[HTML][HTML] Refinery 4.0, a review of the main challenges of the Industry 4.0 paradigm in oil & gas downstream

IG Olaizola, M Quartulli, E Unzueta, JI Goicolea… - Sensors, 2022 - mdpi.com
Industry 4.0 concept has become a worldwide revolution that has been mainly led by the
manufacturing sector. Continuous Process Industry is part of this global trend where there …

A paradigm shift for modeling and operation of oil and gas: From industry 4.0 in CPS to Industry 5.0 in CPSS

X Wang, Y Wang, J Yang, X Wang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Under the impetus of Industry 4.0, oil and gas is undergoing an unprecedented digital
transformation, and many innovative ideas are proposed. However, the achieved higher …

Human centric digital transformation and operator 4.0 for the oil and gas industry

TR Wanasinghe, T Trinh, T Nguyen, RG Gosine… - Ieee …, 2021 - ieeexplore.ieee.org
Working at an oil and gas facility, such as a drilling rig, production facility, processing facility,
or storage facility, involves various challenges, including health and safety risks. It is …

Towards drilling rate of penetration prediction: Bayesian neural networks for uncertainty quantification

M Bizhani, E Kuru - Journal of Petroleum Science and Engineering, 2022 - Elsevier
Drilling rate of penetration (ROP) prediction has long been a part of any drilling activity. By
accurate prediction of ROP, optimization can be done that maximizes ROP and reduces …

[HTML][HTML] Artificial general intelligence for the upstream geoenergy industry: a review

JX Li, T Zhang, Y Zhu, Z Chen - Gas Science and Engineering, 2024 - Elsevier
Abstract Artificial General Intelligence (AGI) is set to profoundly impact the traditional
upstream geoenergy industry (ie, oil and gas industry) by introducing unprecedented …

Uncertainty quantification of reservoir performance using machine learning algorithms and structured expert judgment

M Fathy, FK Haghighi, M Ahmadi - Energy, 2024 - Elsevier
The increasing demand for fossil energy necessitates forecasting of reservoir performance
and informed decision-making under various production scenarios. Although reservoir …

Advancements in field development planning through mathematical analysis for reserves estimation, casing design, accidental events and carbon dioxide storage

M Giakoumi, C Konstantinou, N Papadimitriou… - Gas Science and …, 2024 - Elsevier
The objective of this work is to introduce novel methodologies in specific parts of Field
Development Plans (FDPs) by leveraging contemporary technological advancements …

Selection of sand control completion techniques using machine learning

H Laoufi, Z Megherbi, N Zeraibi, A Merzoug… - ARMA/DGS/SEG …, 2022 - onepetro.org
Sand production is one of the major problems in many oil and gas assets around the world.
Uncontrollable sand production can affect hydrocarbon recovery and increase operational …

Big data analytics in oil and gas industry

V Shah, J Shah, K Dudhat, P Mehta… - … Technol. Sustain. Smart …, 2022 - api.taylorfrancis.com
An oilfield is a commercial asset similar to any other in that it requires investment to generate
revenue. When it comes to the way the oil and gas (O&G) sector spends to create cash flow …

Case studies involving machine learning for predictive maintenance in oil and gas production operations

L Saputelli, C Palacios, C Bravo - … Learning Applications in …, 2022 - api.taylorfrancis.com
Throughout history, maintenance has moved from reactive maintenance of fixing it when it
breaks toward more systematic analysis techniques in terms of root-cause analysis …