China University of Petroleum

Jun Yao

Kai Zhang

Yongfei Yang

Hai Sun

Lei Zhang

Jie Liu

Xin Wang

Wei Wang

Lei Liu

Ke Wang

Xia Yan

Fei Luo

Shujing Liu

Dongyan Fan

Heng Zhou

Ning Wu

Huaisen Song

Lei Yang

Zhaoqin Huang

Wenhui Song

Liang Gong

Wenjie Zhang

Yuanbo Wang

Yufan He

Bozhao Xu

Fugui Liu

Qingqing Jiao

Liu Tao

Qianfei Lv

Shuaishi Fu

Liang Zhou

Xu Zhang

Yingwen Li

Xu Zhou

Zhihui Liu

Xinze Li

Qian Sang

Feng Sun

Xiaoguang Huang

Pengfei Liu

Haiyuan Yang

Yuda Kan

Junrong Liu

Provided are a thermal-hydrological-mechanical-chemical coupling exploitation experimental device for a deep oil and gas reservoir, and a simulation system. The device includes a loading bin, a sample holding bin, a true triaxial pressure loading mechanism arranged on the loading bin, a temperature control system arranged on the true triaxial pressure loading mechanism, and a monitoring system having a detection element arranged in the rock sample and the sample holding bin. A sample entry port is formed in one side surface of the loading bin. The sample holding bin has one end slidably arranged in the sample entry port, can be sealed and connected with the sample entry port, and is configured for placing and fixing a rock sample. Multiple through holes are uniformly formed on an outer end cover of the sample holding bin and are configured for detecting and adding water, gas, and oil.

Thermal-hydrological-mechanical-chemical coupling exploitation experimental device of deep oil and gas reservoir and simulation system

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 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

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

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

A method and system for determining contact angles of porous media, including: in a displacement simulation experiment, injecting a displacement fluid into a actual core sample, and performing computed tomography scanning on the core to determine three-dimensional images at different oil displacing time points; segmenting different phases of the three-dimensional images to obtain segmented three-dimensional images; marking a contact line between different phases according to the segmented three-dimensional images, where the phases are underground fluids or displacement fluids and a rock matrix in the displacement simulation experiment; and determining a contact angle of the porous media at different 3D positions at different time points according to the contact line. The method and system provided can obtain the dynamic changing process of the contact angle at different 3D positions in the core at different displacement time points, reflect the wettability of the real reservoir environment more accurately.

Method and system for determining contact angle of porous media

Growing community of inventors

Qingdao, China

Jun Yao