Results 21 to 30 of about 3,202 (214)

Lithology Identification of Sandstone-type Uranium Ore Beds in the Songliao Basin based on Interpretable Machine Learning Model

Donghua Ligong Daxue Xuebao. Ziran Kexue Ban
[Objective] Traditional lithology identification methods suffer from low accuracy, slow recognition speed, and poor generalization performance, thus there is an urgent need for an efficient and accurate solution.
XIAO Kun, YANG Pengbo, YANG Yaxin, HU Xudong, LI Hongxing, HUANG Xiao, WANG Dianxue, JIAO Changwei, HE Rong, CHEN Mengshi, YIN Dening   +10 more
doaj   +1 more source

Identification of Rock Properties of Rock Wall Cut by Roadheader Based on PSO-VMD-LSSVM

Frontiers in Earth Science, 2022
The problem of low digging efficiency and mining imbalance due to outdated digging technology and low degree of equipment intelligence has long existed in coal mine roadway excavation work.
Pengfei Qi, Jucai Chang, Xiao Chen, Tuo Wang, Mengyun Wu   +4 more
doaj   +1 more source

Lithology Identification Method and Application Based on Generative Adversarial Neural Network

Cejing jishu
Lithology identification is the basis of reservoir evaluation and the key to reservoir parameter calculation and reservoir evaluation and development.
YIN Qiong
doaj   +1 more source

Enhanced machine learning tree classifiers for lithology identification using Bayesian optimization

Applied Computing and Geosciences, 2022
Lithology identification is a fundamental activity in oil and gas exploration. The application of artificial intelligence (AI) is currently being adopted as a state-of-the-art means of automating lithology identification.
Solomon Asante-Okyere, Chuanbo Shen, Harrison Osei   +2 more
doaj   +1 more source

A Geomorphometric Approach to Estimate the Deterioration of Earthen Archaeological Sites by Rainfall and Diffusion Processes: The Huaca Chornancap (Eighth–14th Century ad), Lambayeque, Peru

Archaeological Prospection, EarlyView.
ABSTRACT Rain‐induced erosion processes can severely damage Earthen archaeological sites. Huaca Chornancap (HCH; eighth–14th century ad) is a platform located in the Lambayeque region (Peru) exposed to seasonal rain due to El Niño Southern Oscillation (ENSO).
Luigi Magnini, Maria Ilaria Pannaccione Apa, Robert Gutiérrez Cachay, Marco Fernández Manayalle, Carlos Eduardo Wester La Torre, Guido Ventura   +5 more
wiley   +1 more source

A lithology identification method while drilling based on KAN neural network

Meitan xuebao
Lithology identification while drilling is an important geological guarantee means for transparent detection of coal mine geology. The traditional lithology identification method mainly relies on manual judgment, which relies on the accumulation of ...
Bo WANG, Liujun XIE, Hongyun CHEN, Linfeng ZENG, Sihongren SHEN, Naichuan WANG, Dewei ZHANG   +6 more
doaj   +1 more source

A machine learning lithologic identification method combined with vertical reservoir information

地质科技通报, 2023
Compared with coring data, well logging data contain much lithologic information with the advantages of strong continuity and low cost. The machine learning method is applied to explore the correlation between the log curves and the lithology of the ...
Chi Zhang, Mao Pan, Shuiqing Hu, Yafei Hu, Yiqun Yan   +4 more
doaj   +1 more source

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Critical expansion points: Mechanical signs of surrounding rock instability

Deep Underground Science and Engineering, EarlyView.
This study proposes the Rock Bearing‐Expansion Model (RockBEM) with critical expansion points (CEPs) to quantify post‐peak damage stages in deep‐buried rock masses via plane strain compression test (PSCT). CEP hysteresis&interval ratios reveal bearing performance dynamics and failure severity, advancing mechanistic insights into deep underground rock ...
Jiaqi Wen, Chang Deng, Haijun Wang, Lei Tang, Jihong Yu   +4 more
wiley   +1 more source

The Research on Complex Lithology Identification Based on Well Logs: A Case Study of Lower 1st Member of the Shahejie Formation in Raoyang Sag

Energies, 2023
Lithology identification is the basis for sweet spot evaluation, prediction, and precise exploratory deployment and has important guiding significance for areas with low exploration degrees.
Zhaojing Song, Dianshi Xiao, Yongbo Wei, Rixin Zhao, Xiaocheng Wang, Jiafan Tang   +5 more
doaj   +1 more source