Results 1 to 10 of about 3,202 (214)

Reservoir Lithology Identification Based on Multicore Ensemble Learning and Multiclassification Algorithm Based on Noise Detection Function [PDF]

Sensors, 2023
Reservoir lithology identification is an important part of well logging interpretation. The accuracy of identification affects the subsequent exploration and development work, such as reservoir division and reserve prediction. Correct reservoir lithology
Menglei Li, Chaomo Zhang
doaj   +2 more sources

Study on automatic lithology identification method while drilling based on acoustic pressure-rock physics parameters mapping. [PDF]

PLoS ONE
The lithology identification while drilling is a critical component of intelligent coal mine exploration. Investigating automatic lithology identification methods is of great significance for enhancing reservoir prediction accuracy and the automation ...
Wei Jiang, Qingfeng Wang, Baoyong Yan, Yang Liu, Shuhan Shi, Hong Fu   +5 more
doaj   +2 more sources

Attention mechanism-enhanced graph convolutional neural network for unbalanced lithology identification [PDF]

Scientific Reports
In this study, we propose a novel method for identifying lithology using an attention mechanism-enhanced graph convolutional neural network (AGCN). The aim of this method is to address the limitations of traditional approaches that evaluate unbalanced ...
Aiting Wang, Shuyu Zhao, Kai Xie, Chang Wen, Hong-ling Tian, Jian-Biao He, Wei Zhang   +6 more
doaj   +2 more sources

Convolutional autoencoder network lithology recognition based on scratch tests [PDF]

Scientific Reports
To address the characteristic of frequent lithological alternations in the continental shale of the Songliao Basin in China and meet the refined requirements of reservoir modeling, it is necessary to establish a higher-precision lithology identification ...
Suling Wang, Zhihui Ren, Kangxing Dong, Yanchun Li, Jinbo Li, Pengyun Wen, Ruyi Qu, Tingting Li, Zhennan Wen   +8 more
doaj   +2 more sources

A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning

Energies, 2020
The identification of underground formation lithology can serve as a basis for petroleum exploration and development. This study integrates Extreme Gradient Boosting (XGBoost) with Bayesian Optimization (BO) for formation lithology identification and ...
Zhixue Sun, Baosheng Jiang, Xiangling Li, Jikang Li, Kang Xiao   +4 more
doaj   +3 more sources

Intelligent lithologic identification of sandy conglomerate reservoirs in District No.7 of Karamay oilfield

Shenzhen Daxue xuebao. Ligong ban, 2023
The sandy conglomerate reservoirs in Karamay are characterized by diverse lithology and interlayers. The cost of the conventional coring methods is high, and the identification accuracy in non-coring section is low, which leads to difficulty in reservoir
LU Ji, LIN Botao, SHI Can, ZHANG Jiahao
doaj   +1 more source

Progress of lithology identification technology while drilling

矿业科学学报, 2022
Lithology identification while in drilling is a convenient and efficient technology to obtain information about formation. It has the advantages of instant, accurate, environmental protection and energy saving.
Yue Zhongwen, Yue Xiaolei, Yang Renshu, Wang Xu, Li Wei, Dai Shiqing, Li Yang   +6 more
doaj   +1 more source

Application of High-Resolution Core Curve Construction in Logging Lithology Identification

Cejing jishu, 2023
Stratum lithology identification based on logging curves is an important direction in the interpretation of logging data, it is usually combined with drilling and coring experiments.
YOU Ting, ZHU Tianyi, XU Pengye, WANG Shuhua, HE Xing, YU Lijun   +5 more
doaj   +1 more source

An optimized identification method of coal-bearing stratum lithology

Gong-kuang zidonghua, 2020
In view of difficulties in obtaining stratum information parameters and low accuracy of lithology identification in existing lithology identification method of coal-bearing stratum in coal mine underground, an optimized identification method of coal ...
ZHANG Ning, ZHANG Youzhen, YAO Ke
doaj   +1 more source

Cross-Well Lithology Identification Based on Wavelet Transform and Adversarial Learning

Energies, 2023
For geological analysis tasks such as reservoir characterization and petroleum exploration, lithology identification is a crucial and foundational task.
Longxiang Sun, Zerui Li, Kun Li, Haining Liu, Ge Liu, Wenjun Lv   +5 more
doaj   +1 more source