Real-time porosity prediction using gas-while-drilling data and machine learning with reservoir associated gas: Case study for Hassi Messaoud field, Algeria
A novel inverse intelligent model is developed to predict porosity in real time while drilling. It
applies established machine learning (ML) models to gas-while-drilling (GWD) data …
applies established machine learning (ML) models to gas-while-drilling (GWD) data …
Integrating drilling parameters and machine learning tools to improve real-time porosity prediction of multi-zone reservoirs. Case study: Rhourd Chegga oilfield …
A Ouladmansour, O Ameur-Zaimeche… - Geoenergy Science and …, 2023 - Elsevier
Porosity is a key variable for hydrocarbon reservoirs evaluation. It can be directly determined
in laboratory tests using core samples or calculated indirectly from well logs. However, these …
in laboratory tests using core samples or calculated indirectly from well logs. However, these …
Modelling and Simulating Eulerian Venturi Effect of SBM to Increase the Rate of Penetration with Roller Cone Drilling Bit
Drilling bits are essential downhole hardware that facilitates drilling operations in high-
pressure, high-temperature regions and in most carbonate reservoirs in the world. While the …
pressure, high-temperature regions and in most carbonate reservoirs in the world. While the …
[PDF][PDF] Modelling and Simulating Eulerian Venturi Effect of SBM to Increase the Rate of Penetration with Roller Cone Drilling Bit. Energies 2023, 16, 4185
Drilling bits are essential downhole hardware that facilitates drilling operations in
highpressure, high-temperature regions and in most carbonate reservoirs in the world. While …
highpressure, high-temperature regions and in most carbonate reservoirs in the world. While …