(652c) A New MINLP Model for Optimal Planning of Offshore Oil and Gas Field Infrastructure with Production Sharing Agreements | AIChE

(652c) A New MINLP Model for Optimal Planning of Offshore Oil and Gas Field Infrastructure with Production Sharing Agreements


Grossmann, I. E. - Presenter, Carnegie Mellon University

Optimal investment and operations planning of offshore oil and gas field facilities is very critical problem given that it involves huge investments and high potential profits [1-2].  Therefore, an efficient model that on one hand captures the realistic reservoir profiles, interaction among various fields and facilities, wells drilling limitations and other practical trade-offs involve in the offshore development planning, on the other hand it should be able to extend to include other complexities especially that arises due to the fiscal rules [3] and uncertainties [4-5].

In this paper, we present an efficient strategic/tactical planning model for offshore oilfield development problem that includes Production Sharing Agreements and fairly generic to be extended to other complexities. The proposed multiperiod non-convex MINLP model for multi-field site includes three components (oil, water and gas) explicitly in the formulation using 3rd and higher order polynomials avoiding bilineairties and other nonlinear terms. With the objective of maximizing total NPV for long-term planning horizon, the model involves decisions related to FPSO (floating production, storage and offloading) installation and expansion schedule and respective oil, liquid and gas capacities, connection between the fields and FPSO’s, well drilling schedule and production rates of these three components in each time period. The resulting model can be solved with DICOPT in an efficient way for realistic instances and gives good quality solutions. Furthermore, it can be reformulated into an MILP model after piecewise linearization and other linearization techniques that can be solved globally in an efficient way.

Including fiscal considerations, especially progressive Production Sharing Agreements (PSA’s), as part of the investment and operation decisions for this problem can significantly impact the optimal solution and required computational time. In particular, these specific rules determine the profit that the operating company can keep as well as the royalties, taxes that are paid to the government through complex calculations. Therefore, an effective extension of the proposed model to include the complex rules in Production Sharing Agreements (PSA’s) for multiple field case will also be presented. Solutions of realistic instances involving 10 fields, 3 FPSO’s and 20 years planning horizon will be reported, as well as comparisons between the computational performance of the proposed MINLP and MILP formulations.   The difference in solutions and computational impact of adding the PSA constraints versus using a simple NPV optimization is also reported.


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