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Multivariate Time Series Forecasting of Oil Production Based on Ensemble Deep Learning and Genetic Algorithm
27/27 checkable references clean · checked 2026-08-28
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
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The 27 checked references that resolve
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Development of Oil Production Forecasting Method based on Deep Learning
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Multilayer Neural Network with Multi-Valued Neurons in time series forecasting of oil production
resolves10.3390/pr9071194
Optimized ANFIS Model Using Aquila Optimizer for Oil Production Forecasting
resolves10.1007/s13202-021-01405-w
Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm
resolves10.1016/j.jhydrol.2019.124288
Semi-analytical solution for productivity evaluation of a multi-fractured horizontal well in a bounded dual-porosity reservoir
resolves10.1007/s13369-021-05997-7
Box–Jenkins Methodology Application to Improve Crude Oil Production Forecasting: Case Study in a Colombian Field
resolves10.1109/TASE.2021.3077537
A Hybrid Prediction Method for Realistic Network Traffic With Temporal Convolutional Network and LSTM
resolves10.1016/j.promfg.2020.01.033
Deep Learning-based Production Forecasting in Manufacturing: a Packaging Equipment Case Study
resolves10.1016/j.petrol.2022.110757
Data-driven approach for hydrocarbon production forecasting using machine learning techniques
resolves10.2118/179739-PA
Production From a Fractured Well With Finite Fracture Conductivity in a Closed Reservoir: An Exact Analytical Solution for Pseudosteady-State Flow
resolves10.1007/s00500-020-04954-0
Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station
resolves10.1016/j.petrol.2017.08.037
Analytical model for production performance analysis of multi-fractured horizontal well in tight oil reservoirs
resolves10.1016/j.apm.2007.06.031
The impact of extreme weather on offshore production in the Gulf of Mexico
resolves10.3390/pr10061137
Forecasting Oil Production Flowrate Based on an Improved Backpropagation High-Order Neural Network with Empirical Mode Decomposition
resolves10.1016/j.neucom.2018.09.082
Time series forecasting of petroleum production using deep LSTM recurrent networks
resolves10.1109/ACCESS.2020.2968536
Hourly Heat Load Prediction Model Based on Temporal Convolutional Neural Network
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Risk analysis applied to petroleum exploration and production: an overview
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Short-Term Load Forecasting for Industrial Customers Based on TCN-LightGBM
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Ultra-short term wind power prediction applying a novel model named SATCN-LSTM
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Temporal convolution network based on attention mechanism for well production prediction
The 17 references without a DOI — listed, not checked
no DOI — not checkedref2
no DOI — not checkedA deep gated recurrent neural network for petroleum production forecasting
no DOI — not checkedref8
no DOI — not checkedShort-Term Electrical Load Forecasting Based on VMD and GRU-TCN Hybrid Network
no DOI — not checkedA review on application of data-driven models in hydrocarbon production forecast
no DOI — not checkedWell production forecasting based on ARIMA-LSTM model considering manual operations
no DOI — not checkedPrediction of reservoir key parameters in 'sweet spot' on the basis of particle swarm optimization to TCN-LSTM network
no DOI — not checkedParallel Spatio-Temporal Attention-Based TCN for Multivariate Time Series Prediction
no DOI — not checkedForecasting oil production using ensemble empirical model decomposition based Long Short-Term Memory neural network
no DOI — not checkedref25
no DOI — not checkedWell production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm
no DOI — not checkedref27
no DOI — not checkedPrediction on production of oil well with attention-CNN-LSTM
no DOI — not checkedref36
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no DOI — not checkedA Network Security Situation Prediction Method through the Use of Improved TCN and BiDLSTM
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