Similar papers
Open access
2026
Machine-Learning-Based Multi-Surrogate-Assisted Joint Optimization for Hydraulic Fracturing Design and Production Control
: The distribution of hydraulic fractures and production control strategies have significant influences on the fluid flow and production performance of low-permeability waterflooding reservoirs. Traditional approaches typically focus solely on fracture parameters while overlooking production control. To address this li...
Xiaopeng Ma, Bin Zhang, Jin-Sheng Zhao et al.
· Energy Engineering · 0 citations
Dec 2026
Predicting Inside-Pipe Displacement Efficiency with a Machine-Learning Model Using Experimental Data
The primary cementing process (PCP) is a crucial procedure in oil and gas well construction, providing well barriers and zonal isolation to ensure safe and efficient operations. However, achieving efficient displacement of yield-stress fluids, such as drilling mud and cement slurries, remains challenging due to com...
Hu Dai, Zhi-Bin Sun
· Journal of Energy Engineerin... · 0 citations
Conference
Aug 2026
Machine Learning–Based Rate of Penetration Prediction Using Multi-Well Field Data in Deviated Wells
A model is identified that not only reproduces historical data accurately but also yields correct responses under a diverse range of varying input parameters, and the proposed methodology establishes a reproducible basis for developing more reliable ROP forecasting tools for complex well trajectories.
Nayem Ahmed, Ramadan Ahmed, V. Soriano et al.
· SPE/IADC Asia Pacific Drilli... · 0 citations
Aug 2026
CO2 Pre-Fracturing Full Life-Cycle Simulation and Parameter Optimization Considering Geomechanics and Dynamic Fractures in Shale Oil Reservoirs
Hydraulic fracturing is essential for shale oil development, but conventional water-based fracturing fluids may cause formation damage and environmental concerns because of incomplete flowback. Employing CO2 as a prefracturing fluid is a feasible and promising approach. However, the enhanced oil recovery (EOR) perfor...
Li-Yao Fan, Fan Yang, Yu-Liang Su et al.
· Energy & Fuels · 0 citations
Open access
Sep 2026
Strain-Based Quantitative Inversion of Localized Corrosion Defects in Storage Tanks Using Finite Element-Driven Machine Learning
Wall thinning caused by corrosion changes the circumferential strain response of storage tanks, but nonlinear coupling among structural parameters, loading conditions, strain characteristics, and defect geometry makes direct inversion difficult. This paper develops a strain-based, finite element (FE)-based machine lear...
Li-Jie Zhu, Jian-Gang Sun, Xiao-Hui Shi et al.
· Applied Sciences · 0 citations
Open access
Sep 2026
Application of finite element modeling and deep learning for displacement estimation in deep excavations
This research demonstrates that the proposed DNN-FEM approach provides a highly accurate and computationally efficient tool for estimating Diaphragm Wall (DW) and soil displacements in deep excavation projects.
To Thanh Sang, Tuong Tran Kien
· The Transport and Communicat... · 0 citations