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 …

Real-time measurement of drilling fluid rheological properties: A review

N Liu, D Zhang, H Gao, Y Hu, L Duan - Sensors, 2021 - mdpi.com
The accurate and frequent measurement of the drilling fluid's rheological properties is
essential for proper hydraulic management. It is also important for intelligent drilling …

Real-time predictive capabilities of analytical and machine learning rate of penetration (ROP) models

C Soares, K Gray - Journal of Petroleum Science and Engineering, 2019 - Elsevier
Real-time drilling optimization consists of selecting operational parameters that maximize a
desirable measure of drilling performance. Drilling optimization efforts often aspire to …

Application of hybrid artificial neural networks for predicting rate of penetration (ROP): A case study from Marun oil field

SB Ashrafi, M Anemangely, M Sabah… - Journal of petroleum …, 2019 - Elsevier
Rate of Penetration (ROP) can be considered as a crucial factor in optimization and cost
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …

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 …

Prediction of drilling rate of penetration (ROP) using hybrid support vector regression: A case study on the Shennongjia area, Central China

C Gan, WH Cao, M Wu, X Chen, YL Hu, KZ Liu… - Journal of Petroleum …, 2019 - Elsevier
Rate of penetration (ROP) prediction is crucial for the optimization and control in drilling
process due to its vital role in maximizing the drilling efficiency. This paper proposes a novel …

[HTML][HTML] Comparison of accuracy and computational performance between the machine learning algorithms for rate of penetration in directional drilling well

O Hazbeh, SK Aghdam, H Ghorbani, N Mohamadian… - Petroleum …, 2021 - Elsevier
Oil and gas reservoirs are of the main assets of countries possessing them. Production from
these reservoirs is one of the main concerns of engineers, which can be achieved by drilling …

Computational intelligence based prediction of drilling rate of penetration: A comparative study

OS Ahmed, AA Adeniran, A Samsuri - Journal of Petroleum Science and …, 2019 - Elsevier
Application of artificial intelligence in the accurate prediction of the rate of penetration (ROP),
an important measure of drilling performance, has lately gained significant interest in oil and …

Developing a new rigorous drilling rate prediction model using a machine learning technique

M Mehrad, M Bajolvand, A Ramezanzadeh… - Journal of Petroleum …, 2020 - Elsevier
Drilling rate of penetration (ROP) prediction is an enormously important step to optimize
drilling controllable parameters. Therefore, numerous efforts have been done in order to …

A novel dynamic model for the online prediction of rate of penetration and its industrial application to a drilling process

C Gan, WH Cao, KZ Liu, M Wu - Journal of Process Control, 2022 - Elsevier
Accurate prediction of the rate of penetration (ROP) is a difficult issue in the drilling process,
especially under complex formation conditions. Many methods, such as mechanism and …