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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. [ABSTRACT FROM AUTHOR]

A key element of quantifying both the hazard and risk due to induced earthquakes is a suite of appropriate ground-motion prediction equations (GMPEs) that encompass the possible shaking levels due to such events. Induced earthquakes are likely to be of smaller magnitude and shallower focal depth than the tectonic earthquakes for which most GMPEs are derived. Furthermore, whereas GMPEs for moderate-to-large magnitude earthquakes are usually derived to be transportable to different locations and applications, taking advantage of the limited regional dependence observed for such events, the characteristics of induced earthquakes warrant the development of application-specific models. A preliminary ground-motion model for induced seismicity in the Groningen gas field in The Netherlands is presented as an illustration of a possible approach to the development of these equations. The GMPE is calibrated to local recordings of small-magnitude events and captures the epistemic uncertainty in the extrapolation to larger magnitude considered in the assessment of the resulting hazard and risk. [ABSTRACT FROM AUTHOR]

Probabilistic aggregation and dependency estimation are essential in portfolio methods, production forecasting, and resource estimation. The use of arithmetic addition understates the true value of the resource estimates within a portfolio of fields. Potentially, this could result in deferral of a project, or loss of lucrative business and commercial opportunities, such as project investment, facilitysizing decisions, or incremental gas-supply commitments. A statistically robust method for aggregation of resource estimates that appropriately uses expert opinion is presented in this paper. Using two integrated-project examples, this paper introduces new methods for (1) probabilistic aggregation of the resource estimates for multiple fields and (2) estimating a measure of dependency between the resource estimates of individual fields. The new analytical method for probabilistic aggregation is based on multivariate skew-normal (MSN) distributions, which can model a wide range of skewness through a shape parameter and are used heavily in financial and actuarial applications. In studies of the fields in which the multiple-realizations appestimation theroach is used as a basis for the uncertainty framework, tornado diagrams are generated routinely to describe the dependence of the field resources on reservoir parameters. The improved method for evaluating measures of dependency between the resource estimates within a portfolio of fields uses these tornado diagrams as a basis. Incorporating the expertise and knowledge of geologists and petroleum engineers is a critical element of the method. These methods for probabilistic aggregation and estimating dependencies were developed within the context of the oil industry, but their use is not limited to the oil industry. They are general and can be used in other probabilistic-aggregation problems. Application of these techniques requires limited time and effort, compared to individual-field studies, and can have a profound impact on the uncertainty range of the total resources for the portfolio of fields. [ABSTRACT FROM AUTHOR]