Research graph
References from Full-field petroleum production forecasting: Is deep learning all you need?. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
2018 · External reference
Probabilistic well production forecasting in volve field using temporal fusion transformer deep learning models
2023 · External reference
Multivariate time series modelling approach for production forecasting in unconventional resources
2020 · External reference
Impact of geological variables in controlling oil-reservoir performance: an insight from a machine-learning technique
10.2118/201196-pa · 2020 · External reference
TabNet: attentive interpretable tabular learning
2021 · External reference
Analysis of decline curves
10.2118/945228-g · 1945 · External reference
Deep learning-based and kernel-based proxy models for nonlinearly constrained life-cycle production optimization
2023 · External reference
Support vector regression
2015 · External reference
Review of application of artificial intelligence techniques in petroleum operations
10.1016/j.ptlrs.2022.07.002 · 2023 · External reference
Deep learning of representations for unsupervised and transfer learning
2011 · External reference
A review on application of data-driven models in hydrocarbon production forecast
10.1016/j.petrol.2022.110296 · 2022 · External reference
Evaluating time series forecasting models: an empirical study on performance estimation methods
10.1007/s10994-020-05910-7 · 2019 · External reference
Unresolved reference
2008 · External reference
A generalized neural tangent kernel analysis for two-layer neural networks
2020 · External reference
Unresolved reference
2017 · External reference
Multi-horizon well performance forecasting with temporal fusion transformers
2024 · External reference
Unresolved reference
1978 · External reference
Oil production forecast models based on sliding window regression
10.1016/j.petrol.2020.107916 · 2020 · External reference
The role of Occam’s razor in knowledge discovery
10.1023/a:1009868929893 · 1999 · External reference
Unresolved reference
2018 · External reference
Multi-step forecasting for big data time series based on ensemble learning
10.1016/j.knosys.2018.10.009 · 2019 · External reference
Unresolved reference
2017 · External reference
Unresolved reference
2016 · External reference
Why do tree-based models still outperform deep learning on tabular data?
2022 · External reference
Unresolved reference
2009 · External reference
Unresolved reference
2009 · External reference
Unresolved reference
2024 · External reference
A state-of-the art literature review on capacitance resistance models for reservoir characterization and performance forecasting
10.3390/en11123368 · 2018 · External reference
A stability principle for learning under non-stationarity
2023 · External reference
A machine learning approach to real-time uncertainty assessment of SAGD forecasts
2022 · External reference
Unresolved reference
2021 · External reference
Unresolved reference
2022 · External reference
Unresolved reference
2019 · External reference
New forecasting method for liquid rich shale gas condensate reservoirs with data driven approach using principal component analysis
10.1016/j.jngse.2017.01.014 · 2017 · External reference
A new metric of absolute percentage error for intermittent demand forecasts
10.1016/j.ijforecast.2015.12.003 · 2016 · External reference
The effect of intrinsic dataset properties on generalization: unraveling learning differences between natural and medical images
2024 · External reference
The bellkor solution to the netflix grand prize
2009 · External reference
Data-driven technique estimates skin factor and average pressure during oil-flowing periods
10.1016/j.petrol.2022.111061 · 2022 · External reference
Machine learning forecasts oil rate in mature onshore field jointly driven by water and steam injection
2019 · External reference
Application of machine learning to oil production forecast under uncertainties-the linear model
2019 · External reference
Attention-based LSTM network-assisted time series forecasting models for petroleum production
10.1016/j.engappai.2023.106440 · 2023 · External reference
Simple and scalable predictive uncertainty estimation using deep ensembles
2017 · External reference
An experimental review on deep learning architectures for time series forecasting
10.1142/s0129065721300011 · 2021 · External reference
A critical review of physics-informed machine learning applications in subsurface energy systems
2023 · External reference
Hyperparameter selection in continual learning
2024 · External reference
A machine learning analysis based on big data for eagle ford shale formation
2019 · External reference
Hydrocarbon production dynamics forecasting using machine learning: a state-of-the-art review
2023 · External reference
Data mining: a novel strategy for production forecast in tight hydrocarbon resource in Canada by random forest analysis
2020 · External reference
Time-series forecasting with deep learning: a survey
10.1098/rsta.2020.0209 · 2021 · External reference
Unresolved reference
2022 · External reference
A systematic machine learning method for reservoir identification and production prediction
2022 · External reference
Evaluating the relationship between well parameters and production using multivariate statistical models: a middle bakken and three forks case history
2016 · External reference
How to avoid machine learning pitfalls: a guide for academic researchers
2021 · External reference
Unresolved reference
2018 · External reference
Machine learning to rate and predict the efficiency of waterflooding for oil production
10.3390/en15031199 · 2022 · External reference
The accuracy of extrapolation (time series) methods: results of a forecasting competition
10.1002/for.3980010202 · 1982 · External reference
Unresolved reference
2012 · External reference
Deep double descent: where bigger models and more data hurt
2019 · External reference
Application of machine learning algorithms and integrated production modelling to improve accuracy of liquid production rate measurements using multiphase flow meters
2021 · External reference
Well production forecast in volve field: application of rigorous machine learning techniques and metaheuristic algorithm
10.1016/j.petrol.2021.109468 · 2022 · External reference
A comparative machine learning study for time series oil production forecasting: ARIMA, LSTM, and prophet
10.1016/j.cageo.2022.105126 · 2022 · External reference
An intelligent data driven approach for production prediction
2019 · External reference
Unresolved reference
2012 · External reference
Unresolved reference
2023 · External reference
Nonlinear regression algorithm for uncertainty analysis in production data measurements, Estancia Cholita, Santa Cruz, Argentina
2020 · External reference
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
10.1038/s42256-019-0048-x · 2018 · External reference
Time series forecasting of petroleum production using deep LSTM recurrent networks
10.1016/j.neucom.2018.09.082 · 2019 · External reference
Time series prediction using support vector machines: a survey
10.1109/mci.2009.932254 · 2009 · External reference
Nonparametric regression using deep neural networks with ReLU activation function
2020 · External reference
Unresolved reference
2025 · External reference
Green AI
10.1145/3381831 · 2020 · External reference
Application of rough neural network to forecast oil production rate of an oil field in a comparative study
2021 · External reference
Application of machine learning and artificial intelligence in oil and gas industry
10.1016/j.ptlrs.2021.05.009 · 2021 · External reference
Assessment of big data analytics based ensemble estimator module for the real-time prediction of reservoir recovery factor
2019 · External reference
Attention is all you need
2017 · External reference
Insights into the application of machine learning in reservoir engineering: current developments and future trends
10.3390/en16031392 · 2023 · External reference
Production prediction at ultra-high water cut stage via recurrent neural network
10.1016/s1876-3804(20)60119-7 · 2020 · External reference
Data-driven deep-learning forecasting for oil production and pressure
10.1016/j.petrol.2021.109937 · 2022 · External reference
Deep learning is not So mysterious or different
2025 · External reference
Unresolved reference
2000 · External reference
A survey on green deep learning
2021 · External reference
A data-driven shale gas production forecasting method based on the multi-objective random forest regression
10.1016/j.petrol.2020.107801 · 2021 · External reference
Measurement of high-water-content oil-water two-phase flow by electromagnetic flowmeter and differential pressure based on phase-isolation
10.1016/j.flowmeasinst.2022.102142 · 2022 · External reference
Hybrid deep neural networks for reservoir production prediction
10.1016/j.petrol.2020.108111 · 2021 · External reference
Meta learning using deep N-BEATS model for production forecasting with limited history
2023 · External reference
Are transformers effective for time series forecasting?
2022 · External reference
Pros and cons of applying proxy-models as a substitute for full reservoir simulations
2009 · External reference
