2021
DOI: 10.5194/se-2021-24
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Accelerating Bayesian microseismic event location with deep learning

Abstract: Abstract. We present a series of new open source deep learning algorithms to accelerate Bayesian full waveform point source inversion of microseismic events. Inferring the joint posterior probability distribution of moment tensor components and source location is key for rigorous uncertainty quantification. However, the inference process requires forward modelling of micro-seismic traces for each set of parameters explored by the sampling algorithm, which makes the inference very computationally intensive. In … Show more

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