Results 261 to 270 of about 2,839,750 (318)

Intelligent Identification of Formation Lithology While Drilling

International Petroleum Technology Conference
Abstract During drilling engineering, the rate of penetration (ROP) is the basic index to measure the drill ability of various rocks, and drilling parameters are the main control factors that affect the ROP. Identifying formation lithology while drilling can promptly adjust drilling parameters and effectively improve drilling efficiency.
C. Peng, H. L. Zhang, J. H. Fu, Q. F. Li, J. Li, B. Zhu, J. P. Peng, H. R. Zhang   +7 more
openaire   +1 more source

Advanced machine learning artificial neural network classifier for lithology identification using Bayesian optimization

Frontiers in Earth Science
Identifying lithology is crucial for geological exploration, and the adoption of artificial intelligence is progressively becoming a refined approach to automate this process.
Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, A. Miftah, M. Fnais, Biraj Kanti Mondal   +5 more
semanticscholar   +1 more source

Identification of Lithology in Gulf of Mexico Miocene Rocks

Offshore Technology Conference, 1996
Abstract In the (W of Mexico, many gas-saturated sands are not Bright Spots and thus arc difficult m dewct on conventional 31) seismic data. These small amplitude reelections occur frequently in pliocene-Miocene exploration plays when the acoustic impedances of the gas-saturated sands id shales are approximately the
F.J. Hilterman, J.W.C. Sherwood, R. Schellhorn, Brad Bankhead, Bryan DeVault   +4 more
openaire   +1 more source

Deep Learning Method for Lithology Identification from Borehole Images

Proceedings, 2017
Lithology identification is one of the keys to understand the nature of hydrocarbon reservoir. Deep learning has become a popular and reliable method for image classification and in other fields. Instead of using ordinary neural networks and conventional logging curves, this paper developed deep learning methods and showed that it is possible to ...
P.Y. Zhang, J.M. Sun, Y.J. Jiang, J.S. Gao   +3 more
openaire   +1 more source

Refined lithology identification: Methodology, challenges and prospects

Geoenergy Science and Engineering, 2023
Heng Shi, ZhenHao Xu, Peng Lin, Wen Ma
openaire   +1 more source

Lithology Classification Based on Set-Valued Identification Method

Journal of Systems Science and Complexity, 2022
Jing Li, Lifang Wu, Wenjun Lü, Ting Wang, Yu Kang, Deyong Feng, Hansheng Zhou   +6 more
openaire   +1 more source

Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network

Automation in Construction, 2021
Zaobao Liu
exaly  

Automated lithology classification from drill core images using convolutional neural networks

Journal of Petroleum Science and Engineering, 2021
Fatimah Alzubaidi, Peyman Mostaghimi, Pawel Swietojanski   +2 more
exaly  

Enhanced lithology identification with few-shot well-logging data using a Confidence-Enhanced Semi-Supervised Meta-Learning Approach

Measurement
Hengxiao Li, Youzhuang Sun, Sibo Qiao
semanticscholar   +1 more source

Reservoir Lithology Identification Based on Improved Adversarial Learning

IEEE Geoscience and Remote Sensing Letters, 2023
Lei Song, Xingyao Yin, Linjie Yin
openaire   +1 more source