CO2 EOR performance evaluation in an unconventional reservoir through mechanistic constrained proxy modeling

FI Syed, T Muther, AK Dahaghi, S Neghabhan - Fuel, 2022 - Elsevier
There are multiple parameters including reservoir characteristics, hydraulic fracture design,
injection solvent selection, and the enhanced oil recovery (EOR) operational design, etc …

Applications of artificial neural networks in the petroleum industry: a review

HH Alkinani, AT Al-Hameedi… - SPE Middle East oil …, 2019 - onepetro.org
Oil/gas exploration, drilling, production, and reservoir management are challenging these
days since most oil and gas conventional sources are already discovered and have been …

Application of polymeric relative permeability modifiers for water control purposes: Opportunities and challenges

MT Hayavi, A Kalantariasl, MR Malayeri - Geoenergy Science and …, 2023 - Elsevier
High water production during the extraction of hydrocarbon is an increasingly major concern
for the petroleum industry since it increases operating costs, causes water disposal …

The application of deep learning algorithms to classify subsurface drilling lost circulation severity in large oil field datasets

S Mardanirad, DA Wood, H Zakeri - SN Applied Sciences, 2021 - Springer
In this paper, we present how precise deep learning algorithms can distinguish loss
circulation severities in oil drilling operations. Lost circulation is one of the costliest …

An experimental investigation of asphaltene stability in heavy crude oil during carbon dioxide injection

S Fakher, M Ahdaya, M Elturki, A Imqam - Journal of Petroleum …, 2020 - Springer
Carbon dioxide (CO 2) injection is one of the most applied enhanced oil recovery methods
in the hydrocarbon industry, since it has the potential to increase oil recovery significantly …

Prediction of lost circulation prior to drilling for induced fractures formations using artificial neural networks

HH Alkinani, AT Al-Hameedi… - SPE Oklahoma City Oil …, 2019 - onepetro.org
Lost circulation is a complicated problem to be predicted with conventional statistical tools.
As the drilling environment is getting more complicated nowadays, more advanced …

[HTML][HTML] Application of artificial neural networks in the drilling processes: can equivalent circulation density be estimated prior to drilling?

HH Alkinani, ATT Al-Hameedi, S Dunn-Norman… - Egyptian Journal of …, 2020 - Elsevier
As the drilling environment became more challenging nowadays, managing equivalent
circulating density (ECD) is a key factor to minimize non-productive time (NPT) due to many …

Refracture candidate selection using hybrid simulation with neural network and data analysis techniques

W Yanfang, S Salehi - Journal of Petroleum Science and Engineering, 2014 - Elsevier
By now very few analytical models have been developed to select well refracture candidates
due to complicated multi-parameter relationships. In this study, we proposed a new method …

Artificial neural network for permeability damage prediction due to sulfate scaling

R Zabihi, M Schaffie, H Nezamabadi-Pour… - Journal of Petroleum …, 2011 - Elsevier
Waterflooding is an important oil recovery method, which is used to maintain reservoir
pressure and to increase oil productivity. One of the most common problems caused by …

Neuro-simulation modeling of chemical flooding

MS Karambeigi, R Zabihi, Z Hekmat - Journal of Petroleum Science and …, 2011 - Elsevier
Chemical flooding has proved to enhance oil recovery of reservoirs considerably.
Development strategies of this method are more efficient when they consider both aspects of …