Derivation of a near-surface damping model for the Groningen gas field

Abstract

Summary Seismic damping of near-surface deposits is an important input to site-response analysis for seismic hazard assessment. In Groningen, the Netherlands, gas production from a reservoir at 3 km depth causes seismicity. Above the gas field, an 800 m thick layer of unconsolidated sediments exist, which consists of a mixture of sand, gravel, clay and peat strata. Shear waves induced at 3 km depth experience most of their anelastic attenuation in these loose sediments. A good estimate of damping is therefore crucial for modeling realistic ground-motion levels. In Groningen, we take advantage of a large network of 200 m deep vertical arrays to estimate damping from recordings of the induced events. As a first step, we apply seismic interferometry by deconvolution to estimate local transfer functions over these vertical arrays. Subsequently, two different methods are employed. The first is the ’up-going’ method, where the amplitude decay of the retrieved up-going wave is used. The second is the ’up-down’ method, where the amplitude difference between retrieved up- and down-going waves is utilized. For the up-going method, the amplitude of the up-going direct wave is affected by both elastic and anelastic effects. In order to estimate the anelastic attenuation it is necessary to remove the elastic amplification first. Despite the fact that elastic compensation could be determined quite accurately, non-physical damping values were estimated for a number of boreholes. Likely, the underlying cause was small differences in effective response functions of geophones at different depths. It was found that the up-down method is more robust. With this method, elastic propagation corrections are not needed. In addition, small differences in in situ geophone response are irrelevant because the up- and down-going waves retrieved at the same geophone, are used. For the 1D case we showed that for estimating the local transfer function, the complex reverberations need to be included in the interferometric process. Only when this is done, the transfer function does not contain elastic transmission loss and Q estimation can be made without knowing the soil profile in detail. Uncertainty in the estimated damping was found from the signal-to-noise ratio of the estimated transfer function. The Q profiles estimated with the up-down method were used to derive a damping model for the top 200 m of the entire Groningen field. A scaling relation was derived by comparing estimated Q profiles with low-strain damping profiles that were constructed using published models for low-strain damping linked to soil properties. This scaling relation, together with the soil-properties based damping model, allowed up-scaling of the model to each grid-cell in the Groningen field. For depths below 200 m, damping was derived from the attenuation of the microseism over Groningen. The mean damping model, over a frequency band between 2 and 20 Hz, was estimated to be 2.0% (0-50 m depth), 1.3% (50-100 m), 0.66% (100-150 m), 0.57% (150-200 m) and 0.5% (200-580 m).

Ground-motion prediction models for induced earthquakes in the Groningen gas field, the Netherlands

“…The framework of the V4 model has remained unchanged, with each subsequent version representing a refinement based on improved modelling, for example of the soil damping model (Ruigrok et al 2022), and the continued growth of the groundmotion database. Up to the V5 model, the derivation used surface recordings from the B-network and geophone recordings at 200 m depth from the G-network (see Section 3), because measured V S profiles were available at the former but not the latter, and the intention was to avoid the additional uncertainty in the transfer functions and AFs used to deconvolve the G-station recordings.…”

“…The basic framework is presented below, but the reader interested in greater detail regarding the model derivation can refer to Bommer et al (2022). Using the V S profiles down to the NS_B horizon at each recording station, together with the damping profiles (Ruigrok et al 2022), transfer functions (TFs) are developed to deconvolve the Fourier amplitude spectra (FAS) to the reference rock horizon; here, as in all the site response modelling, we make the standard assumption of vertically propagating waves. The high-frequency damping parameter is estimated using the method of Anderson and Hough (1984) and then the FAS are inverted to estimate the geometric spreading coefficients (using the hinge distances constrained by finite difference simulations of the wave propagation), the average quality factor Q (using a layered Q model), and the stress parameter Δσ.…”

A database of ground motion recordings, site profiles, and amplification factors from the Groningen gas field in the Netherlands

“…The damping model was derived from analysis of the borehole records, the process sometimes also leading to small adjustments of the shallowest part of the V S profiles, where the measurements may not be very reliable. The derivation of the damping model for the Groningen field is presented in Ruigrok et al (2022), For stations where no measurements took place, the V S profiles inferred from the model of Kruiver et al (2017a) for the locations of the stations are provided instead. These stations are listed in a table contained in the database.…”

“…The damping model was derived from analysis of the borehole records, the process sometimes also leading to small adjustments of the shallowest part of the V S profiles, where the measurements may not be very reliable. The derivation of the damping model for the Groningen field is presented in Ruigrok et al (2022),…”

“…The complete GMM consists of predictions at a deep (∼800 m) buried rock horizon, to which the nonlinear amplification factors for the overlying soil columns are applied (Bommer et al, 2017b). The GMM for response spectral accelerations has evolved through numerous iterations and extensive review by an international panel of experts (see “Acknowledgments” section), incorporating the results of simulations (Edwards et al, 2019), derivation of a field-specific model of soil damping (Ruigrok et al, 2022), and inclusion of scenario-dependence in the linear amplification factors at short periods (Stafford et al, 2017). The final GMM (Bommer et al, 2022a) is now available at the NAM website (see “References” section).…”