Enhanced Carbon Storage Process from Flue Gas Streams Using Rice Husk Silica Nanoparticles: An Approach in Shallow Coal Bed Methane Reservoirs

Abstract

Carbon capture and storage (CCS) is considered a key process to reach net-zero emission by the 2050 aim of limiting global warming. Coal bed methane (CBM) is considered potential geological reservoirs for underground CCS due to the CO2–CH4 exchange feasibility by adsorptive phenomena. Global implementation has been focused only on deep reservoirs to provide methane recovery. Thus, this work proposes a modified CCS process based on silica nanoparticle inclusion for shallow CBM reservoirs (<300 m). The nanomaterials were evaluated at high pressure in two main stages including i) CO2 sorption on a single CO2 stream and ii) CO2 selectivity on a flue gas stream (N2–CO2 mixture). This work includes silica nanomaterial synthesized from rice husk as agro-waste sources with better technical-economic feasibility framed in a circular economy to reduce costs and maximize the use of available resources. Rice husk silica (RSi) nanoparticles were doped with 1.0, 3.0, and 5.0 wt % of urea (Si–U), diethylamine (Si-DE), triethylamine (Si-TE), and ethylenediamine (Si-EM) to enhance the CO2 sorption. First, CO2 sorption was evaluated at 30 °C and between 0.084 and 3 MPa using a CO2 stream to determine the best-doped amount of each N-source. Then, the best nanoparticles were used to impregnate CBM at 10 and 20 wt %, and the subsequent CO2 storage on the flue gas stream (70% v/v N2 and 30% v/v CO2) was done. The results showed that CO2 sorption on RSi increases with the N-group coating in the order RSi-DE < RSi-TE < RSi-U < RSi-EM. Also, the best-doped amount for each N-source was 3 wt %. For CBM impregnation, the nanofluid containing 20 wt % of RSi-EM3 presented the best yield increasing the CO2 sorption from 0.05 to 0.75 mmol g–1, meaning an increase of more than 1000% in the sorption capacity.

Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

“…The storage behavior of shallow and low-pressure sequestration of CO 2 in coal seams is of particular interest as a result of its shallow injection depth compared to that of other reservoirs. For instance, Giraldo et al 155 proposed an improved carbon capture and storage (CCS) process based on the inclusion of silica nanoparticles as additives for shallow coalbed methane reservoirs with a depth less than 300 m. The silica nanoparticles were employed to enhance the adsorption capacity of the coal seam. The results showed that the treated samples exhibited an increase in adsorption capacity of over 1000%.…”

Recent Advances in Carbon Dioxide Sequestration in Deep Unmineable Coal Seams Using CO2-ECBM Technology: Experimental Studies, Simulation, and Field Applications

“…Reference conducted an experiment to investigate the effects of nanoparticle application in CO 2 sequestration in shallow CBM reservoirs (<300m). Different rice husk silicas (RSi) were used to observe their effects on enhancing sorption capacity, which was synthesized from a local Colombian mill.…”

“…Chemical structures of used modifiers: (a) urea, (b) ethylenediamine, (c) diethylamine, and (d) triethylamine. This figure was reproduced with permission from ref . Copyright 2023 American Chemical Society.…”

Experimental Investigations on Enhanced Coal Seam Methane Extraction by Injecting Gas: A Review

“…35 The interaction between CO 2 , CH 4 , and water molecules 36 leads to significant changes in the ultimate macromolecular structure, natural fracture structure, pore structure, and mineral phase of coal, 37−41 and the temperature and pressure of coal storage can affect the effectiveness of CO 2 storage. 42,43 Many scholars have improved the CCS process through nanotechnology, such as Giraldo's 44 proposal of an improved CCS process based on silica nanoparticle inclusions, which enhances the adsorption of CO 2 in the mixture (CO 2 −N 2 ).…”