Drilling parameters optimization using an innovative artificial intelligence model

R Ashena, M Rabiei, V Rasouli… - Journal of …, 2021 - asmedigitalcollection.asme.org
Proper selection of the drilling parameters and dynamic behavior is a critical factor in
improving drilling performance and efficiency. Therefore, the development of an efficient …

An experimental investigation of WAG injection in a carbonate reservoir and prediction of the recovery factor using genetic programming

M Wojnicki, J Lubaś, M Gawroński, S Szuflita… - Energies, 2022 - mdpi.com
Production from mature oil fields is gradually declining, and new discoveries are not
sufficient to meet the growing demand for oil products. Hence, enhanced oil recovery is …

Optimization of drilling parameters using an innovative GA-PS artificial intelligence model

R Ashena, M Rabiei, V Rasouli… - SPE Asia Pacific Oil and …, 2020 - onepetro.org
Proper selection of the drilling parameters and dynamic behavior is a critical factor in
improving drilling performance and efficiency. Real-time monitoring allows the driller to …

Comparison of Three Machine Learning Approaches in Determining Total Organic Carbon (TOC): A Case Study from Marcellus Shale Formation, New York State

D Dimitrijevic, C Cranganu - Artificial Intelligent Approaches in Petroleum …, 2024 - Springer
Abstract Total Organic Carbon (TOC) contained by subsurface source rock units is an ideal
parameter for predicting the potential production of gas and oil shales because it primarily …

Modeling CO2 loading capacity of triethanolamine aqueous solutions using advanced white-box approaches: GMDH, GEP, and GP

F Hadavimoghaddam, B Amiri-Ramsheh… - Discover Applied …, 2024 - Springer
The equilibrium solubility of carbon dioxide (CO2) in the solvents is a key essential
characteristic that has to be evaluated for successful absorption-based CO2 capture …

[PDF][PDF] Prediction of tool wear after machining

F Shahini, N Grgurić - Ri-STEM-2021, 2021 - unirepository.svkri.uniri.hr
The purpose of this article is to regress and predict tool wear from predefined datasets.
Given datasets consists of six different parameters: experiment number, depth of cut (DOC …

Genetic Programming in Graphic Processing Units with TensorFlow

FJR Baeta - 2020 - search.proquest.com
Genetic Programming (GP) is an automatic problem-solving technique inspired by nature,
that optimizes solutions through the evolution of a population of computer programs. This …