Click here to download the press release (Pdf format) announcing the online event co-organised by INFACT, PACIFIC and the NHM on December 3-4, 2020.

Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field

The Groningen gas field is one of the largest gas fields in Europe. The continuous gas extraction led to an induced seismic activity in the area. In order to monitor the seismic activity and study the gas field many permanent and temporary seismic arrays were deployed. In particular, the extraction of the shear wave velocity model is crucial in seismic hazard assessment. Local S-wave velocity-depth profiles allow us the estimation of a potential amplification due to soft sediments.

Ambient seismic noise tomography is an interesting alternative to traditional methods that were used in modelling the S-wave velocity. The ambient noise field consists mostly of surface waves, which are sensitive to the Swave and if inverted, they reveal the corresponding S-wave structures.

In this study, we present results of a depth inversion of surface waves obtained from the cross-correlation of 1 month of ambient noise data from four flexible networks located in the Groningen area. Each block consisted of about 400 3-C stations. We compute group velocity maps of Rayleigh and Love waves using a straight-ray surface wave tomography. We also extract clear higher modes of Love and Rayleigh waves.

The S-wave velocity model is obtained with a joint inversion of Love and Rayleigh waves using the Neighbourhood Algorithm. In order to improve the depth inversion, we use the mean phase velocity curves and the higher modes of Rayleigh and Love waves. Moreover, we use the depth of the base of the North Sea formation as a hard constraint. This information provides an additional constraint for depth inversion, which reduces the S-wave velocity uncertainties.

The final S-wave velocity models reflect the geological structures up to 1 km depth and in perspective can be used in seismic risk modelling.

Train traffic as a powerful noise source for monitoring active faults with seismic interferometry.

Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth is found to be nearly impossible to achieve. We show that seismic noise generated by vehicle traffic, and especially heavy freight trains, can be turned into a powerful repetitive seismic source to continuously probe the Earth's crust at a few kilometers depth. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train‐generated seismic signals allow daily reconstruction of direct P body waves probing the San Jacinto Fault down to 4‐km depth. This new approach may facilitate monitoring most of the San Andreas Fault system using the railway and highway network of California.

Monitoring of fields using body and surface waves reconstructed from passive seismic ambient noise

There are important economic, environmental and societal reasons for monitoring production from oil, gas and geothermal fields. Unfortunately, standard microseismic monitoring is often not useful due to low levels of microseismicity. We propose to use body and surface waves reconstructed from ambient seismic noise for such monitoring. In this work, we use seismic data recorded from a dense sensor array at the Groningen gas field in northern Holland and show how direct P-waves can be extracted from the ambient noise cross correlations and then used to monitor seismic velocity variations over time. This approach has advantages over the use of coda wave interferometry due to the ability to localise such changes in the subsurface. We show how both direct and refracted (head) P-waves as well as Rayleigh surface waves can be used for such field monitoring, with changes of ∼1% being resolved. Both fundamental and first overtone Rayleigh waves are used to localise such changes, which correspond nicely to known geology to within 100 m.

Noise-based passive ballistic wave seismic monitoring on an active volcano

Monitoring temporal changes of volcanic interiors is important to understand magma, fluid pressurization and transport leading to eruptions. Noise-based passive seismic monitoring using coda wave interferometry is a powerful tool to detect and monitor very slight changes in the mechanical properties of volcanic edifices. However, the complexity of coda waves limits our ability to properly image localized changes in seismic properties within volcanic edifices. In this work, we apply a novel passive ballistic wave seismic monitoring approach to examine the active Piton de la Fournaise volcano (La Réunion island). Using noise correlations between two distant dense seismic arrays, we find a 2.4 per cent velocity increase and −0.6 per cent velocity decrease of Rayleigh waves at frequency bands of 0.5–1 and 1–3 Hz, respectively. We also observe a −2.2 per cent velocity decrease of refracted P waves at 550 m depth at the 6–12 Hz band. We interpret the polarity differences of seismic velocity changes at different frequency bands and for different wave types as being due to strain change complexity at depth associated with subtle pressurization of the shallow magma reservoir. Our results show that velocity changes measured using ballistic waves provide complementary information to interpret temporal changes of the seismic properties within volcanic edifices.

Noise-based ballistic wave passive seismic monitoring. Part 1: body waves

Unveiling the mechanisms of earthquake and volcanic eruption preparation requires improving our ability to monitor the rock mass response to transient stress perturbations at depth. The standard passive monitoring seismic interferometry technique based on coda waves is robust but recovering accurate and properly localized P- and S-wave velocity temporal anomalies at depth is intrinsically limited by the complexity of scattered, diffracted waves. In order to mitigate this limitation, we propose a complementary, novel, passive seismic monitoring approach based on detecting weak temporal changes of velocities of ballistic waves recovered from seismic noise correlations. This new technique requires dense arrays of seismic sensors in order to circumvent the bias linked to the intrinsic high sensitivity of ballistic waves recovered from noise correlations to changes in the noise source properties. In this work we use a dense network of 417 seismometers in the Groningen area of the Netherlands, one of Europe's largest gas fields. Over the course of 1 month our results show a 1.5 per cent apparent velocity increase of the P wave refracted at the basement of the 700-m-thick sedimentary cover. We interpret this unexpected high value of velocity increase for the refracted wave as being induced by a loading effect associated with rainfall activity and possibly canal drainage at surface. We also observe a 0.25 per cent velocity decrease for the direct P-wave travelling in the near-surface sediments and conclude that it might be partially biased by changes in time in the noise source properties even though it appears to be consistent with complementary results based on ballistic surface waves presented in a companion paper and interpreted as a pore pressure diffusion effect following a strong rainfall episode. The perspective of applying this new technique to detect continuous localized variations of seismic velocity perturbations at a few kilometres depth paves the way for improved in situ earthquake, volcano and producing reservoir monitoring.

Noise-based ballistic wave passive seismic monitoring – Part 2: surface waves

We develop a new method to monitor and locate seismic velocity changes in the subsurface using seismic noise interferometry. Contrary to most ambient noise monitoring techniques, we use the ballistic Rayleigh waves computed from 30 d records on a dense nodal array located above the Groningen gas field (the Netherlands), instead of their coda waves. We infer the daily relative phase velocity dispersion changes as a function of frequency and propagation distance with a cross-wavelet transform processing. Assuming a 1-D velocity change within the medium, the induced ballistic Rayleigh wave phase shift exhibits a linear trend as a function of the propagation distance. Measuring this trend for the fundamental mode and the first overtone of the Rayleigh waves for frequencies between 0.5 and 1.1 Hz enables us to invert for shear wave daily velocity changes in the first 1.5 km of the subsurface. The observed deep velocity changes (±1.5 per cent) are difficult to interpret given the environmental factors information available. Most of the observed shallow changes seem associated with effective pressure variations. We observe a reduction of shear wave velocity (–0.2 per cent) at the time of a large rain event accompanied by a strong decrease in atmospheric pressure loading, followed by a migration at depth of the velocity decrease. Combined with P-wave velocity changes observations from a companion paper, we interpret the changes as caused by the diffusion of effective pressure variations at depth. As a new method, noise-based ballistic wave passive monitoring could be used on several dynamic (hydro-)geological targets and in particular, it could be used to estimate hydrological parameters such as the hydraulic conductivity and diffusivity.