(128f) Robust Insights into CO2 Hydrate Kinetics in Brine-Saturated Sediments Using Experimental and Machine Learning Approaches for Ccus Application | AIChE

(128f) Robust Insights into CO2 Hydrate Kinetics in Brine-Saturated Sediments Using Experimental and Machine Learning Approaches for Ccus Application

Authors 

Dhamu, V. - Presenter, National University of Singapore
Qureshi, M. F., Qatar University
Linga, P., National University of Singapore
One of the potential Carbon Capture and Sequestration (CCS) methods is capturing CO2 and injecting it into the oceanic sediments where CO2 is converted into CO2 gas hydrates. However, the presence of brine [NaCl] in sediments likely affects the kinetics of CO2 hydrate formation significantly. To tackle this challenge, a real-world scenario was mimicked in this work, by creating artificial brine-rich different-sized sediment beds in a laboratory-scale reactor. Afterward, CO2 was injected multiple times via injection tube directly into the sediment, and the CO2 hydrate formation, dissociation, and morphological changes were recorded.

The experimental results show that the water-to-hydrate conversion [%] was estimated to be about highest in smaller size sediments [~60%] > both (smaller + larger sediments) dual [~35 %] > larger sediments [~20 %]. The visual observations show the smaller-size sediments show the haphazard isotropic advancement of whitish CO2 hydrate whereas in the presence of large-sized sediments, various hydrate capping which trapped brine or CO2 was observed. Moreover, using ~94,000 experimental data (% water to hydrate conversion, pressure, and temperature) a newly proposed CO2 hydrate formation kinetic model was trained using a supervised ML-based algorithm to predict best-optimized parameters having the capability of forecasting CO2 hydrate formation kinetics with %AARD of < 9%. This study’s experimental and modelling results offer valuable insights that can play a pivotal role in advancing the CCS via hydrate technologies.

Acknowledgments

PL acknowledges the funding support from the Agency of Science, Technology and Research (A*STAR) under the low carbon energy research (LCER) funding initiatives (project ID: U2102d2010).