Results 1 to 10 of about 2,839,750 (318)

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   +3 more sources

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

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   +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

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

Automatic lithology identification in meteorite impact craters using machine learning algorithms. [PDF]

Sci Rep
Identifying lithologies in meteorite impact craters is an important task to unlock processes that have shaped the evolution of planetary bodies. Traditional methods for lithology identification rely on time-consuming manual analysis, which is costly and ...
Yirenkyi S, Boateng CD, Ahene E, Danuor SK.   +3 more
europepmc   +2 more sources

Logging-data-driven lithology identification in complex reservoirs: an example from the Niuxintuo block of the Liaohe oilfield

Frontiers in Earth Science
For lithologic oil reservoirs, lithology identification plays a significant guiding role in exploration targeting, reservoir evaluation, well network adjustment and optimization, and the establishment of reservoir models.
Zuochun Fan, Zuochun Fan, Changhao Hu, Shu Jiang, Man Li, Ye Cai, Yue Jiang, Yang Li, Mei Tian   +8 more
doaj   +2 more sources

Interpretable Dual-Channel Convolutional Neural Networks for Lithology Identification Based on Multisource Remote Sensing Data

Remote Sensing
Lithology identification provides a crucial foundation for various geological tasks, such as mineral exploration and geological mapping. Traditionally, lithology identification requires geologists to interpret geological data collected from the field ...
Sijian Wu, Yue Liu
doaj   +2 more sources

Real-time lithology identification while drilling based on drilling parameters analysis with machine learning

Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Accurate formation lithology information is crucial for addressing post-mining issues. Artificial intelligence is increasingly vital for lithology identification but faces challenges in underground coal mines, especially in accurately interpreting ...
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Chunmiao Liang   +6 more
doaj   +2 more sources

Core Image Lithology Identification

International Journal of Computer Science and Information Technology
Core is a part of subsurface rock formations, and rock classification can be achieved by analyzing lithological characteristics such as color, texture, or shape. This is an essential step in oil and gas exploration. In the field of geology, core image analysis is a method for studying the micro-features of rocks, utilizing color and texture ...
Liying Yang
openaire   +2 more sources