Machine learning in reservoir engineering: A Review
W Zhou, C Liu, Y Liu, Z Zhang, P Chen, L Jiang - Processes, 2024 - mdpi.com
With the rapid progress of big data and artificial intelligence, machine learning technologies
such as learning and adaptive control have emerged as a research focus in petroleum …
such as learning and adaptive control have emerged as a research focus in petroleum …
Prediction of uniaxial strength of rocks using relevance vector machine improved with dual kernels and metaheuristic algorithms
The uniaxial compressive strength (UCS) is an essential parameter to study rock
characteristics, determined by direct and indirect methods. However, the direct methods of …
characteristics, determined by direct and indirect methods. However, the direct methods of …
Assessment of the uniaxial compressive strength of intact rocks: An extended comparison between machine and advanced machine learning models
Rock strength is the most deterministic parameter for studying geological disasters in
resource development and underground engineering construction. However, the …
resource development and underground engineering construction. However, the …
Estimation of intact rock uniaxial compressive strength using advanced machine learning
The present investigation introduces an optimal computational model by comparing gene
expression programming (GEP), least square support vector machine (LSSVM), and …
expression programming (GEP), least square support vector machine (LSSVM), and …
Assessment of uniaxial strength of rocks: A critical comparison between evolutionary and swarm optimized relevance vector machine models
The present study compares the evolutionary and swarm-optimized relevance vector
machine (RVM) models to find the optimal model for computing rocks' uniaxial compressive …
machine (RVM) models to find the optimal model for computing rocks' uniaxial compressive …
[HTML][HTML] Bayesian optimization-enhanced ensemble learning for the uniaxial compressive strength prediction of natural rock and its application
C Daniel, X Yin, X Huang, JA Busari, AI Daniel… - Geohazard …, 2024 - Elsevier
Engineering disasters, such as rockburst and collapse, are closely related to structural
instability caused by insufficient bearing capacity of geological materials. Uniaxial …
instability caused by insufficient bearing capacity of geological materials. Uniaxial …
Comprehensive study on the Python-based regression machine learning models for prediction of uniaxial compressive strength using multiple parameters in …
S Kochukrishnan, P Krishnamurthy, N Kaliappan - Scientific Reports, 2024 - nature.com
The strength of rock under uniaxial compression, commonly known as Uniaxial
Compressive Strength (UCS), plays a crucial role in various geomechanical applications …
Compressive Strength (UCS), plays a crucial role in various geomechanical applications …
Hybrid machine learning approach for accurate prediction of the drilling rock index
NM Shahani, X Zheng, X Wei, J Hongwei - Scientific reports, 2024 - nature.com
The drilling rate index (DRI) of rocks is important for optimizing drilling operations, as it
informs the choice of appropriate methods and equipment, ultimately improving the …
informs the choice of appropriate methods and equipment, ultimately improving the …
Visualising the strength development of FICP-treated sand using impedance spectroscopy
Abstract Fungal Induced Calcium Carbonate Precipitation (FICP) is a novel method used in
geotechnical engineering that enhances the engineering properties of sand by using the …
geotechnical engineering that enhances the engineering properties of sand by using the …
Characterizing marble strength and elasticity: Insights from destructive and non-destructive techniques on El Laurel formation (Ecuador)
Measuring the mechanical properties of marbles using simple destructive and non-
destructive techniques could optimize their characterization for several engineering …
destructive techniques could optimize their characterization for several engineering …