Applying Carbon Tax Within CO2 Utilization Networks Including Enhanced Oil Recovery Operations in Qatar

Abstract

Carbon capture and storage (CCS) is a promising and efficient techniques for carbon dioxide (CO2) emission reduction. Combining CCS with enhanced oil recovery (EOR) processes is a very attractive method for carbon capture and utilisation (CCU). These operations enable CO2 emissions to be reduced through geological sequestration, whilst generating additional revenue from enhanced oil production due to CO2 re-injection via EOR. When numerous oil reservoirs are involved, it is vital to allocate available CO2 supplies and schedule EOR operations for these reservoirs at suitable timings. As a result, CO2 both allocation and scheduling are crucial for maximising the economic benefits of EOR operations. As such, this study introduces a resource trade scheme for CO2 integration and utilisation within the state Qatar, where a linear programming (LP) model is developed to address CO2 allocation and scheduling based on environmental and economic objectives. The model considers a single CO2 source (Qatar Gas) within an multi sink scenario which includes several sinks within an industrial setting (QAFCO, QAFAC, PEARL GTL, ORYX GTL, Dukhan Field Well (EOR)). Three scenarios are considered to allocate CO2 to different sinks (including EOR) to obtain the optimal solution for each scenario. The outcome of scenario 1 and 2 demonstrates that the optimal solution is to utilise 15Mt/y of carbon dioxide, which results in an annual profit varying from 3.40 to 6.96 billion dollars and 0.73 and 5.86 billion dollars respectively. The maximum CO2 utilisation occurs at Dukhan Field Well (EOR), which has a utilisation rate of 60%- 69%. Scenario 3 is implemented based on scenario 1 to further improve the model; where the profit increased annually, and the model became more sustainable with a profit ranging from 3.40 to 10.1 billion dollars. The percent of CO2 allocation/utilisation of each sink in scenario 1 (without tax) and scenario 2 (with tax) are almost the same.

Date of Award	2022
Original language	American English
Awarding Institution	HBKU College of Science and Engineering