Application of artificial intelligence techniques in the petroleum industry: a review

H Rahmanifard, T Plaksina - Artificial Intelligence Review, 2019 - Springer
In recent years, artificial intelligence (AI) has been widely applied to optimization problems
in the petroleum exploration and production industry. This survey offers a detailed literature …

Predicting the oil production using the novel multivariate nonlinear model based on Arps decline model and kernel method

X Ma, Z Liu - Neural Computing and Applications, 2018 - Springer
Prediction of petroleum production plays a key role in the petroleum engineering, but an
accurate prediction is difficult to achieve due to the complex underground conditions. In this …

[HTML][HTML] Development of new correlations for the oil formation volume factor in oil reservoirs using artificial intelligent white box technique

S Elkatatny, M Mahmoud - Petroleum, 2018 - Elsevier
Oil formation volume factor (OFVF) is considered one of the main parameters required to
characterize the crude oil. OFVF is needed in reservoir simulation and prediction of the oil …

Development of a new correlation for bubble point pressure in oil reservoirs using artificial intelligencetechnique

S Elkatatny, R Aloosh, Z Tariq, M Mahmoud… - SPE Kingdom of Saudi …, 2017 - onepetro.org
Accurate determination of the bubble point pressure is extremely important for several
applications in oil industry. In reservoir engineering applications the bubble point pressure is …

A comparative evaluation of global search algorithms in black box optimization of oil production: A case study on Brugge field

T Foroud, A Baradaran, A Seifi - Journal of Petroleum Science and …, 2018 - Elsevier
We evaluate the application of eight different global search algorithms to the optimization of
oil production from a mature field. Our focus is on algorithms that treat the reservoir simulator …

Quantification of prediction uncertainty using imperfect subsurface models with model error estimation

MH Rammay, AH Elsheikh, Y Chen - Journal of Hydrology, 2019 - Elsevier
Subsurface reservoirs are far more heterogeneous and complex than the simulation models
in terms of scale, assumptions and description. In this work, we address the issue of …

Virtual multiphase flowmetering using adaptive neuro-fuzzy inference system (ANFIS): A case study of Hai Thach-Moc Tinh field, offshore Vietnam

TN Trung, TH Truong, TV Tung, NH Hai, DQ Khoa… - SPE Journal, 2022 - onepetro.org
For any oil and gas company, well-testing and performance-monitoring programs are
expensive because of the cost of equipment and personnel. In addition, it may not be …

Symmetric Nonlinear Feedback Control and Machine Learning for Sustainable Spherical Motor Operation

M Hassan, E Beshr, M Beshr, AM El-Rifaie - Symmetry, 2023 - mdpi.com
This paper presents a comprehensive evaluation of a new control technique for the sphere
motor system, aimed at achieving accurate tracking, robust and dispersion of vibrations …

A new look into the prediction of static Young's modulus and unconfined compressive strength of carbonate using artificial intelligence tools

Z Tariq, A Abdulraheem, M Mahmoud… - Petroleum …, 2019 - earthdoc.org
Accurate estimation of rock elastic and failure parameters plays a vital role in petroleum, civil
and geotechnical engineering applications. During drilling operations, continuous logs of …

[HTML][HTML] Fractured reservoir history matching improved based on artificial intelligent

SH Riazi, G Zargar, M Baharimoghadam, B Moslemi… - Petroleum, 2016 - Elsevier
In this paper, a new robust approach based on Least Square Support Vector Machine
(LSSVM) as a proxy model is used for an automatic fractured reservoir history matching. The …