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[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 …
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
Accurate prediction of rate of penetration is a prerequisite for optimization of drilling
parameters. However, characteristics such as multiple drilling conditions, inconsistency in …
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 …
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
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 …
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
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 …
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
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 …
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
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 …
huge experimental works, and the discontinuity in the measurement and the limited …
Machine learning models for generating the drilled porosity log for composite formations
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 …
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 …
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
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 …
flexibility. However, the robot is a weak rigid system, and its machining process is unstable …