Artificial intelligence techniques and their application in oil and gas industry

S Choubey, GP Karmakar - Artificial Intelligence Review, 2021 - Springer
Data are being continuously generated from various operational steps in the oil and gas
industry. The recordings of these data and their proper utilization have become a major …

Applications of machine learning for facies and fracture prediction using Bayesian Network Theory and Random Forest: Case studies from the Appalachian basin …

S Bhattacharya, S Mishra - Journal of Petroleum Science and Engineering, 2018 - Elsevier
Identification and prediction of facies and fractures are critical to subsurface geosystems
analysis and hydrocarbon exploration. However, accurate prediction of facies and fractures …

Lithofacies classification and sequence stratigraphic description as a guide for the prediction and distribution of carbonate reservoir quality: a case study of the Upper …

MI Abdel-Fattah, AQ Mahdi, MA Theyab… - Journal of Petroleum …, 2022 - Elsevier
Abstract In the East Baghdad oilfield of central Iraq, the Upper Cretaceous Khasib Formation
is the largest producing carbonate reservoir. The basic architecture of the “Khasib …

Modeling of swab and surge pressures: A survey

A Mohammad, R Davidrajuh - Applied Sciences, 2022 - mdpi.com
Swab and surge pressure fluctuations are decisive during drilling for oil. The axial
movement of the pipe in the wellbore causes pressure fluctuations in wellbore fluid; these …

Status of data-driven methods and their applications in oil and gas industry

K Balaji, M Rabiei, V Suicmez, CH Canbaz… - SPE Europec featured …, 2018 - onepetro.org
Data-driven methods serve as robust tools to turn data into knowledge. Historical data
generally has not been used in an effective way in analyzing processes due to lack of a well …

A method for judging the effectiveness of complex tight gas reservoirs based on geophysical logging data and using the L block of the Ordos Basin as a case study

Q Zhao, J Guo, Z Zhang - Processes, 2023 - mdpi.com
As an important unconventional oil and gas resource, the tight gas reservoir faces many
technical challenges due to its low porosity, low permeability, and strong heterogeneity …

A comprehensive methodology for reservoir cut-off determination

M Zeyghami, M Taghizadeh Sarvestani - Journal of Petroleum Exploration …, 2023 - Springer
The main objective of net pay determination, as an important step of any reservoir study, is to
exclude non-reservoir intervals so that better results are obtained from reservoir …

Analysis of alternative strategies applied to Naïve-Bayes classifier into the recognition of electrofacies: Application in well-log data at Recôncavo Basin, North-East …

MM Ramos, R Bijani, FV Santos, WM Lupinacci… - Geoenergy Science and …, 2023 - Elsevier
This paper is concerned with the applicability of different strategies to improve the definition
of prior probabilities and/or likelihoods of naïve Bayes (NB) classifiers. Standard NB method …

Net pay determination by artificial neural network: Case study on Iranian offshore oil fields

P Masoudi, B Arbab, H Mohammadrezaei - Journal of Petroleum Science …, 2014 - Elsevier
Determining productive zones has always been a challenge for petrophysicists. On the other
hand, Artificial Neural Networks are powerful tools in solving identification problems. In this …

A structured mobility-based methodology for quantification of net-pay cutoff in petroleum reservoirs

H Saboorian-Jooybari - SPE Reservoir Evaluation & Engineering, 2017 - onepetro.org
Petrophysical cutoffs of a hydrocarbon reservoir are among the key parameters to determine
net pay, net-to-gross ratio (NTG), original hydrocarbon (s) in place (OHIP), and reserves …