scholarly journals The future of subsidence modelling: compaction and subsidence due to gas depletion of the Groningen gas field in the Netherlands

2017 ◽  
Vol 96 (5) ◽  
pp. s105-s116 ◽  
Author(s):  
Karin van Thienen-Visser ◽  
Peter A. Fokker

AbstractThe Groningen gas field has shown considerable compaction and subsidence since starting production in the early 1960s. The behaviour is understood from the geomechanical response of the reservoir pressure depletion. By integrating surface movement measurements and modelling, the model parameters can be constrained and understanding of the subsurface behaviour can be improved. Such a procedure has been employed to formulate new compaction and subsidence forecasts. The results are put into the context of an extensive review of the work performed in this field, both in Groningen and beyond. The review is used to formulate a way forward designed to integrate all knowledge in a stochastic manner.

2020 ◽  
Author(s):  
Reuben Zotz-wilson ◽  
Nikoletta Filippidou ◽  
Arjan Linden ◽  
Berend Antonie Verberne ◽  
Auke Barnhoorn

2017 ◽  
Vol 15 (9) ◽  
pp. 3555-3580 ◽  
Author(s):  
Pauline P. Kruiver ◽  
Ewoud van Dedem ◽  
Remco Romijn ◽  
Ger de Lange ◽  
Mandy Korff ◽  
...  

Author(s):  
Pauline P. Kruiver ◽  
Manos Pefkos ◽  
Erik Meijles ◽  
Gerard Aalbersberg ◽  
Xander Campman ◽  
...  

AbstractIn 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.


Author(s):  
K. van Thienen-Visser ◽  
J. P. Pruiksma ◽  
J. N. Breunese

Abstract. The Groningen gas field in the Netherlands is Europe's largest gas field. It has been produced since 1963 and production is expected to continue until 2080. The pressure decline in the field causes compaction in the reservoir which is observed as subsidence at the surface. Measured subsidence is characterized by a delay at the start of production. As linear compaction models cannot explain this behavior, alternative compaction models (e.g. Rate Type Compaction Model and Time Decay model) have been investigated that may explain the measured subsidence. Although the compaction models considered in this study give a good match to this delay, their forecasts are significantly different. Future measurements of subsidence in this area will indicate which type of compaction model is preferred. This will lead to better forecasts of subsidence in future. The pattern of over- and underestimation of the subsidence is similar for the compaction models investigated and tested. The pattern can be explained by differences in modeled porosity and aquifer activity illustrating the improvement of subsurface knowledge on the reservoir using subsidence measurements.


2020 ◽  
Vol 79 (11) ◽  
Author(s):  
Gudrun Richter ◽  
Sebastian Hainzl ◽  
Torsten Dahm ◽  
Gert Zöller

Author(s):  
Benjamin Edwards ◽  
Michail Ntinalexis

AbstractSeismic hazard and risk analyses are increasingly tapping into the previously underused resource of local weak-motion records. This is facilitating the development of local- or even application-specific models for the characterisation of earthquake ground motion. In turn, this offers the opportunity to derive non- or partially non-ergodic models and significantly reduce bias and uncertainty. However, weak-motion data, while carrying important information about local earthquake source, path and site effects, are susceptible to noise. We show that high-frequency noise has a record-, or region-specific, impact on pseudo-spectral acceleration (PSA). This impact depends on the shape of the records’ Fourier amplitude spectrum (FAS): PSA from moderately to highly damped ‘soil’ records (e.g. Groningen, the Netherlands) is much less susceptible to high-frequency noise than PSA from weakly damped ‘rock’ records (e.g. Eastern North America). We make use of simulated ground motion records to develop a parametric model for the lower usable period of PSA (Tmin). The model accounts for the impact of high-frequency noise on PSA, conditional on easily measured parameters characterising the shape of a record’s FAS. We then present a workflow, describing processing undertaken for records of induced seismicity from the Groningen gas field. The workflow includes the definition of maximum and minimum usable frequencies and periods of FAS and PSA, respectively. As part of the workflow, we present an approach that considers multiple estimates of Tmin. These include the parametric model and, additionally, record-specific hybrid simulations that artificially extend or modify time series’ FAS beyond the noise floor to assess subsequent impacts on PSA.


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