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51.
公开(公告)号:US11009620B2
公开(公告)日:2021-05-18
申请号:US16790801
申请日:2020-02-14
Applicant: Chengdu University of Technology
Inventor: Haiyan Zhu , Yapu Zhao , Jianchun Guo , Xuanhe Tang
IPC: G01V1/50 , G01V1/28 , G06F30/23 , G06F111/10
Abstract: A method for determining a favorable time window of an infill well of an unconventional oil and gas reservoir, which comprises the following steps: S1, establishing a three-dimensional geological model with physical properties and geomechanical parameters; S2, establishing a natural fracture network model in combination with indoor core-logging-seismic monitoring; S3, calculating complex fractures in hydraulic fracturing of parent wells; S4, establishing an unconventional oil and gas reservoir model and calculating a current pore pressure field; S5, establishing a dynamic geomechanical model and calculating a dynamic geostress field; S6, calculating complex fractures in horizontal fractures of the infill well in different production times of the parent wells based on pre-stage complex fractures and the current geostress field; S7, analyzing a microseismic event barrier region and its dynamic changes in infill well fracturing; and S8, analyzing the productivity in different infill times, and determining an infill time window.
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52.
公开(公告)号:US20200233108A1
公开(公告)日:2020-07-23
申请号:US16746864
申请日:2020-01-18
Applicant: Chengdu University of Technology
Inventor: Hui CHEN , Lingqi LU , Ying HU , Xuping CHEN , Youhua WEI , Ke GUO , Hongyan QIAN
IPC: G01V1/28
Abstract: A high-resolution processing method for seismic data based on inverse multi-resolution singular value decomposition includes the steps of: step 1: obtaining a single-trace seismic signal X as a raw signal; step 2: decomposing the seismic signal by using MRSVD algorithm to obtain a series of detailed singular values and inversely recursing the detailed singular values layer by layer to obtain a new detailed signal and an approximate signal; and step 3: sequentially superimposing the new detailed signal on the raw signal, layer by layer, to compensate the high-frequency component of the seismic signal so as to obtain a high-resolution seismic signal.
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公开(公告)号:US20190331567A1
公开(公告)日:2019-10-31
申请号:US16396790
申请日:2019-04-29
Applicant: Chengdu University of Technology , Sichuan University
Inventor: Yufeng WEI , Jianfeng LIU , Lu WANG , Huining XU , Xiaozhang LEI , Jianhui DENG , Dongjie XUE , Chunping WANG , Jianliang PEI , Wenxi FU , Da ZHENG
IPC: G01N3/02
Abstract: A loading platform for a rock mechanics test system (MTS) to realize simple and reliable connection between a high temperature and high pressure force sensor in a triaxial chamber cavity and an upper solid rigid column. The loading platform for rock mechanics test includes a master rod, a secondary rod and a stop sleeve sleeved on the master rod; the stop sleeve is provided with two corbel structures; the secondary rod is composed of a secondary rod head body and a secondary rod body; a circular magnetic block is fixed on the secondary rod to adsorb a hole alignment sleeve sleeved on the secondary rod; and the hole alignment sleeve marked with a first scale line and a second scale line.
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公开(公告)号:US20250069378A1
公开(公告)日:2025-02-27
申请号:US18236859
申请日:2023-08-22
Applicant: Chengdu University of Technology
Inventor: Dongsheng CAI , Qi HUANG , Jian Li
Abstract: An intelligent safety supervision system applied to a ship is provided. An image acquisition module is configured to acquires high-definition images in real time. An automatic recognition module is configured to obtains ship dynamic and static data. A ship server to-performs feature recognition on the ship dynamic and static data to obtain a data processing result, to-transmits the ship dynamic and static data and the data processing result, and receives alarm indication information. An alarm module outputs an alarm. A ship client displays the data processing result, and determines whether to transmit the alarm indication information according to the data processing result. A communication module receives and transmits the ship dynamic and static data and the data processing result. A shore-side supervision system includes a ship safety supervision big data analysis platform for performing secondary feature recognition on the ship dynamic and static data, so as to obtain a secondary data processing result.
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公开(公告)号:US12186856B1
公开(公告)日:2025-01-07
申请号:US18628733
申请日:2024-04-07
Applicant: CHENGDU UNIVERSITY OF TECHNOLOGY
Inventor: Tao Ren , Qingyou Liu , Gang Jiang , Yujia Li , Zheng Jiang , Yachuan You , Lin Xian
Abstract: The present disclosure provides a grinding robot for an inside wall of a small diameter pipe. The grinding robot includes a grinding device, a transmission device, and a driving device. By arranging the grinding robot into the above three portions, the overall bending pipe passability of the robot can be increased, which is convenient for the grinding robot to grind the small diameter pipe. A first gimbal and two second gimbals provided in the transmission device enable the grinding robot to flexibly pass through bends of the pipe, and enable a grinding driving force to be variably transmitted to the grinding device. When the grinding body rotates and contacts a pipe wall, a reaction force of the pipe wall on the grinding body is balanced by an adjusting spring adjustment force in a balance adjusting device and a self-weight of a grinding body.
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56.
公开(公告)号:US12175633B1
公开(公告)日:2024-12-24
申请号:US18763894
申请日:2024-07-03
Applicant: Chengdu University of Technology
Inventor: Guangle Yao , Honghui Wang , Wenlong Zhou , Wei Zeng , Chen Wang , Ruijia Li , Xiaoyu Xu , Jun Li , Siyuan Sun
Abstract: A method of enhancing an abnormal area of a ground-penetrating radar image based on hybrid-supervised learning includes the steps of: building a database including a real image set, a simulation image set and a simulation image label set; adopting a generative adversarial network; processing semi-supervised training and unsupervised training alternately to obtain a trained model, then inputting a real radar image with abnormal area that needs to be enhanced into the model and processing through the generative network to output an abnormal-area-enhanced image. The method overcomes the problems of differences in characteristics between simulated images and real images, and low utilization efficiency of real image information by unsupervised methods, and improves the utilization efficiency of the enhanced network for real image information, the saliency of abnormal areas on real images, and the generalization ability of the enhanced network, therefore effectively enhances the significance of abnormal areas in ground-penetrating radar images.
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公开(公告)号:US20240360733A1
公开(公告)日:2024-10-31
申请号:US18508923
申请日:2023-11-14
Applicant: Chengdu University of Technology
Inventor: Jianguo ZHAO , Qingyou LIU , Haiyan ZHU , Min WAN , Guorong WANG , Xuecheng DONG , Xu LUO , Yingju PEI , Xingming WANG
CPC classification number: E21B23/001 , E21B47/06 , E21B47/09 , E21B47/13
Abstract: A downhole traction system includes a driving system and a downhole wheeled tractor. The driving system is connected with the downhole wheeled tractor; the downhole wheeled tractor comprises a tractor body, a power unit and a plurality of traction units; the plurality of traction units are arranged along the extension direction of the tractor body; each of the traction units comprises a driving arm, a supporting arm, a supporting wheel, a driving assembly and a supporting assembly; the driving arm and the supporting arm are movably connected with the tractor body; and the supporting wheel is connected with the driving arm and the supporting arm. When the supporting assembly drives the supporting arm to extend along the radial direction of the tractor body under the hydraulic drive action of the hydraulic power unit, the supporting wheel can be abutted against the well wall.
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公开(公告)号:US12118698B1
公开(公告)日:2024-10-15
申请号:US18631002
申请日:2024-04-09
Applicant: Chengdu University of Technology
CPC classification number: G06T5/77 , G06V10/25 , G06V10/44 , G06V10/60 , G06V10/751 , G06V20/17 , G06V20/188 , G06T2207/20132
Abstract: Provided are a method for inpainting a highlight region of a vegetation image captured by an unmanned aerial vehicle, a device, a medium, and a product. The method includes: acquiring an image to be inpainted, and a historic image; inputting the image to be inpainted to a trained target detection network to obtain a waterbody highlight region image block; determining a template image block of the image to be inpainted based on the waterbody highlight region image block; cropping the historical image to obtain a plurality of candidate image blocks of the image to be inpainted; determining similarity between each candidate image block and the template image block by using a deep learning image coarse matching method; and screening candidate image blocks with the similarity greater than a predetermined threshold, and determining an optimal candidate image block in the candidate image blocks by using a pixel-by-pixel matching method.
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公开(公告)号:US12025761B2
公开(公告)日:2024-07-02
申请号:US18058794
申请日:2022-11-25
Applicant: Chengdu University of Technology , Guizhou Geological Environment Monitoring Institute (Guizhou Institute of Environmental Geology)
Inventor: Bin Yu , Yangchun Li , Weiwei Deng , Lingwei Yang , Wenhong Chen
Abstract: This is an early identification method for a shallow soil landslide, belonging to the technical field of landslide prevention and control engineering. The present invention accurately determines and identifies a shallow soil landslide in a quantitative manner, improving the early identification efficiency of a landslide and helping to improve the disaster prevention effect.
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60.
公开(公告)号:US20240094419A1
公开(公告)日:2024-03-21
申请号:US18341781
申请日:2023-06-27
Applicant: Chengdu University of Technology
Inventor: Chaorong Wu , Cheng Liu , Kaixing Huang , Yong Li , Yizhen Li , Junxiang Li , Yuexiang Hao
IPC: G01V1/30
CPC classification number: G01V1/30 , G01V2210/6169
Abstract: A seismic quantitative prediction method for shale total organic carbon (TOC) based on sensitive parameter volumes is as follows. A target stratum for a TOC content to be measured is determined, logging curves with high correlations with TOC contents are analyzed, the logging curves are found as sensitive parameters; sample data are constructed using the sensitive parameters; a radial basis function (RBF) neural network is trained with the sample data as an input and the TOC content at a depth corresponding to the sample data as an output to obtain a RBF neural network prediction model; sensitive parameter volumes are obtained by using the sensitive parameters and post stack three-dimension seismic data to invert; prediction samples are constructed using the sensitive parameter volumes; the predicted samples are input to the RBF neural network prediction model to calculate corresponding TOC values, thereby the TOC content of the target stratum is predicted.
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