Shale In-Situ Stress logging prediction method based on dynamic, static and anisotropic

In-situ stress is an important rock mechanical parameter for determining horizontal well borehole trajectories, analyzing well wall stability, selecting fracturing sections and compartments, and formulating oil and gas extraction measures throughout the entire life cycle of oil and gas reservoirs. Aiming at the problems of shale reservoir anisotropy and low precision of In-Situ Stress evaluation, we carried out rock acoustic-mechanical coupling experiments, tested nine sets of rock acoustic-mechanical parameters from different angles, and established a model for evaluating the dynamic, static, and anisotropic properties of rocks. First, the dynamic stiffness coefficients of rocks were constructed based on the acoustic information of rocks from different angles, and the static stiffness coefficients of rocks were constructed based on the stress-strain curves of rocks. Second, stiffness coefficients of C11d, C12d and C66d were constructed based on C33d and C44d tested in the laboratory. Stiffness coefficients constructed with this method were more accurate than those of the traditional ANNIE model. Based on the acoustic-force coupling experiment, a model was constructed to convert rock static stiffness coefficients. This, in turn, realized the prediction of the stiffness coefficient of the whole well section. Again, four models, namely, dynamic isotropic geopathic stress model (Model A), static isotropic geopathic stress model (Model B), dynamic isotropic geopathic stress model (Model C), and a static isotropic geopathic stress model, were adopted to evaluate the In-Situ Stress and compared with the experimental results. In-situ stress and compared with the experimental results. The study's results show that the A model predicts the maximum and minimum horizontal principal stresses with an average absolute error of 19%. 07%, 21.93%. The B model predicts an average absolute error of 13.95%, 13.33%. The C model predicts an average absolute error of 17.64%, 17.59%. The D model predicts the average absolute error of 3.05%, 3.33%. The error of D model is controlled within 5% and has the highest prediction accuracy. The research results provide more reliable rock mechanical parameters for hydraulic fracturing design in shale gas extraction, providing a new way of thinking for the prediction of the ground stress field.