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A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage
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Optimizing Workover Rig Fleet Sizing and Scheduling Using Deterministic and Stochastic Programming Models.

Miguel A Fernández Pérez1,2, Fabricio Oliveira3, Silvio Hamacher1

  • 1Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, RJ 22451-900, Brazil.

Industrial & Engineering Chemistry Research
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Summary
This summary is machine-generated.

This study introduces deterministic and stochastic programming models to optimize oil well workover rig operations. The models efficiently determine rig fleet size and scheduling, maximizing production and minimizing costs under uncertainty.

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Area of Science:

  • Operations Research
  • Petroleum Engineering

Background:

  • The workover rig problem is a critical and complex challenge in the oil and gas industry.
  • Efficient management of workover rigs is essential for maximizing oil production and minimizing operational costs.

Purpose of the Study:

  • To develop and evaluate deterministic and stochastic programming models for optimizing the workover rig problem.
  • To determine optimal rig fleet size and scheduling strategies considering operational costs and production maximization.

Main Methods:

  • An integer linear programming model was formulated for the deterministic approach.
  • A two-stage stochastic programming model was developed to address uncertainty in intervention times.
  • Various scenario-generation methods were compared within the stochastic framework.
  • Experiments were conducted using real-world problem instances.

Main Results:

  • The proposed models effectively address large-scale instances of the workover rig problem.
  • Quality solutions were achieved within computationally reasonable timeframes.
  • The stochastic approach successfully incorporates uncertainty in intervention times.

Conclusions:

  • The presented deterministic and stochastic programming models offer a robust methodology for solving the workover rig problem.
  • The models provide a valuable tool for optimizing oil industry operations, balancing production and cost.