Integrated production optimization of oil fields with pressure and routing constraints: The Urucu field

Integrated production optimization of oil fields with pressure and routing constraints: The Urucu field

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Abstract

This paper develops a framework for integrated production optimization of complex oil fields such as Urucu, which has a gathering system with complex routing degree of freedom, limited processing capacity, pressure constraints, and wells with gas-coning behavior. The optimization model integrates simplified well deliverability models, vertical lift performance relations, and the flowing pressure behavior of the surface gathering system. The framework relies on analytical models history matched to field data and simulators tuned to reflect operating conditions. A mixed-integer linear programming (MILP) problem is obtained by approximating these models with piecewise-linear functions. Procedures were developed to obtain simplified piecewise-linear approximations that ensure a given accuracy with respect to complex and precise models. Computational experiments showed that the integrated production optimization problem can be solved sufficiently fast for real-time applications. Further, the operational conditions calculated with the simplified models during the optimization process match the precise models.
Content

This paper develops a framework for integrated production optimization of complex oil fields such as Urucu, which has a gathering system with complex routing degree of freedom, limited processing capacity, pressure constraints, and wells with gas-coning behavior. The optimization model integrates simplified well deliverability models, vertical lift performance relations, and the flowing pressure behavior of the surface gathering system. The framework relies on analytical models history matched to field data and simulators tuned to reflect operating conditions. A mixed-integer linear programming (MILP) problem is obtained by approximating these models with piecewise-linear functions. Procedures were developed to obtain simplified piecewise-linear approximations that ensure a given accuracy with respect to complex and precise models. Computational experiments showed that the integrated production optimization problem can be solved sufficiently fast for real-time applications. Further, the operational conditions calculated with the simplified models during the optimization process match the precise models.

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