Optimizing the Carbon Footprint of Polymer Injection Utilizing a Deep Learning Log Interpretation Framework

Author:

Katterbauer Klemens1,Al Shehri Abdallah1,Hassan Saleh1,Yousef Ali1

Affiliation:

1. Saudi Aramco

Abstract

Abstract The world of energy industries is exhibiting tremendous efforts to ensure the sustainability of its operations and reduce its carbon footprint. These efforts include optimizing field operations to be more sustainable while maintaining production levels. The 4th Industrial Revolution is having enormous impact on the oil and gas industry, also allowing better analysis of carbon footprint reduction opportunities. Modern logging technologies are able to accurately characterize the formation and measure its production behavior. Polymer injection technologies have the potential to significantly reduce water cut, thereby helping to optimize the carbon footprint. We evaluated the impact of various polymer injection strategies on the Volve field with several production and injection wells to simulate the impact of injecting polymers on the fluid production rates. The injection of polymers helps in reducing the water production rates from the reservoir, thereby reducing the carbon footprint related to the handling of the produced water and injection of water. Various scenarios were evaluated in order to determine the overall impact on carbon emissions and based on a probability-likelihood framework the overall carbon footprint was determined. While the optimal injection strategy may depend on various factors, polymers demonstrate the ability to reduce significantly the overall carbon footprint while increasing hydrocarbon production.

Publisher

SPE

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