Applications of Machine Learning in Sweet-Spots Identification: A Review

H Khanjar - SPE Journal, 2024 - onepetro.org
The identification of sweet spots, areas within a reservoir with the highest production
potential, has been revolutionized by the integration of machine learning (ML) algorithms …

Comparison of different machine learning algorithms for predicting the SAGD production performance

Z Huang, Z Chen - Journal of Petroleum Science and Engineering, 2021 - Elsevier
Abstract Steam Assisted Gravity Drainage (SAGD) is a typical thermal recovery process
consisting of an upper horizontal injector and a lower horizontal producer, which heats and …

Downhole quantitative evaluation of gas kick during deepwater drilling with deep learning using pilot-scale rig data

Q Yin, J Yang, M Tyagi, X Zhou, N Wang, G Tong… - Journal of Petroleum …, 2022 - Elsevier
Gas kick occurs frequently during deep-water drilling operations caused by the lack of safe
margin between pore pressure and leakage pressure. The existing research is limited to gas …

Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification

T Astsauri, M Habiburrahman, AF Ibrahim, Y Wang - Scientific Reports, 2024 - nature.com
Reservoir characterization, essential for understanding subsurface heterogeneity, often
faces challenges due to scale-dependent variations. This study addresses this issue by …

Gamma ray log generation from drilling parameters using deep learning

AU Osarogiagbon, O Oloruntobi, F Khan… - Journal of Petroleum …, 2020 - Elsevier
Lithology identification plays a vital role in defining the petroleum reservoir. Although well
logging represents the traditional means of obtaining petrophysical data for lithology …

Data-driven proxy model for waterflood performance prediction and optimization using Echo State Network with Teacher Forcing in mature fields

L Deng, Y Pan - Journal of Petroleum Science and Engineering, 2021 - Elsevier
Waterflood has been widely applied across the world as the most important secondary
recovery process to improve reservoir performance. The schemes applied to waterflood …

Optimization of fracturing parameters with machine-learning and evolutionary algorithm methods

Z Dong, L Wu, L Wang, W Li, Z Wang, Z Liu - Energies, 2022 - mdpi.com
Oil production from tight oil reservoirs has become economically feasible because of the
combination of horizontal drilling and multistage hydraulic fracturing. Optimal fracture design …

A novel data-driven pressure/rate deconvolution algorithm to enhance production data analysis in unconventional reservoirs

Y Pan, L Deng, WJ Lee - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Horizontal wells with hydraulic fractures enable economical hydrocarbon extraction from
unconventional reservoirs, and the associated transient production data is a reliable source …

Modelling of the impact of stress concentration on permeability in porous medium based on machine learning method

H Qu, Y Peng, J Huang, Z Pan, F Zhou - Geoenergy Science and …, 2023 - Elsevier
The behavior of stress-dependent permeability has been an important research topic for
oil/gas production. The majority of permeability models for porous media have been …

Identification of karst cavities from 2D seismic wave impedance images based on Gradient-Boosting Decision Trees Algorithms (GBDT): Case of ordovician fracture …

AKF Kouassi, L Pan, X Wang, Z Wang, AK Mulashani… - Energies, 2023 - mdpi.com
The precise characterization of geological bodies in fracture-vuggy carbonates is
challenging due to their high complexity and heterogeneous distribution. This study aims to …