Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges

P Lu, L Ye, Y Zhao, B Dai, M Pei, Y Tang - Applied Energy, 2021 - Elsevier
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …

A review on shale oil and gas characteristics and molecular dynamics simulation for the fluid behavior in shale pore

S Sun, S Liang, Y Liu, D Liu, M Gao, Y Tian… - Journal of Molecular …, 2023 - Elsevier
Shale oil and gas primarily exist in nanoscale pore-fracture networks. Thus, it is essential to
clarify the flow behavior of hydrocarbon in confined nanopores. This paper summarizes …

A systematic data-driven approach for production forecasting of coalbed methane incorporating deep learning and ensemble learning adapted to complex production …

S Du, J Wang, M Wang, J Yang, C Zhang, Y Zhao… - Energy, 2023 - Elsevier
Coalbed methane (CBM) as an essential component of clean energy is of strategic
significance to global sustainable development, with its production forecast being the basis …

Sticky layers affect oil transport through the nanopores of realistic shale kerogen

S Wang, Y Liang, Q Feng, F Javadpour - Fuel, 2022 - Elsevier
Understanding the transport mechanism of hydrocarbons through kerogen nanopores is
crucial to shale oil production. However, existing studies primarily focus on single …

Unconventional hydrocarbon resources: geological statistics, petrophysical characterization, and field development strategies

T Muther, HA Qureshi, FI Syed, H Aziz, A Siyal… - Journal of Petroleum …, 2022 - Springer
Hydrocarbons exist in abundant quantity beneath the earth's surface. These hydrocarbons
are generally classified as conventional and unconventional hydrocarbons depending upon …

Long short-term memory suggests a model for predicting shale gas production

R Yang, X Liu, R Yu, Z Hu, X Duan - Applied Energy, 2022 - Elsevier
Predicting the production behaviors of shale gas wells is of great importance for further
developing future unconventional hydrocarbon strategies. An accurate prediction …

Advances in the application of deep learning methods to digital rock technology.

X Li, B Li, F Liu, T Li, X Nie - Advances in Geo-Energy …, 2023 - search.ebscohost.com
Digital rock technology is becoming essential in reservoir engineering and petrophysics.
Three-dimensional digital rock reconstruction, image resolution enhancement, image …

Micromechanism of partially hydrolyzed polyacrylamide molecule agglomeration morphology and its impact on the stability of crude oil− water interfacial film

Z Wang, Y Xu, Y Gan, X Han, W Liu, H Xin - Journal of Petroleum Science …, 2022 - Elsevier
Based on the background of oilfield chemical flooding produced liquid treatment projects, to
achieve new insight into the micromechanism of the impact of polymer molecules applied to …

A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction

G Zhou, Z Guo, S Sun, Q Jin - Applied Energy, 2023 - Elsevier
In the coming decades, the demand for shale oil will likely surge because of predicted
increases in the global population and productivity. Efficiently predicting shale oil production …

[HTML][HTML] Shale gas production evaluation framework based on data-driven models

YW He, ZY He, Y Tang, YJ Xu, JC Long… - Petroleum Science, 2023 - Elsevier
Increasing the production and utilization of shale gas is of great significance for building a
clean and low-carbon energy system. Sharp decline of gas production has been widely …