Estimation of micro-earthquake source locations based on full adjoint P and S wavefield imaging

Abstract

SUMMARY Locating micro-earthquakes with high resolution and accuracy is a challenge for traveltime inversion, which has uncertainty on the order of a Fresnel zone (many wavelengths). We develop a wave-equation imaging method to increase resolution and reduce location errors to less than a wavelength, but requires very densely deployed receiver arrays with wide aperture and considerable computational cost. Instead of using acoustic data or direct P wave arrivals only, we use elastic multicomponent data and present a new method that uses the full P and S adjoint wavefields to image the microseismic source locations. We separate the P and S waves from the data, and extrapolate the P and S wavefields of each receiver subarray by solving the P and S adjoint wave equations in parallel. We formulate three source imaging conditions by multiplying over subarrays the adjoint P wavefield (IP), S wavefield (IS) and cross-correlated P and S wavefields (IPS). We perform numerical experiments on the highly realistic SEG SEAM4D reservoir model using surface acquisition array geometries. Results for 2-D and 3-D microseismic source estimations show clean images without noisy artefacts at shallow depths. In particular, IPS provides the highest resolution source location image, while IP is limited by the P wavelength and IS is influenced by small coda artefacts. The major-axis alignment and resolution of the source location image are determined by the hypocentral location with respect to the receiver array and illumination-angle coverage, respectively. We discuss the impacts of S-wave attenuation and frequency bandwidth on the source location images. Noise tests indicate that the imaging results are relatively insensitive to ambient noise, as is observed for the surface monitoring data. Using smoothed velocity models, the imaging results are similar to the results using the true realistically heterogeneous velocity model. The 90 per cent confidence ellipse of the source location due to Gaussian-distributed velocity errors shows a larger depth error as the source becomes deeper, while the horizontal error does not change as much.