Non-Vertical Well Trajectory Design Based on Multi-Objective Optimization
Source abstract
Abstract
The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. In this paper, a multi-objective wellbore trajectory optimization mathematical model is established, which takes into account the five factors of wellbore trajectory length, friction, torque, trajectory complexity, and target accuracy. A DR-NSGA-III-MGA algorithm (dynamic reference NSGA-III with multi-granularity adaptation) is proposed. By introducing multi-granularity reference vector generation and an information entropy-guided search direction adaptation mechanism, the performance of the algorithm in the complex target space is improved, and the three-stage wellbore trajectory is optimized. Simulation experiments show that the DR-NSGA-III-MGA algorithm is stable in a variety of complex problems, while maintaining good convergence, and has good generalization ability and practical application value.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Drilling and Well Engineering · Reservoir Engineering and Simulation Methods · Oil and Gas Production Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematics and Statistics, Northeast Petroleum University, Daqing 163318, China
School of Geosciences, Northeast Petroleum University, Daqing 163318, China
NEPU Sanya Offshore Oil & Gas Research Institute, Northeast Petroleum University, Sanya 572000, China
Funding
National Natural Science Foundation of China · Guiding Innovation Fund of Northeast Petroleum University: Intelligent Optimization Design of Horizontal Well Trajectory
References (34)
Show source-provided references
1. Horizontal section length optimization design for horizontal wells using genetic algorithms
2. Vector-based three-dimensional (3D) well-path optimization assisted by geological modelling and borehole-log extraction10.1016/j.upstre.2021.100053 ↗
3. Sha, L.X., Zhang, Q.Z., Li, L., and Qiu, S. (2024). Complex Wellbore Trajectory Optimization Method Based on Fast Adaptive Quantum Genetic Algorithm. (201710132117), CN Patent.
4. FSQGA-based 3D complexity wellbore trajectory optimization10.2516/ogst/2018008 ↗
5. Selection of optimal well trajectory using multi-objective genetic algorithm and TOPSIS method10.1007/s13369-023-08149-1 ↗
6. Hybrid machine learning framework for multi-well trajectory optimization in an unconventional field10.1016/j.jgsce.2024.205443 ↗
7. Particle swarm optimization10.1109/ICNN.1995.488968 ↗
8. Ding, H. (2004). Research on Optimization Design and Decision-Making Analysis of Nonlinear Well Trajectory. [Master’s Thesis, Dalian University of Technology].
9. Designing and optimizing deviated wellbore trajectories using novel particle swarm algorithms10.1016/j.jngse.2014.05.029 ↗
10. Borehole trajectory prediction and 3D visualization system development
11. Method for designing the optimal trajectory for drilling a horizontal well based on particle swarm optimization (PSO) and analytic hierarchy process (AHP)10.1007/s10553-019-01008-6 ↗
12. Cellular automata-based multi-objective hybrid Grey Wolf Optimization and particle swarm optimization algorithm for wellbore trajectory optimization10.1016/j.jngse.2020.103695 ↗
13. Application of fast marching method and quality map to well trajectory optimization with a novel well parametrization10.1016/j.geoen.2023.212301 ↗
14. Ant system: Optimization by a colony of cooperating agents10.1109/3477.484436 ↗
15. Chaos-based ant colony hybrid optimization method
16. Function optimization with hybrid and improved ant colony algorithm
17. Research on the application of ant colony optimization algorithm in WSN routing
18. Li, C.Y. (2019). Research on the Application of Ant Colony Algorithm in Wellbore Trajectory Planning. [Master’s Thesis, Xi’an Shiyou University].
19. 3D well path design using a multi-objective genetic algorithm10.1016/j.jngse.2015.08.051 ↗
20. Multi-objective optimization of oil well drilling using elitist non-dominated sorting genetic algorithm10.1007/s12182-014-0321-x ↗
21. Huang, W.D., Wu, M., Cheng, J., Chen, X., Cao, W., Hu, Y., and Gao, H. (2017, January 17–20). Multi-objective drilling trajectory optimization based on NSGA-II. Proceedings of the 2017 11th Asian Control Conference (ASCC), Gold Coast, QLD, Australia.10.1109/ASCC.2017.8287347 ↗
22. Multi-objective cellular particle swarm optimization for wellbore trajectory design10.1016/j.asoc.2019.01.010 ↗
23. Application of adaptive grid-based multi-objective particle swarm optimization algorithm for directional drilling trajectory design10.1016/j.geoen.2023.211431 ↗
24. Sha, L.X., Li, W.Y., and Zhang, Q.Z. (2019). Complex Wellbore Trajectory Optimization Method Based on Improved Multi-Objective Particle Swarm Optimization Algorithm. (201910410779.7), CN Patent, Available online: https://www.xjishu.com/zhuanli/54/201910410779.html.
25. Yin, H.U., Fan, T., Zhao, X., and Li, Q. (2024). Multi-objective intelligent dynamic optimization design for well trajectory while drilling in horizontal wells. Res. Sq., preprint.10.21203/rs.3.rs-3865026/v1 ↗
26. Guan, Z., Chen, T., and Liao, H. (2021). Theory and Technology of Drilling Engineering, Springer.10.1007/978-981-15-9327-7 ↗
27. Ren, Y.F. (2024). Research on Intelligent Design and Optimization Method of Wellbore Trajectory, Yangtze University.
28. Collette, Y., and Siarry, P. (2004). Multiobjective Optimization: Principles and Case Studies, Springer Science & Business Media.10.1007/978-3-662-08883-8 ↗
29. A review of multi-objective optimization: Methods and its applications10.1080/23311916.2018.1502242 ↗
30. Miettinen, K. (1999). Nonlinear Multiobjective Optimization, Springer Science & Business Media.10.1007/978-1-4615-5563-6 ↗
31. Bezerra, L.C.T., López-Ibáñez, M., and Stützle, T. (2017, January 19–22). An empirical assessment of the properties of inverted generational distance on multi-and many-objective optimization. Proceedings of the International Conference on Evolutionary Multi-criterion Optimization, Münster, Germany.10.1007/978-3-319-54157-0_3 ↗
32. Friction and torque prediction and analysis of Kendong 405-Ping 1 extended-reach well
33. Schulze-Riegert, R., Bagheri, M., Krosche, M., Kueck, N., and Ma, D. (2011, January 21–23). Multiple-objective optimization applied to well path design under geological uncertainty. Proceedings of the SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, The Woodlands, TX, USA.10.2118/141712-MS ↗
34. Samuel, G.R. (2009, January 17–19). Ultra-extended-reach drilling (u-ERD: Tunnel in the Earth)—A new well-path design. Proceedings of the SPE/IADC Drilling Conference and Exhibition, Amsterdam, The Netherlands. SPE-119459-MS.10.2118/119459-MS ↗