SUMMARY 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.
SUMMARY 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.
SUMMARY 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.
Passive monitoring via coda-wave interferometry is now widely used to follow temporal changes of seismic wave speed in the crust due to tectonic, volcanic or environmental forcing. However, this method is still limited by its poor spatial resolution which prevents accurate location of the source of the velocity change. Here we show that, with a dense seismic array and intense spatial averaging, we can retrieve ballistic P-waves and Rayleigh waves from daily ambient-noise correlations. Measuring their time-shift in the time vs. offset domain for subsequent days allows us to monitor and locate velocity changes in the near-surface due to pore-pressure variations caused by rainfall and atmospheric pressure changes. This study paves the way to reservoir monitoring applications, especially for ground water resources management. Presentation date: Wednesday, October 14, 2020 Session Start Time: 1:50 PM Presentation Time: 2:40 PM Location: 361A Presentation Type: Oral
Passive seismic imaging is a low-impact, low-cost technique that can be used for exploration and evaluation of ore deposits. Recent development of autonomous seismic recorders ("nodes") allows for reliable continuous recording of seismic data for weeks or months at a time. In addition to improving field operations for traditional 3D active-source reflection surveys, nodes greatly increase the flexibility of seismic survey design and, most importantly, permit low-cost collection of dense passive seismic data with minimal impact on the local environment. The technique uses ambient seismic noise from natural and anthropogenic sources for subsurface imaging and monitoring. A seismic velocity model built from analysis of surface wave dispersion curves is used to establish the structure, lithology and physical characteristics of materials in the sub-surface. The results can be used alone or jointly with other geophysical or geological data, or employed to improve imaging of active source data. The Sally platinum-group metal (PGM) Deposit in Ontario, Canada is located at the North margin of the Proterozoic Coldwell Complex, a ring-shaped series of gabbros overlain by syenites. The goal of the seismic survey was to determine the structure and geometry of the Eastern Gabbros, a series of high-density, seismically-fast gabbros and pyroxenites that host the mineralization. The resulting surface wave velocity model traced the lower margin of the Eastern Gabbros and also identified a strong velocity anomaly in Archean footwall granodiorite to the north (below) the main intrusion. This anomaly is 500m wide and 2000m in length, and extends from near the surface to a depth of approximately 1.5 km. The anomaly seems to coincide with a magnetic anomaly and is tentatively interpreted as a pyroxenite intrusion of the type that hosts the PGM mineralisation. Presentation Date: Wednesday, October 14, 2020 Session Start Time: 1:50 PM Presentation Time: 3:55 PM Location: 360C Presentation Type: Oral
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.
Passive seismic imaging is a low-impact, low-cost technique that can be used to explore for and evaluate oil and gas deposits. Recent development of autonomous seismic recorders ("nodes") allows for reliable continuous recording of seismic data for weeks or months at a time. In addition to improving field operations for traditional 3D active-source reflection surveys, nodes greatly increase the flexibility of seismic survey design and, most importantly, permit low-cost collection of dense passive seismic data with minimal impact on the local environment. The technique uses ambient seismic noise from natural and anthropogenic sources for subsurface imaging and monitoring. Cross-correlation between receiver pairs of stations is used to extract the Green function and a near-surface velocity model can be estimated from the analysis of surface wave dispersion curves obtained from the cross-correlated data. This model is then used to establish the structure, lithology and physical characteristics of materials in the sub-surface. The results can be used either alone or jointly with other geophysical or geological data, or employed to improve imaging of active source data. Here we show an example of application of the method in the Dolomite area, Nevada, USA. This survey aimed to characterize the ground in order to identify possible location of oil in the area.
An understanding of the thickness of the cover is important for many aspects of human activities such as seismic hazard characterization, infrastructure projects, extraction of different types of mineral resources or fossil fuel (coal, oil and natural gas), and characterization of groundwater aquifers in bedrock formations. Many mineral deposits are overlain by younger cover (sediments, soil or alluvium) which complicates exploration. Most investigation of cover thickness is done by drilling but the demand for more data is increasing. Fulfilling this need with existing methods is either imprecise or expensive, cumbersome and sometimes risky. Passive seismic imaging is a low-impact, low-cost technique that can be used for exploration and evaluation of cover thickness. Recent development of autonomous seismic recorders ("nodes") allows for reliable continuous recording of seismic data for weeks or months at a time. In addition to complementing traditional 3D active-source reflection surveys, autonomous nodes greatly increase the flexibility of seismic survey design and, most importantly, permit low-cost collection of dense passive seismic data with minimal impact on the local environment. In this abstract, we present a few applications of our ambient noise surface wave tomography (ANSWT) for cover mapping at different scales. Two examples of mineral exploration are presented as well as an application used for seismic hazard characterization. All three results are ground-truthed using borehole information or other geophysical results. The different applications of ANSWT presented were successful for cover mapping because of the sharp seismic wave velocity contrasts usually encountered at the interface between cover and basement. The ease in the field deployment and the low cost and environmental impact makes this imaging method particularly suitable for large cover-mapping surveys.
