Pierre Boué

Body wave extraction and tomography at Long Beach, California, with ambient‐noise interferometry

We retrieve P diving waves by applying seismic interferometry to ambient-noise records observed at Long Beach, California, and invert travel times of these waves to estimate 3-D P wave velocity structure. The ambient noise is recorded by a 2-D dense and large network, which has about 2500 receivers with 100 m spacing. Compared to surface wave extraction, body wave extraction is a much greater challenge because ambient noise is typically dominated by surface wave energy. For each individual receiver pair, the cross-correlation function obtained from ambient-noise data does not show clear body waves. Although we can reconstruct body waves when we stack correlation functions over all receiver pairs, we need to extract body waves at each receiver pair separately for imaging spatial heterogeneity of subsurface structure. Therefore, we employ two filters after correlation to seek body waves between individual receiver pairs. The first filter is a selection filter based on the similarity between each correlation function and the stacked function. After selecting traces containing stronger body waves, we retain about two million correlation functions (35% of all correlation functions) and successfully preserve most of body wave energy in the retained traces. The second filter is a noise suppression filter to enhance coherent energy (body waves here) and suppress incoherent noise in each trace. After applying these filters, we can reconstruct clear body waves from each virtual source. As an application of using extracted body waves, we estimate 3-D P wave velocities from these waves with travel time tomography. This study is the first body wave tomography result obtained from only ambient noise recorded at the ground surface. The velocity structure estimated from body waves has higher resolution than estimated from surface waves.

Body and surface wave reconstruction from seismic noise correlations between arrays at Piton de la Fournaise volcano

Body wave reconstruction from ambient seismic noise correlations is an important step toward improving volcano imaging and monitoring. Here we extract body and surface waves that propagate in Piton de la Fournaise volcano on La Reunion island using ambient noise cross correlation and array-processing techniques. Ambient noise was continuously recorded at three dense arrays, each comprising 49 geophones. To identify and enhance the Greens function from the ambient noise correlation, we apply a double beamforming (DBF) technique between the array pairs. The DBF allows us to separate surface and body waves, direct and reflected waves, and multipathing waves. Based on their azimuths and slownesses, we successfully extract body waves between all the combinations of arrays, including the wave that propagates through the active magmatic system of the volcano. Additionally, we identify the effects of uneven noise source distribution and interpret the surface wave reflections.

Locating Microseism Sources Using Spurious Arrivals in Intercontinental Noise Correlations

The accuracy of Greens functions retrieved from seismic noise correlations in the microseism frequency band is limited by the uneven distribution of microseism sources at the surface of the Earth. As a result, correlation functions are often biased as compared to the expected Greens functions, and they can include spurious arrivals. These spurious arrivals are seismic arrivals that are visible on the correlation and do not belong to the theoretical impulse response. In this article, we propose to use Rayleigh wave spurious arrivals detected on correlation functions computed between European and United States seismic stations to locate microseism sources in the Atlantic Ocean. We perform a slant stack on a time-distance gather of correlations obtained from an array of stations that comprises a regional deployment and a distant station. The arrival times and the apparent slowness of the spurious arrivals lead to the location of their source, which is obtained through a grid search procedure. We discuss improvements in the location through this methodology as compared to classical back-projection of microseism energy. This method is interesting because it only requires an array and a distant station on each side of an ocean, conditions that can be met relatively easily.