rock information.

Method and system for constructing digital rock

Provided are a detection method, a detection apparatus and a detection process. The detection method includes: using a sensor for idle scanning to obtain a first output electrical signal, and performing feedback correction on the first output electrical signal to eliminate a noise to obtain first correction data; using the sensor to scan a correction specimen page to obtain a second output electrical signal, and performing the feedback correction on the second output electrical signal to eliminate a noise to obtain second correction data; calculating according to the first correction data, the second correction data and an electrical signal predetermined value to obtain third correction data; using the sensor to scan a to-be-detected object to obtain a third output electrical signal; and correcting the third output electrical signal according to the first correction data and the third correction data. In the detection method obtains an accurate detection result.

Detection method, detection apparatus and detection process

Growing community of inventors

Shandong, China

Kai Zhang