Multichannel Coherency Migration grid search (MCMgs) in locating microseismic events by a surface array

Microseismic monitoring has been used in geo-energy related activities, such as shale-gas ex-ploitation, mining, deep geothermal exploitation, geotechnical and structural engineering, for detecting and locating fractures, rock failures, and micro-earthquakes. The success of micro-seismic monitoring depends on reliable detection and location of the recorded microseismic-ity. Multichannel Coherency Migration (MCM) is a detection and location waveform migra-tion based approach which does not require phase picking, identification, and association and performs well on noisy data. Its caveat is a high computational cost, which impedes its ap-plication of MCM on large datasets or for real-time monitoring. To address this issue, we propose an improved approach, the Multichannel Coherency Migration grid search (MCMgs), by introducing an adaptive grid optimization technique. Based on results from synthetic and real data, we show that MCMgs reduces the computation time up to 64 times. In addition, MCMgs generates multiple maximum coherency values with various grid sizes instead of a single (maximum) coherency value that links to a single grid point and size, thus resulting in more accurate locations. Our simulation results on different deployment geometries demon-strate that MCMgs is effective even with a small number of recordings available - a minimum of seven. We conduct a sensitivity analysis to assess how the detectability of events is affected by the spatial arrangement of the deployed monitoring array. If a limited number of seismome-ters are available for deployment, our analysis favors a patch array deployment geometry. We show that twelve seismometers deployed at a patch array geometry can have similar detection and localisation capability as a large rectangular array of more than 100 seismometers but at a much lower computational and deployment cost

Fracture parameter inversion from passive seismic shear-wave splitting: A validation study using full-waveform numerical synthetics

Fractures are pervasive features within the Earth's crust and they have a significant influence on the multi-physical response of the subsurface. The presence of coherent fracture sets often leads to observable seismic anisotropy enabling seismic techniques to remotely locate and characterise fracture systems. Since fractures play a critical role in the geomechanical and fluid-flow response, there has been significant interest in quantitatively imaging in situ fractures for improved hydro-mechanical modelling. In this study we assess the robustness of inverting for fracture properties using shear-wave splitting measurements. We show that it is feasible to invert shear-wave splitting measurements to quantitatively estimate fracture strike and fracture density assuming an effective medium fracture model. Although the SWS results themselves are diagnostic of fracturing, the fracture inversion allows placing constraints on the physical properties of the fracture system. For the single seismic source case and optimum receiver array geometry, the inversion for strike has average errors of between 11° and 25°, whereas for density has average errors between 65% and 80% for the single fracture set and 30% and 90% for the double fracture sets. For real microseismic datasets, the range in magnitude of microseismicity (i.e., frequency content), spatial distribution and variable source mechanisms suggests that the inversion of fracture properties from SWS measurements is feasible

Analysis of fracture induced scattering of microseismic shear-waves

Fractures are pervasive features within the Earth’s crust and have a significant influence on the multi-physical response of the subsurface. The presence of coherent fracture sets often leads to observable seismic scattering enabling seismic techniques to remotely locate and characterise fracture systems. In this study, we confirm the general scale-dependence of seismic scattering and provide new results specific to shear-wave propagation. We do this by generating full waveform synthetics using finite-difference wave simulation within an isotropic background model containing explicit fractures. By considering a suite of fracture models having variable fracture density and fracture size, we examine the widening effect of wavelets due to scattering within a fractured medium by using several different approaches, such as root-mean-square envelope analysis, shear-wave polarisation distortion, differential attenuation analysis and peak frequency shifting. The analysis allows us to assess the scattering behavior of parametrised models in which the propagation direction is either normal or parallel to the fracture surfaces. The quantitative measures show strong observable deviations for fractures size on the order of or greater than the dominant seismic wavelength within the Mie and geometric scattering regime for both propagation normal and parallel to fracture strike. The results suggest that strong scattering is symptomatic of fractures having size on the same order of the probing seismic wave

Multichannel coherence migration grid search (MCMgs) in locating microseismic events recorded by a surface array

Microseismic monitoring has been used in geo-energy related activities, such as shale-gas exploitation, mining, deep geothermal exploitation, geotechnical and structural engineering, for detecting and locating fractures, rock failures and micro-earthquakes. The success of microseismic monitoring depends on reliable detection and location of the recorded microseismicity. Multichannel coherence migration (MCM) is a detection and location waveform migration-based approach which does not require phase picking, identification and association and performs well on noisy data. Its caveat is a high computational cost, which impedes its application of MCM on large data sets or for real-time monitoring. To address this issue, we propose an improved approach, the multichannel coherence migration grid search (MCMgs), by introducing an adaptive grid optimization technique. Based on results from synthetic and real data, we show that MCMgs reduces the computation time up to 64 times. In addition, MCMgs generates multiple maximum coherence values with various grid sizes instead of a single (maximum) coherence value that links to a single gridpoint and size, thus resulting in more accurate locations. Our simulation results on different deployment geometries demonstrate that MCMgs is effective even with a small number of recordings available—a minimum of seven. We conduct a sensitivity analysis to assess how the detectability of events is affected by the spatial arrangement of the deployed monitoring array. If a limited number of seismometers are available for deployment, our analysis favours a patch array deployment geometry. We show that 12 seismometers deployed at a patch array geometry can have similar detection and localization capability as a large rectangular array of more than 100 seismometers but at a much lower computational and deployment cost.ISSN:0956-540XISSN:1365-246