Pre-Drilling Prediction of 3D Geomechanical Parameters Based on Seismic Data: A Case Study of Tarim Oilfield

ABSTRACT A pre-drill prediction method of 3D geomechanical parameters based on seismic data is proposed. Firstly, the wave impedance parameters are predicted in the target area by the logging-constrained method, which mainly uses post-stack seismic data and logged data from drilled wells. The density and velocity data are obtained by separating the wave impedance data. Then, the density and velocity data are used as input to calculate 3D geomechanical parameters in the region, including elasticity parameters, strength parameters, and stress parameters. In particular, experimental data are used to correct the accuracy of the model. The results accurately reflect the geological complexity and non-homogeneity of the region by evaluating the elastic properties, mechanical properties, and stress magnitude of each point. This method can greatly improve the longitudinal resolution of the inversion results by fully exploiting a priori information from the logs and involving them in the seismic inversion process. Pre-drill parameters prediction of a complex field in the Tyuritag of the Tarim Basin is carried out. INTRODUCTION A growing number of oil and gas field development projects are facing the challenge of safe, rapid, and efficient development, such as offshore projects like Hibernia and the Gulf of Mexico in Canada, and onshore projects in tectonically active areas like the Cusiana field in Colombia and the Tarim Basin in China. However, as drilling depths continue to deepen, the geological environment encountered in oil and gas development is becoming increasingly complex. The difficulty of engineering problems related to geomechanics is also increasing. On the one hand, there are more and more complex accidents in various wells, such as well wall instability, well leakage, and sand production. Underground accidents seriously increase the time and cost of construction operations. It is estimated that at least 10% of the average well budget is used for unplanned operations due to wellbore instability (Sheng, 2006; Wei, 2012). On the other hand, the inaccuracy of geomechanical modeling makes geomechanics-related engineering measures unable to achieve the expected goals. In shale oil and gas development, about 30-50% of fracturing clusters do not contribute to product improvement. The root cause is poorly designed hydraulic fracturing strategies due to the lack of accurate geomechanical data (Zhang, 2018; Parshall, 2015).