A Method for Predicting In-Situ Stress Based on Experimental, Logging and Engineering Data

The characterization of in-situ stress primarily involves the maximum horizontal principal stress, the minimum horizontal principal stress, and the vertical stress. However, due to the cumulative error arising from the integration of the density curve, inaccuracies occur in the calculation of vertical pore pressure, leading to reduced precision in the characterization of vertical stress. Additionally, challenges in accurately identifying the Kaiser effect point during acoustic emission experiments, as well as difficulties in obtaining the Biot coefficient, contribute to significant errors in the computation of the maximum and minimum horizontal principal stresses. To address these issues, a method for predicting in-situ stress based on experimental, logging, and engineering data is proposed. Specifically, the pressure gradient curve is corrected using in-situ stress experimental data, while the pore pressure calculation model is calibrated with MDT data. The Kaiser point is identified through a combination of suspected effective points, and the Biot coefficient is inversely calculated using Mini-Frac Test data. The in-situ stress data points obtained via this method resolve the apparent inconsistencies present in vertical and lateral inter-well data, yielding more reasonable results. The following insights and conclusions are drawn: (1) Accurate identification of the Kaiser point is critical for measuring in-situ stress using the acoustic emission method. Screening and identifying the Kaiser point by combining effective points significantly reduces the likelihood of misinterpretation; (2) Calibration of the pore pressure calculation model with MDT data produces results that better align with actual geological characteristics; (3) Mini-Frac Test data can be utilized not only to correct the results of the minimum horizontal principal stress but also to inversely calculate a relatively accurate Biot coefficient. This study innovates the methodology for reading the Kaiser point. The proposed in-situ stress prediction method, which integrates experimental, logging, and engineering data, has been successfully applied to low-permeability reservoir modification, achieving notable improvements after implementing targeted measures.