Intelligent hydraulic fracturing under industry 4.0—a survey and future directions
J Jia, Q Fan, J Jing, K Lei, L Wang - Journal of Petroleum Exploration and …, 2024 - Springer
This paper investigates the automation of hydraulic fracturing within the context of Industry
4.0, defining intelligent fracturing systems through three components: surface equipment …
4.0, defining intelligent fracturing systems through three components: surface equipment …
[HTML][HTML] Machine learning in petrophysics: Advantages and limitations
Abstract Machine learning provides a powerful alternative data-driven approach to
accomplish many petrophysical tasks from subsurface data. It can assimilate information …
accomplish many petrophysical tasks from subsurface data. It can assimilate information …
Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models
Well-log interpretation estimates in situ rock properties along well trajectory, such as
porosity, water saturation, and permeability, to support reserve-volume estimation …
porosity, water saturation, and permeability, to support reserve-volume estimation …
Sonic Well-Log Imputation Through Machine-Learning-Based Uncertainty Models
Sonic well logs provide critical information to calibrate seismic data and support
geomechanical characterization. Advanced subsurface data analytics and machine learning …
geomechanical characterization. Advanced subsurface data analytics and machine learning …
Unsupervised time series clustering, class-based ensemble machine learning, and petrophysical modeling for predicting shear sonic wave slowness in …
S Bhattacharya - Geophysics, 2022 - library.seg.org
Shear sonic logs are critical for formation evaluation, rock physics, quantitative reservoir
characterization, and geomechanical studies. Although empirical and conventional machine …
characterization, and geomechanical studies. Although empirical and conventional machine …
Comparative study of machine-learning-based methods for log prediction
V Simoes, H Maniar, A Abubakar, T Zhao - Petrophysics, 2023 - onepetro.org
Improving data quality during log preprocessing is an important task that can consume most
of the time of the petrophysicist, with a high impact on the final interpretation. As part of the …
of the time of the petrophysicist, with a high impact on the final interpretation. As part of the …
Well-Log-Based Reservoir Property Estimation With Machine Learning: A Contest Summary
Well logs are processed and interpreted to estimate in-situ reservoir properties, which are
essential for reservoir modeling, reserve estimation, and production forecasting. While the …
essential for reservoir modeling, reserve estimation, and production forecasting. While the …
An Unsupervised Machine-Learning Workflow for Outlier Detection and Log Editing With Prediction Uncertainty
R Akkurt, TT Conroy, D Psaila, A Paxton, J Low… - Petrophysics, 2023 - onepetro.org
Recent advances in data science and machine learning (ML) have brought the benefits of
these technologies closer to the mainstream of petrophysics. ML systems, where decisions …
these technologies closer to the mainstream of petrophysics. ML systems, where decisions …