Characterization of Gas-charged Sediments from Joint Inversion of Qp and Qs with Sonic Logs

Seismic attenuation is an effective indicator of the presence of gas. Compared with velocity, attenuation responses more strongly to saturation, pore pressure and permeability in addition to porosity. Quantitatively assessing various rock properties from seismic attenuation is a high-dimensionally non-linear inverse problem. We propose a Bayesian workflow to estimate properties of gas-charged sediments by jointly inverting P- and S-wave quality factors based on Dvorkin-Mavko attenuation model, which is capable of simultaneously linking Qp and Qs of seismic and petrophysical logging datasets to key sediment properties of interest. In this paper, the compressional- and shear- wave quality factor Q's are measured from both OBS and sonic waveform datasets of Hydrate Ridge at Oregon Margin by centroid frequency shift approach. Then, according to the Bayesian theorem, the likelihood function consists of a multi-variate Gaussian distribution under the assumption that the error between measured and modeled Q's is Gaussian. Subsequently, the posterior is efficiently sampled by Differential-Evolution Markov-Chain Monte Carlo (Higdon, 2011). Combining the well data into this joint inversion can enormously mitigates the ambiguity and estimates more unknowns. The results for gas saturation and porosity is in good agreement with previous research in this area.