Pore pressure prediction in offshore Niger delta using data-driven approach: Implications on drilling and reservoir quality

J Pwavodi, IN Kelechi, P Angalabiri, SC Emeremgini… - Energy …, 2023 - Elsevier
Despite exploration and production success in Niger Delta, several failed wells have been
encountered due to overpressures. Hence, it is very essential to understand the spatial …

[图书][B] Handbook of energy transitions

M Asif - 2022 - api.taylorfrancis.com
The global energy scenario is undergoing an unprecedented transition. In the wake of
enormous challenges, such as increased population, higher energy demands, increasing …

Pore pressure prediction by empirical and machine learning methods using conventional and drilling logs in carbonate rocks

MR Delavar, A Ramezanzadeh - Rock Mechanics and Rock Engineering, 2023 - Springer
Precise pore pressure estimation has high significance in terms of drilling and development
operations. Regarding its necessity, empirical and intelligence methods have been …

Artificial neural network prediction of wellbore stability in offshore shallow formations

J Wu, W Liu, J Li, B Han, Q Tan, H Lin, H Liu - Geoenergy Science and …, 2024 - Elsevier
Wellbore instability is one of the most critical challenges during drilling, which may result in
complex problems such as stuck pipe, high torque and mud loss, impeding the drilling …

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 …

Prediction of elastic parameters in gas reservoirs using ensemble approach

MR Aghakhani Emamqeysi, M Fatehi Marji… - Environmental Earth …, 2023 - Springer
Determination of the rock elastic parameters is essential in geomechanical studies. Among
the elastic parameters, Young's modulus (YM) and Poisson's ratio (PR) have many …

Applications of artificial intelligence for static Poisson's ratio prediction while drilling

A Ahmed, S Elkatatny, A Alsaihati - Computational Intelligence …, 2021 - Wiley Online Library
The prediction of continued profile for static Poisson's ratio is quite expensive and requires
huge experimental works, and the discontinuity in the measurement and the limited …

[Retracted] Prediction of the Least Principal Stresses Using Drilling Data: A Machine Learning Application

A Gowida, AF Ibrahim, S Elkatatny… - Computational …, 2021 - Wiley Online Library
The least principal stresses of downhole formations include minimum horizontal stress
(σmin) and maximum horizontal stress (σmax). σmin and σmax are substantial parameters …

An integrated machine learning workflow to estimate in situ stresses based on downhole sonic logs and laboratory triaxial ultrasonic velocity Data

A Mustafa, M Kelley, G Lu… - Journal of Geophysical …, 2024 - Wiley Online Library
The optimum performance of various subsurface operations such as stimulation treatments,
wellbore drilling, horizontal well placement, underground mining, and tunneling rely on …

Comparison of dynamic and static properties of sandstone and estimation of shear wave velocity and Poisson's ratio

MR Motahari, O Amini, A Iraji… - Bulletin of Engineering …, 2022 - Springer
Geomechanical properties of rocks are the basic requirements for the construction of civil
structures. In the present study, a new relationship between static elastic modulus (Es) and …