Machine learning methods applied to drilling rate of penetration prediction and optimization-A review

LFFM Barbosa, A Nascimento, MH Mathias… - Journal of Petroleum …, 2019 - Elsevier
Drilling wells in challenging oil/gas environments implies in large capital expenditure on
wellbore's construction. In order to optimize the drilling related operation, real-time decisions …

A machine learning approach to predict drilling rate using petrophysical and mud logging data

M Sabah, M Talebkeikhah, DA Wood… - Earth Science …, 2019 - Springer
Predicting the drilling rate of penetration (ROP) is one approach to optimizing drilling
performance. However, as ROP behavior is unique to specific geological conditions its …

Intelligent decisions to stop or mitigate lost circulation based on machine learning

AK Abbas, AA Bashikh, H Abbas, HQ Mohammed - Energy, 2019 - Elsevier
Lost circulation is one of the frequent challenges encountered during the drilling of oil and
gas wells. It is detrimental because it can not only increase non-productive time and …

Complications in drilling operations in basalt for CO2 sequestration: An overview

RK Singh, NP Nayak - Materials Today: Proceedings, 2023 - Elsevier
The review article addresses the functional impediments of drilling in basaltic formation for
CO 2 storage. The rising temperature of earth due to increased emission of CO 2 is an …

[HTML][HTML] Implementing artificial neural networks and support vector machines to predict lost circulation

AK Abbas, NA Al-haideri, AA Bashikh - Egyptian Journal of Petroleum, 2019 - Elsevier
Lost circulation is one of the major challenges encountered during drilling operations. The
events related to the lost circulation can be responsible for losses of hundreds of millions of …

Computational prediction of the drilling rate of penetration (ROP): A comparison of various machine learning approaches and traditional models

E Brenjkar, EB Delijani - Journal of Petroleum Science and Engineering, 2022 - Elsevier
Rate of penetration (ROP) prediction, can assist precise planning of drilling operations and
can reduce drilling costs. However, easy estimation of this key factor by traditional or …

Drilling rate of penetration prediction of high-angled wells using artificial neural networks

AK Abbas, S Rushdi, M Alsaba… - Journal of Energy …, 2019 - asmedigitalcollection.asme.org
Predicting the rate of penetration (ROP) is a significant factor in drilling optimization and
minimizing expensive drilling costs. However, due to the geological uncertainty and many …

Rock drillability intelligent prediction for a complex lithology using artificial neural network

H Gamal, S Elkatatny, A Abdulraheem - Abu Dhabi International …, 2020 - onepetro.org
The fourth industrial revolution and its vision for developing and governing the technologies
supported artificial intelligence (AI) applications in the different petroleum industry …

Improving drilling performance through optimizing controllable drilling parameters

A Bani Mustafa, AK Abbas, M Alsaba… - Journal of Petroleum …, 2021 - Springer
The prediction of the drilling rate of penetration (ROP) is one of the key aspects of drilling
optimization due to its significant role in reducing expensive drilling costs. Many variables …

[HTML][HTML] Improving predictive models for rate of penetration in real drilling operations through transfer learning

FJ Pacis, A Ambrus, S Alyaev, R Khosravanian… - Journal of …, 2023 - Elsevier
The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling
industry as it directly translates to cost savings and emission reductions. A prerequisite for a …