Velocity calibration for microseismic event location using surface data

Abstract

Because surface-based monitoring of hydraulic fracturing is not restricted by borehole geometry or the difficulties in maintaining subsurface equipment, it is becoming an increasingly common part of microseismic monitoring. The ability to determine an accurate velocity model for the monitored area directly affects the accuracy of microseismic event locations. However, velocity model calibration for location with surface instruments is difficult for several reasons: well log measurements are often inaccurate or incomplete, yielding intractable models; origin times of perforation shots are not always accurate; and the non-uniqueness of velocity models obtained by inversion becomes especially problematic when only perforation shots are used. In this paper, we propose a new approach to overcome these limitations. We establish an initial velocity model from well logging data, and then use the root mean square (RMS) error of double-difference arrival times as a proxy measure for the misfit between the well log velocity model and the true velocity structure of the medium. Double-difference RMS errors are reduced by using a very fast simulated annealing for model perturbance, and a sample set of double-difference RMS errors is then selected to determine an empirical threshold. This threshold value is set near the minimum RMS of the selected samples, and an appropriate number of travel times within the threshold range are chosen. The corresponding velocity models are then used to relocate the perforation-shot. We use the velocity model with the smallest relative location errors as the basis for microseismic location. Numerical analysis with exact input velocity models shows that although large differences exist between the calculated and true velocity models, perforation shots can still be located to their actual positions with the proposed technique; the location inaccuracy of the perforation is \2 m. Further tests on field data demonstrate the validity of this technique.

Cross double‐difference inversion for simultaneous velocity model update and microseismic event location

“…; Bardainne and Gaucher ; Jiang et al . ). If we discretize the velocity model in equation , we obtain a linear equation relating the misfit between the observed and calculated arrival time to the desired perturbations to the velocity structure parameters and the origin time of the perforation shot: where is the layer number and is the length of the raypath from the perforation shot perf to the receiver k in the n th layer.…”

“…Sonic logs can be used to build an initial 1D layered velocity model. We then can use perforation shot with a known location and unknown origin time to calibrate the velocity model (Warpinski et al 2005;Bardainne and Gaucher 2010;Jiang et al 2016). If we discretize the velocity model in equation (1), we obtain a linear equation relating the misfit between the observed and calculated arrival time r perf k to the desired perturbations to the velocity structure parameters and the origin time of the perforation shot:…”

“…; Bardainne and Gaucher ; Jiang et al . ). In some cases, it may cause velocity‐related errors in locating the microseismic events in areas not covered by the ray trajectories of the perforation shots (Grechka ; Grechka, Singh and Das ).…”

“…velocity model can be constructed from sonic logs and calibrated by perforation shots (or string shots) (Warpinski et al 2005; Bardainne and Gaucher 2010;Jiang et al 2016). In some cases, it may cause velocity-related errors in locating the microseismic events in areas not covered by the ray trajectories of the perforation shots (Grechka 2010;Grechka, Singh and Das 2011).…”

Velocity model optimization for surface microseismic monitoring via amplitude stacking

“…Because a perforation shot position is generally very well known, it can be relocated iteratively to reduce the location error. However, existing iterative techniques mainly rely on picking of P and S wave arrival times (Bardainne and Gaucher, 2010;Pei et al, 2008Pei et al, , 2009Tan et al, 2013;Jiang et al, 2016), meaning that seismograms with high signal-to-noise ratios (S/N) are required. This approach is suitable for borehole monitoring arrays; however, for microseismic monitoring at the surface, the seismograms of perforation shots tend to have low S/N ratios, and existing velocity model optimization methods do not perform well.…”