Well production forecasting based on ARIMA-LSTM model considering manual operations

Citations

Cited by:

1. Wang, Yong & Yang, Zhongsen & Wang, Li & Ma, Xin & Wu, Wenqing & Ye, Lingling & Zhou, Ying & Luo, Yongxian, 2022. "Forecasting China's energy production and consumption based on a novel structural adaptive Caputo fractional grey prediction model," Energy, Elsevier, vol. 259(C).
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3. Soheila Khajoui & Saeid Dehyadegari & Sayyed Abdolmajid Jalaee, 2024. "Predicting the impact of e-commerce indices on international trade in Iran and other selected members of the Organization for Economic Co-operation and Development (OECD) by using the artificial intel," Papers 2403.20310, arXiv.org.
4. Fargalla, Mandella Ali M. & Yan, Wei & Deng, Jingen & Wu, Tao & Kiyingi, Wyclif & Li, Guangcong & Zhang, Wei, 2024. "TimeNet: Time2Vec attention-based CNN-BiGRU neural network for predicting production in shale and sandstone gas reservoirs," Energy, Elsevier, vol. 290(C).
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6. Soheila Khajoui & Saeid Dehyadegari & Sayyed Abdolmajid Jalaee, 2024. "Forecasting Imports in OECD Member Countries and Iran by Using Neural Network Algorithms of LSTM," Papers 2402.01648, arXiv.org.
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13. Zhao, Xinxing & Li, Kainan & Ang, Candice Ke En & Cheong, Kang Hao, 2023. "A deep learning based hybrid architecture for weekly dengue incidences forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
14. Anna Samnioti & Vassilis Gaganis, 2023. "Applications of Machine Learning in Subsurface Reservoir Simulation—A Review—Part II," Energies, MDPI, vol. 16(18), pages 1-53, September.
15. Zhuang, Xinyu & Wang, Wendong & Su, Yuliang & Li, Yuan & Dai, Zhenxue & Yuan, Bin, 2024. "Spatio-temporal sequence prediction of CO2 flooding and sequestration potential under geological and engineering uncertainties," Applied Energy, Elsevier, vol. 359(C).
16. Hai Wang & Shengnan Chen, 2023. "Insights into the Application of Machine Learning in Reservoir Engineering: Current Developments and Future Trends," Energies, MDPI, vol. 16(3), pages 1-11, January.
17. Pan, Shaowei & Yang, Bo & Wang, Shukai & Guo, Zhi & Wang, Lin & Liu, Jinhua & Wu, Siyu, 2023. "Oil well production prediction based on CNN-LSTM model with self-attention mechanism," Energy, Elsevier, vol. 284(C).
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20. Wen, Kai & Jiao, Jianfeng & Zhao, Kang & Yin, Xiong & Liu, Yuan & Gong, Jing & Li, Cuicui & Hong, Bingyuan, 2023. "Rapid transient operation control method of natural gas pipeline networks based on user demand prediction," Energy, Elsevier, vol. 264(C).
21. Lv, Sheng-Xiang & Wang, Lin, 2022. "Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization," Applied Energy, Elsevier, vol. 311(C).
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23. Li, Ruilian & Zeng, Deliang & Li, Tingting & Ti, Baozhong & Hu, Yong, 2023. "Real-time prediction of SO2 emission concentration under wide range of variable loads by convolution-LSTM VE-transformer," Energy, Elsevier, vol. 269(C).
24. Li, Ye & Chen, Yiyan & Lean, Hooi Hooi, 2024. "Geopolitical risk and crude oil price predictability: Novel decomposition ensemble approach based ternary interval number series," Resources Policy, Elsevier, vol. 92(C).
25. Chin-Wen Liao & I-Chi Wang & Kuo-Ping Lin & Yu-Ju Lin, 2021. "A Fuzzy Seasonal Long Short-Term Memory Network for Wind Power Forecasting," Mathematics, MDPI, vol. 9(11), pages 1-15, May.
26. Hou, Lei & Cheng, Yiyan & Wang, Xiaoyu & Ren, Jianhua & Geng, Xueyu, 2022. "Effect of slickwater-alternate-slurry injection on proppant transport at field scales: A hybrid approach combining experiments and deep learning," Energy, Elsevier, vol. 242(C).
27. Lu, Yutian & Wang, Bo & Zhao, Yingying & Yang, Xiaochen & Li, Lizhe & Dong, Mingzhi & Lv, Qin & Zhou, Fujian & Gu, Ning & Shang, Li, 2022. "Physics-informed surrogate modeling for hydro-fracture geometry prediction based on deep learning," Energy, Elsevier, vol. 253(C).
28. Mimoun Benali & Lahboub Karima, 2024. "Modelling Stock Prices of Energy Sector using Supervised Machine Learning Techniques," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 594-602, March.
29. Yan Guo & Dezhao Tang & Wei Tang & Senqi Yang & Qichao Tang & Yang Feng & Fang Zhang, 2022. "Agricultural Price Prediction Based on Combined Forecasting Model under Spatial-Temporal Influencing Factors," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
30. Bingbing Wang & Xiangjie Lu & Yanzhao Ren & Sha Tao & Wanlin Gao, 2022. "Prediction Model and Influencing Factors of CO 2 Micro/Nanobubble Release Based on ARIMA-BPNN," Agriculture, MDPI, vol. 12(4), pages 1-18, March.