China University of Petroleum

Hai Sun

Jun Yao

Kai Zhang

Yongfei Yang

Lei Zhang

Lei Liu

Xia Yan

Yuda Kan

Yuanbo Wang

Dongyan Fan

Heng Zhou

Fei Luo

Wenhui Song

Xu Zhang

Fugui Liu

Lei Yang

Shuaishi Fu

Bozhao Xu

Xu Zhou

Zhaoqin Huang

Feng Sun

Liang Zhou

Liang Gong

Xiaoguang Huang

Huaisen Song

Qian Sang

Yufan He

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

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

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Shandong, China

Hai Sun