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Unraveling reservoir compaction parameters through the inversion of surface subsidence observations

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Author: Muntendam-Bos, A.G. · Fokker, P.A.
Type:article
Date:2009
Institution: TNO Bouw en Ondergrond
Source:Geophysical Research Letters, 1, 13, 43-55
Identifier: 241322
Keywords: Compaction · Covariance · Delay · Inversion · Subsidence · Compaction · Markov processes · Monte Carlo methods · Natural gas fields · Statistical methods · Subsidence · Bayesian analysis · compaction · correlation · data assimilation · gas field · hydrocarbon reservoir · inverse analysis · Markov chain · Monte Carlo analysis · observational method · parameterization · spatiotemporal analysis · subsidence · Benelux · Eurasia · Europe · Netherlands · Western Europe

Abstract

In an attempt to derive more information on the parameters driving compaction, this paper explores the feasibility of a method utilizing data on compaction-induced subsidence. We commence by using a Bayesian inversion scheme to infer the reservoir compaction from subsidence observations. The method's strength is that it incorporates all the spatial and temporal correlations imposed by the geology and reservoir data. Subsequently, the contributions of the driving parameters are unravelled. We apply the approach to a synthetic model of an upscaled gas field in the northern Netherlands. We find that the inversion procedure leads to coupling between the driving parameters, as it does not discriminate between the individual contributions to the compaction. The provisional assessment of the parameter values shows that, in order to identify adequate estimate ranges for the driving parameters, a proper parameter estimation procedure (Markov Chain Monte Carlo, data assimilation) is necessary. © Springer Science+Business Media B.V. 2008.