Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter
K. Beers (TU Delft - Civil Engineering & Geosciences)
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Abstract
This thesis explores the usage of the particle filter as a data assimilation technique to estimate subsurface processes, such as reservoir volume change from space-geodetic PS-InSAR surface measurements. The specific research area is Groningen, where subsidence is induced by hydrocarbon and salt production.
The satellite radar PS-InSAR technique is used for observing subsidence values in the line-of-sight for a Radarsat-2 descending and a TerraSAR ascending set of measurements. A geomechanical model, the Mogi point source, translates subsurface volume changes to surface deformation. The geomechanical model parameters are estimated by the data assimilation technique particle filter from the observed surface measurements.
The particle filter is tested on synthetic data in a couple of test situations with an identical twin experiment. In addition the knowledge of the synthetic data experiments is used in the particle filter application on the PS-InSAR
measurements of the Groningen gas field. A workflow is created in how to apply the steps of the particle filter on the PS-InSAR measurements in Groningen. Several solutions are developed for improving the fit between measurements and model.