1‐D, 2‐D, and 3‐D Monte Carlo Ambient Noise Tomography Using a Dense Passive Seismic Array Installed on the North Sea Seabed

Abstract

AbstractIn a variety of geoscientific applications we require 3‐D maps of properties of the Earth's interior and the corresponding map of uncertainties to assess their reliability. On the seabed it is common to use Scholte wave dispersion data to infer these maps using inversion‐based imaging theory. Previously we introduced a 3‐D fully nonlinear Monte Carlo tomography method that inverts for shear velocities directly from frequency‐dependent travel time measurements and which improves accuracy of the results and better estimates uncertainties. Here for the first time we apply that method to real data and compare it to two previous methods. We cross correlated 6.5 hr of ambient noise data recorded on a dense seismic array over Grane, North Sea, and observed two Scholte wave modes. For each mode, phase velocity maps are estimated using Eikonal tomography, which are in turn used to study the shear‐wave velocity structure of the subsurface. We applied three nonlinear inversion methods to the Grane data: standard 1‐D depth inversions, a 2‐D joint inversion along a vertical cross section, and a fully 3‐D inversion. We compare the shear‐velocity and uncertainty structures estimated along the same 2‐D cross section. Thus we show that the standard 1‐D inversion method creates significant errors in the results due to the independence of those 1‐D inversions, whereas the 2‐D and 3‐D inversions improve results by accounting for lateral spatial correlations. The 3‐D inversion bypasses the initial seabed Eikonal tomography step, thus avoiding the errors that the initial step introduces into subsequent 1‐D and 2‐D inversions.