QUANTUM OPTIMIZATION FOR THE REDUNDANCY ALLOCATION PROBLEM IN SMART COMPLETION SYSTEMS

- 326087
Extended Abstracts (EA)
Download
Favorite this paper
How to cite this paper?
Abstract

The Oil and Gas (O&G) industry demands reliable systems. In this context, the Redundancy Allocation Problem (RAP) emerges as a mathematical formulation that enables the identification of reliability-maximizing scenarios for these systems. However, due to its combinatorial nature and NP-hard complexity, it is necessary to explore efficient approaches to solve it. This work investigates the application of quantum optimization for solving RAP in electrical intelligent completion (SCI-E) systems in the offshore industry, with emphasis on their multiple subsystems. The RAP formulation was adapted to the QUBO (Quadratic Unconstrained Binary Optimization) model and solved using the QAOA (Quantum Approximate Optimization Algorithm) with the COBYLA optimizer. Simulations were performed on IBM's quantum simulator using a 21-qubit instance. Finally, the results indicate that, despite current limitations, the quantum approach holds potential for solving combinatorial problems in the O&G sector.

Share your ideas or questions with the authors!

Did you know that the greatest stimulus in scientific and cultural development is curiosity? Leave your questions or suggestions to the author!

Sign in to interact

Have a question or suggestion? Share your feedback with the authors!

Programme
08:00 to 09:40 on 10/06/2025
Bromélia
Institutions
  • 1 UFPE
  • 2 Universidade Federal de Pernambuco
  • 3 Universidade Federal de Pernambuco - UFPE
  • 4 CEERMA/NT-CAA/UFPE
  • 5 CEERMA/DEP/UFPE
Track
  • 26. SE-QPO
Keywords
Quantum optimization
Redundancy allocation problem
Oil & Gas Industry