Abstract
This study evaluated two distinct cryo-fracturing techniques using liquid nitrogen (LN2). The evaluation included tests for peak compression strength, acoustic emission, and energy absorption. The experiments compared single-exposure freezing time (FT) and multiple-exposure freezing–thawing cycle (FTC) processes on dried specimens. The outcomes indicated that FTC experiments demonstrated lower uniaxial compression stress (UCS) values compared to FT experiments because, during the thawing phase, the ice inside the pores reverts to liquid as the temperature rises. The difference between average baseline experiments versus FT180 and FTC6 indicated a reduction in stress of 14.5% and 38.5%, respectively. The standard error of our experiments ranged from 0.58% for FT60 to 5.35% for FTC6. The damage factor follows a downward trend in both FT and FTC experiments as the time of LN2 treatment augments. The amount of energy that can be absorbed in elastic or plastic deformation before failure is less for FTC specimens with the same total LN2 exposure time. Samples undergoing the freezing time process demonstrate a greater and denser quantity of acoustic emissions in comparison to freezing–thawing cycle processes, suggesting a positive correlation with uniaxial compressive strength outcomes. The large network of fractures formed by the FTC and PFTC techniques indicated that they have the greatest potential as stimulation approaches. The engineering results were improved by adding the geological context, which is essential to apply these findings to coals that have comparable origins.
Original language | English |
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Article number | 2359 |
Journal | Energies |
Volume | 17 |
Issue number | 10 |
DOIs | |
Publication status | Published - May 2024 |
Keywords
- coalbed methane
- immersion tests
- LN fracturing
- unconfined test
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Engineering (miscellaneous)
- Energy Engineering and Power Technology
- Energy (miscellaneous)
- Control and Optimization
- Electrical and Electronic Engineering