Accurate knowledge of the ground conditions is critical for geo-risk assessment purposes such as mapping shallow gas hydrate deposits, over-pressured zones, or geological anomalies. Traditional seismic reflection profiling is a relatively fast and flexible method of processing seismic data to recover information on the spatial variation in facies boundaries and subsurface structure.
However, the method usually does not provide quantitative information on the composition of the sediments and their physical properties. Seismic inversion is a method to convert the wave signals from time-to space-domain and derive specific material properties by using iterative numerical modeling. In this paper, we introduce a probabilistic seismic inversion scheme to recover the vertical profiles of the shallow soil bulk density from marine seismic survey data.
This acoustic impedance inversion is based on the geophysical seismic convolution method and the reversible jump Markov chain Monte Carlo (rj-MCMC) method. The rj-MCMC is a recently developed stochastic sampling technique that allows the modeling to free the number of layers under the seafloor. Hence the number of soil units is estimated from the data in an objective manner. We applied this new approach to a single trace of post-stack seismic data, collected from the Hydrate Ridge area on the west coast of Oregon. Since the purpose of this shallow seismic inversion is to support the design of the offshore foundation, we focused on the relatively short length of seismic signals near the seafloor.
The inverted results of the bulk densities along the depth compare well with the field measurements performed at the nearby drilled borehole. This study introduces an advantage of the probabilistic seismic inversion approach to support shallow marine site characterization from low-frequency data, and we discuss the benefits of this new approach on geotechnical site characterization.
Source: Offshore Technology Conference, 4-7 May 2020, Houston, Texas, USA
Document ID: OTC-30573-MS