Data driven model for sonic well log prediction
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 …
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
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, 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 …
(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
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 …
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
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 …
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
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 …
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 …
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
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; …
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
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 …
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
The experimental Poisson's ratio prediction is time-consuming and expensive and resulted
in discontinuous profile. Besides, the limited applicability of the existing empirical …
in discontinuous profile. Besides, the limited applicability of the existing empirical …