Abstract
Summary Seismic travel time tomography has been proven as an effective tool in reconstruction of Earth’s p-wave velocity model in offshore projects. Data of different resolutions and scales are to be integrated to reconstruct the underlying velocity field which may be further correlated to other geotechnical and geomechanical parameters. In this study, we apply a probabilistic method to invert criosshole seismic tomography travel time data which utilizes geostatistical priors, i.e. models that features the spatial pattern and continuity of the underlying velocity field inferred from limited amount of data in the boreholes. The method starts with a Bayesian analysis over the Kriging mean and correlation model parameters, and posterior samples from this step is input to a geostatistical simulator that generates realistic prior models as an input to the probabilistic inversion process. Extended Metropolis sampler then is hired to generate samples of posterior realizations of p-wave velocity model. The proposed method is applied on a synthetic ground model of p-wave velocity and results indicate the efficiency of the algorithm in reconstructing the underlying p-wave velocity model with the possibility of uncertainty quantification through multiple realizations generated.
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