Hybrid Framework for Enhanced Dynamic Optimization of Intelligent Completion Design in Multilateral Wells with Multiple Types of Flow Control Devices

Jamal Ahdeema, Morteza Haghighat Sefat and Khafiz Muradov ()
Additional contact information
Jamal Ahdeema: Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK
Morteza Haghighat Sefat: Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK
Khafiz Muradov: Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK

Energies, 2023, vol. 16, issue 20, 1-25

Abstract: Multilateral wells (MLWs) equipped with multiple flow control devices (FCDs) are becoming increasingly favored within the oil sector due to their ability to enhance well-to-reservoir exposure and effectively handle unwanted fluid breakthrough. However, combining various types of FCDs in multilateral wells poses a complex optimization problem with a large number of highly correlated control variables and a computationally expensive objective function. Consequently, standard optimization algorithms, including metaheuristic and gradient-based approaches, may struggle to identify an optimal solution within a limited computational resource. This paper introduces a novel hybrid optimization (HO) framework combining particle swarm optimization (PSO) and Simultaneous Perturbation Stochastic Approximation (SPSA). It is developed to efficiently optimize the completion design of MLWs with various FCDs while overcoming the individual limitations of each optimization algorithm. The proposed framework is further enhanced by employing surrogate modelling and global sensitivity analysis to identify critical parameters (i.e., highly sensitive) that greatly affect the objective function. This allows for a focused optimization effort on these key parameters, ultimately enhancing global optimization performance. The performance of the novel optimization framework is evaluated using the Olympus benchmark reservoir model. The model is developed by three intelligent dual-lateral wells, with inflow control devices (ICDs) installed within the laterals and interval control valves (ICVs) positioned at the lateral junctions. The results show that the proposed hybrid optimization framework outperforms all industry-standard optimization techniques, achieving a Net Present Value of approximately USD 1.94 billion within a limited simulation budget of 2500 simulation runs. This represents a substantial 26% NPV improvement compared to the open-hole case (USD 1.54 billion NPV). This improvement is attributed to more efficient water breakthrough management, leading to a notable 24% reduction in cumulative water production and, consequently, a 26% increase in cumulative oil production.

Keywords: inflow control devices; inflow control valves; intelligent completion; advanced wells; hybrid optimization; proxy modelling; optimization algorithms; Olympus field model; multilateral wells; global sensitivity analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/20/7189/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/20/7189/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:20:p:7189-:d:1264673

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().