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 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.