A novel machine learning approach for detecting outliers, rebuilding well logs, and enhancing reservoir characterization

M Ali, P Zhu, M Huolin, H Pan, K Abbas… - Natural Resources …, 2023 - Springer
Irregular measurements may occur during the drilling process due to unconsolidated
formation resulting in poor signal recordings by the logging tool. This affects the quality of …

Machine learning methods for estimating permeability of a reservoir

H Khan, A Srivastav, A Kumar Mishra… - International Journal of …, 2022 - Springer
The prediction of permeability from the information of a well log is a crucial and extensive
task that is observed in the earth sciences. The permeability of a reservoir is greatly …

Determination of bubble point pressure & oil formation volume factor of crude oils applying multiple hidden layers extreme learning machine algorithms

S Rashidi, M Mehrad, H Ghorbani, DA Wood… - Journal of Petroleum …, 2021 - Elsevier
An important requirement of reservoir management is to understand the properties of
reservoir fluids and dependent phase behaviors. This makes it possible to determine the …

[HTML][HTML] 测井资料PSO-XGBoost 渗透率预测

谷宇峰, 张道勇, 鲍志东 - 石油地球物理勘探, 2021 - html.rhhz.net
渗透率预测模型主要分为物理模型和拟合模型. 物理模型基于测井理论, 能得到可靠的渗透率
预测值, 但推广性较差; 逐步迭代为经典的拟合算法, 能快速预测渗透率, 但难以确定各类测井 …

[HTML][HTML] Prediction of water saturation from well log data by machine learning algorithms: Boosting and super learner

F Hadavimoghaddam, M Ostadhassan… - Journal of Marine …, 2021 - mdpi.com
Intelligent predictive methods have the power to reliably estimate water saturation (Sw)
compared to conventional experimental methods commonly performed by petrphysicists …

Enhanced oil recovery by nanoparticles flooding: From numerical modeling improvement to machine learning prediction

B Alwated, MF El–Amin - Advances in Geo-Energy Research, 2021 - ager.yandypress.com
Nowadays, enhanced oil recovery using nanoparticles is considered an innovative
approach to increase oil production. This paper focuses on predicting nanoparticles …

A new data-driven predictor, PSO-XGBoost, used for permeability of tight sandstone reservoirs: A case study of member of chang 4+ 5, western Jiyuan Oilfield, Ordos …

Y Gu, D Zhang, Z Bao - Journal of Petroleum Science and Engineering, 2021 - Elsevier
Permeability is universally regarded as a critical analysis parameter for some geological
work such as formation characterization and oil deposit exploitation. It can be obtained by …

Estimation of hydrogen solubility in aqueous solutions using machine learning techniques for hydrogen storage in deep saline aquifers

MR Dehghani, H Nikravesh, M Aghel, M Kafi… - Scientific Reports, 2024 - nature.com
The porous underground structures have recently attracted researchers' attention for
hydrogen gas storage due to their high storage capacity. One of the challenges in storing …

Insights into the estimation of surface tensions of mixtures based on designable green materials using an ensemble learning scheme

R Soleimani, AH Saeedi Dehaghani - Scientific Reports, 2023 - nature.com
Precise estimation of the physical properties of both ionic liquids (ILs) and their mixtures is
crucial for engineers to successfully design new industrial processes. Among these …

Rock thermal properties from well-logging data accounting for thermal anisotropy

A Shakirov, E Chekhonin, Y Popov, E Popov… - Geothermics, 2021 - Elsevier
The limitations of the existing techniques for in situ rock thermal property measurements and
numerous cases with non-coring drilling determine the necessity for methods of rock thermal …