Estimation of parameters for 3D geomechanical modeling from triaxial test results

Triaxial testing serves as a fundamental method for evaluating the elastic and strength properties of rocks, crucial for developing accurate 3D geomechanical models. This paper presents a novel method for determining strength parameters by incorporating the dependence of uniaxial compressive strengt...

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Bibliographic Details
Published inEnergy Geoscience Vol. 6; no. 1; p. 100354
Main Author Kukhtinskii, Artem
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.03.2025
KeAi Communications Co., Ltd
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Summary:Triaxial testing serves as a fundamental method for evaluating the elastic and strength properties of rocks, crucial for developing accurate 3D geomechanical models. This paper presents a novel method for determining strength parameters by incorporating the dependence of uniaxial compressive strength (UCS) on P-wave velocity into the Hoek-Brown criterion. Additionally, a new approach is introduced to process triaxial test data efficiently using Python libraries such as SciPy, NumPy, Matplotlib, and Pandas. Furthermore, the paper addresses challenges in determining elastic parameters through triaxial testing. A Python script is developed to automate the calculation of elastic modulus and Poisson's ratio, overcoming subjectivity in selecting the linear portion of stress-strain curves. The script optimally identifies the linear region by minimizing the fit error with appropriate constraints, ensuring a more objective and standardized approach. The proposed methodologies are demonstrated using limestone specimens from Central Asian gas fields. These innovations offer faster, more reliable results, reducing error and enhancing the comparability of analyses in geomechanics, with potential applications across various geological settings. [Display omitted] •A novel approach integrates UCS dependence on VP into a strength criterion.•A method is proposed for consistent parameters determination from triaxial tests.•The methods are applied to a set of over 50 limestone triaxial tests using Python.•Both methods provide an automated reliable way for triaxial tests processing.
ISSN:2666-7592
2666-7592
DOI:10.1016/j.engeos.2024.100354