Velocity model calibration for surface microseismic monitoring based on a 3D gently inclined layered equivalent model

Abstract

Shale gas has become a major source of natural gas production and has received worldwide attention. Hydraulic fracturing is widely performed to stimulate oil and gas wells with considerable success. Given high-precision microseismic (MS) event locations, we can predict the development trend and region of fracturing and evaluate the stimulation effect, thereby providing technical guidance for subsequent exploitation. An accurate velocity model is essential for MS event positioning. However, simple velocity models, such as the uniform or vertical transverse isotropy (VTI) velocity model, are generally applied to calibrate the velocity model. Despite calibration, the VTI model may still face challenges in obtaining accurate MS event locations. Based on the structural characteristics of shale, we propose a novel local velocity model calibration algorithm for surface MS monitoring. To calibrate the velocity model, the actual strata interfaces are replaced with 3D gently inclined planes. We utilize very fast simulated annealing (VFSA) to concurrently tune the velocity, depth, and angle parameters of the model. Through the assessment of both the stacked amplitude at the position of the perforation shot and the relocation error of the perforation shot, we determine the ideal velocity model. To evaluate the effectiveness of our approach, we conduct experiments on both a synthetic model and a field dataset, and statistically analyze the location error. The results show that the proposed method obviously reduces the perforation shot relocation error and is well-suited for calibrating velocity models that are close to slightly inhomogeneous layered media.

Localization for surface microseismic monitoring based on arrival time correction and VFOM

“…Meticulously characterizing numerous microseismic events provided insights into the temporal and spatial evolution patterns of the fracture network, along with an estimation of the effective stimulated reservoir volume [6,11]. The fracture network is determined by fitting point clusters at the positions of microseismic events; thus, the accurate location of microseismic events is of paramount importance in microseismic monitoring [12].…”