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    Research

    Human geosciences

    202401202401

    Empirical evaluation of the strength and deformation characteristics of natural and synthetic gas hydrate-bearing sediments with different ranges of porosity, hydrate saturation, effective stress, and strain rate

    Jun Yoneda, Kiyofumi Suzuki, Motoi Oshima, Michihiro Muraoka, Yusuke JinJun Yoneda, Kiyofumi Suzuki, Motoi Oshima, Michihiro Muraoka, Yusuke Jin

    Methane hydrate, Pressure core, Strength, Stiffness, Young’s modulus, Triaxial test, Uniaxial test

    Strength and deformation modulus prediction based on the proposed empirical equation and data from logging.

    Evaluating the mechanical properties of gas (primarily methane) hydrate-bearing sediments is essential for commercial production as a next-generation resource and understanding the global carbon cycle. Triaxial and uniaxial compression tests have been conducted on synthetic gas hydrate and natural core samples recovered from deep-sea beds using pressure coring techniques. The results show that four factors are vital in establishing the strength of hydrate-bearing sediments: hydrate saturation, effective confining stress, porosity, and strain rate. However, no study has evaluated these factors in a unified and quantitative manner, and even if the physical properties of the reservoir are known in detail from logging, predicting the strength has been challenging. In this study, pressure cores were drilled and recovered from the Eastern Nankai Trough in April 2018 after Japan’s second offshore production test, and triaxial or uniaxial compression tests were performed on 12 pressure core samples brought back to the laboratory. The mechanical properties of the hydrate-bearing sediments were classified with previous obtained results from 53 pressure cores and 223 synthetic cores, and empirical equations for triaxial compressive strength and deformation modulus were proposed as functions of gas hydrate saturation, effective confining pressure, porosity, and strain rate. The obtained equations were found to correlate well with the experimental data and can predict the strength and deformation modulus from logging data.