Journal of Cleaner Production | VOL. 247
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A multi-objective and multi-scenario optimization model for operation control of CO2-flooding pipeline network system

Publication Date Feb 1, 2020

Abstract

Abstract Countries with high carbon emissions are actively exploring carbon capture, utilization and storage (CCUS) system. CCUS-based CO2 enhanced oil recovery (CO2-EOR) technology is favored for sustainable oilfield development and its contribution to mitigating global warming. In this paper, under the crafts constraints of injection stations and CO2-flooding wells, as well as the flow rate and pressure constraints along pipeline network, a multi-objective mixed integer nonlinear programming (MOMINLP) model is proposed for the optimal operation control of oilfield surface CO2-flooding pipeline network system. The minimum operating costs of pumps, the maximum CO2 injection volume and the minimum demand-injection volume deviation are set as objective functions. The uncertainty of demand CO2 injection volume caused by geological uncertainty is settled by scenario-based stochastic programming method. In addition, the piecewise linearization method and the augmented e-constraint method (AUGMECON) are introduced to deal with the nonlinear constraints and get the Pareto optimal solutions, respectively. Finally, the proposed model is successfully applied to a large-scale looped and branched CO2-flooding pipeline network system in Sinkiang, China with three cases for comparison to verify its applicability and superiority.

Concepts
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Carbon Capture, Utilization And Storage
Multi-objective Mixed Integer Nonlinear Programming
CO2 Injection Volume
Augmented E-constraint Method
Piecewise Linearization Method
High Carbon Emissions
Pareto Optimal Solutions
Geological Uncertainty
Pressure Constraints
Multi-objective Nonlinear Programming Model

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