In order to inform decision-making regarding measures to mitigate the impact of induced seismicity in the Groningen gas field in the Netherlands, a comprehensive seismic risk model has been developed. Starting with gas production scenarios and the consequent reservoir compaction, the model generates synthetic earthquake catalogues which are deployed in Monte Carlo analyses, predicting ground motions at a buried reference rock horizon that are combined with nonlinear amplification factors to estimate response spectral accelerations at the surface. These motions are combined with fragility functions defined for the exposed buildings throughout the region to estimate damage levels, which in turn are transformed to risk in terms of injury through consequence functions. Several older and potentially vulnerable buildings are located on dwelling mounds that were constructed from soils and organic material as a flood defence. These anthropogenic structures are not included in the soil profile models used to develop the amplification factors and hence their influence has not been included in the risk analyses to date. To address this gap in the model, concerted studies have been identified to characterize the dwelling mounds. These include new shear-wave velocity measurements that have enabled dynamic site response analyses to determine the modification of ground shaking due to the presence of the mound. A scheme has then been developed to incorporate the dwelling mounds into the risk calculations, which included an assessment of whether the soil-structure interaction effects for buildings founded on the mounds required modification of the seismic fragility functions.

A comprehensive database that has been used to develop ground motion models for induced earthquakes in the Groningen gas field is provided in a freely accessible online repository. The database includes more than 8500 processed ground motion recordings from 87 earthquakes of local magnitude ML between 1.8 and 3.6, obtained from a large network of surface accelerographs and borehole geophones placed at 50 m depth intervals to a depth of 200 m. The 5%-damped pseudo-acceleration spectra and Fourier amplitude spectra of the records are also provided. Measured shear-wave velocity (VS) profiles, obtained primarily from seismic Cone Penetration Tests (CPTs), are provided for 80 of the ∼100 recording stations. A model representing the regional dynamic soil properties is presented for the entire gas field plus a 5 km onshore buffer zone, specifying lithology, VS, and damping for all layers above the reference baserock horizon located at about 800 m depth. Transfer functions and frequency-dependent amplification factors from the reference rock horizon to the surface for the locations of the recording stations are also included. The database provides a valuable resource for further refinement of induced seismic hazard and risk modeling in Groningen as well as for generic research in site response of thick, soft soil deposits and the characteristics of ground motions from small-magnitude, shallow-focus induced earthquakes.

Long-term exploration of the Groningen gas field in the Netherlands led to induced seismicity. Over the past nine years, an increasingly sophisticated Ground Motion Model (GMM) has been developed to assess the site response and the related seismic hazard. The GMM output strongly depends on the shear-wave velocity (V S ), among other input parameters. To date, V S model data from soil profiles (Kruiver et al., Bulletin of Earthquake Engineering, 15(9): 3555–3580, 2017; Netherlands Journal of Geosciences, 96(5): s215–s233, 2017) have been used in the GMM. Recently, new V S profiles above the Groningen gas field were constructed using ambient noise surface wave tomography. These so-called field V S data, even though spatially limited, provide an independent source of V S to check whether the level of spatial variability in the GMM is sufficient. Here, we compared amplification factors (AF) for two sites (Borgsweer and Loppersum) calculated with the model V S and the field V S (Chmiel et al., Geophysical Journal International, 218(3), 1781–1795, 2019 and new data). Our AF results over periods relevant for seismic risk (0.01–1.0 s) show that model and field V S profiles agree within the uncertainty range generally accepted in geo-engineering. In addition, we compared modelled spectral accelerations using either field V S or model V S in Loppersum to the recordings of an earthquake that occurred during the monitoring period (ML 3.4 Zeerijp on 8 January 2018). The modelled spectral accelerations at the surface for both field V S and model V S are coherent with the earthquake data for the resonance periods representative of most buildings in Groningen (T = 0.2 and 0.3 s). These results confirm that the currently used V S model in the GMM captures spatial variability in the site response and represents reliable input for the site response calculations.

<p>The site response input in the Groningen seismic hazard assessment is based on modelled shear-wave velocity (V<sub>S</sub>) profiles. Two sets of data were used to compare in situ (field) and model data of V<sub>S</sub>. The first set consists of data from several blocks of ~ 400 nodes. Inversion of passive seismic data from a coarse grid of ~ 6 km x 10 km resulted in V<sub>S</sub> profiles to a depth of 800 m and from a denser grid of ~ 1 km x 1 km more detail to a depth of 100 m. The field V<sub>S</sub> profiles were a combination these two depth ranges. The site response analysis based on either the field or model V<sub>S</sub> profiles showed on average similar amplification factors over periods relevant for seismic risk. The model V<sub>S</sub> profiles are therefore a good representation. The second set consists of V<sub>S</sub> data from MASW surveys on dwelling mounds. The local detailed field V<sub>S</sub> profiles reach a depth of 18 m. Site response analyses using the full model V<sub>S</sub> profiles or profiles with the top 18 m replaced by field V<sub>S</sub> showed that the amplification on dwelling mounds is underestimated significantly, on average by 7 to 28 %. Because of this, a frequency-dependent Penalty Factor has been derived. In the risk calculations, this Factor is to be applied to buildings on dwelling mounds to transform the estimated motions at the ground surface (based on model V<sub>S</sub>) into motions at the top of the dwelling mound.</p>

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