[HTML][HTML] A review of data-driven intelligent monitoring for geological drilling processes

S Du, C Huang, X Ma, H Fan - Processes, 2024 - mdpi.com
The exploration and development of resources and energy are fundamental to human
survival and development, and geological drilling is a key method for deep resource and …

Prediction of rate of penetration based on drilling conditions identification for drilling process

X Yang, M Wu, C Lu, W Li, L Chen, S Du - Neurocomputing, 2024 - Elsevier
Accurate prediction of rate of penetration is a prerequisite for optimization of drilling
parameters. However, characteristics such as multiple drilling conditions, inconsistency in …

A Bayesian optimized variational mode decomposition-based denoising method for measurement while drilling signal of down-the-hole drilling

W Ding, S Hou, S Tian, S Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Measurement while drilling (MWD) emerges as a reliable technique for assessing rock mass
properties. However, the measured MWD signals are often contaminated with noise, leading …

Data augmentation considering distribution discrepancy for fault diagnosis of drilling process with limited samples

A Yang, C Lu, W Yu, J Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The fault diagnosis during drilling is necessary to prevent the accidents develop to more
serious status. Data-driven diagnosis methods have great advantages in nonlinear industrial …

Adaptive monitoring for geological drilling process using neighborhood preserving embedding and Jensen–Shannon divergence

H Fan, C Lu, X Lai, S Du, W Yu, M Wu - Control Engineering Practice, 2023 - Elsevier
Since the geological drilling process involves numerous variables and the relationships
between them are also complex, it is not easy to implement an accurate description of …

A novel rate of penetration model based on support vector regression and modified bat algorithm

Y Zhou, C Lu, M Zhang, X Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In the geological drilling process, predicting the rate of penetration (ROP) is significantly
important for improving drilling efficiency and reducing nondrilling time. However, due to the …

Applications of artificial intelligence for static Poisson's ratio prediction while drilling

A Ahmed, S Elkatatny, A Alsaihati - Computational Intelligence …, 2021 - Wiley Online Library
The prediction of continued profile for static Poisson's ratio is quite expensive and requires
huge experimental works, and the discontinuity in the measurement and the limited …

Machine learning models for generating the drilled porosity log for composite formations

H Gamal, S Elkatatny, AA Mahmoud - Arabian Journal of Geosciences, 2021 - Springer
Determining the porosity of the drilled formation is a significant task for formation evaluation
purposes for further implementation in petroleum reservoir simulation and estimating the …

Intelligent Identification over Power Big Data: Opportunities, Solutions, and Challenges.

L Luo, X Li, K Yang, M Wei, J Yang… - … -Computer Modeling in …, 2023 - search.ebscohost.com
The emergence of power dispatching automation systems has greatly improved the
efficiency of power industry operations and promoted the rapid development of the power …

Process-oriented unstable state monitoring and strategy recommendation for burr suppression of weak rigid drilling system driven by digital twin

M Xu, S Liu, H Shen, J Bao - The International Journal of Advanced …, 2022 - Springer
Robots have been widely used in machining due to their excellent expansibility and high
flexibility. However, the robot is a weak rigid system, and its machining process is unstable …