Data driven model for sonic well log prediction

D Onalo, S Adedigba, F Khan, LA James… - Journal of Petroleum …, 2018 - Elsevier
Near wellbore failure during the exploration of hydrocarbon reservoirs presents a serious
concern to the oil and gas industry. To predict the probability of these undesirable …

Real-time prediction of Poisson's ratio from drilling parameters using machine learning tools

O Siddig, H Gamal, S Elkatatny, A Abdulraheem - Scientific Reports, 2021 - nature.com
Rock elastic properties such as Poisson's ratio influence wellbore stability, in-situ stresses
estimation, drilling performance, and hydraulic fracturing design. Conventionally, Poisson's …

Estimation of static young's modulus for sandstone formation using artificial neural networks

AA Mahmoud, S Elkatatny, A Ali, T Moussa - Energies, 2019 - mdpi.com
In this study, we used artificial neural networks (ANN) to estimate static Young's modulus
(Estatic) for sandstone formation from conventional well logs. ANN design parameters were …

Applying different artificial intelligence techniques in dynamic Poisson's ratio prediction using drilling parameters

O Siddig, H Gamal, S Elkatatny… - Journal of Energy …, 2022 - asmedigitalcollection.asme.org
Rock geomechanical properties impact wellbore stability, drilling performance, estimation of
in situ stresses, and design of hydraulic fracturing. One of these properties is Poisson's ratio …

Real-time determination of rheological properties of high over-balanced drilling fluid used for drilling ultra-deep gas wells using artificial neural network

I Gomaa, S Elkatatny, A Abdulraheem - Journal of Natural Gas Science and …, 2020 - Elsevier
Drilling depleted and ultra-deep gas reservoirs required special drilling fluids which should
be capable of bridging along the walls of the well and withstands a high differential …

Application of artificial intelligence techniques in estimating oil recovery factor for water derive sandy reservoirs

AA Ahmed, S Elkatatny, A Abdulraheem… - SPE Kuwait Oil and …, 2017 - onepetro.org
Oil and gas operating companies are always concerned with evaluating the reserve of their
assets. Evaluation process of hydrocarbon reserves requires a full understanding and …

New robust model to estimate formation tops in real time using artificial neural networks (ANN)

S Elkatatny, A Al-AbdulJabbar, AA Mahmoud - Petrophysics, 2019 - onepetro.org
Determination of the formation tops is an important and critical parameter while drilling a
hydrocarbon well since it is one of the main factors affecting selection of the casing setting …

[HTML][HTML] A gated recurrent unit model to predict Poisson's ratio using deep learning

FS Alakbari, ME Mohyaldinn, MA Ayoub… - Journal of Rock …, 2024 - Elsevier
Static Poisson's ratio (ν s) is crucial for determining geomechanical properties in petroleum
applications, namely sand production. Some models have been used to predict ν s; …

Influence of mud filtrate on the pore system of different sandstone rocks

H Gamal, S Elkatatny, A Adebayo - Journal of Petroleum Science and …, 2021 - Elsevier
During drilling the oil and gas wells, the drilling fluid is used for many purposes in the drilling
operations. The mud filtrate might invade the formation, and as a result, alterations will occur …

Real-time static Poisson's ratio prediction of vertical complex lithology from drilling parameters using artificial intelligence models

A Ahmed, S Elkatatny, A Abdulraheem - Arabian Journal of Geosciences, 2021 - Springer
The experimental Poisson's ratio prediction is time-consuming and expensive and resulted
in discontinuous profile. Besides, the limited applicability of the existing empirical …