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Time-dependent inversion of surface subsidence due to dynamic reservoir compaction

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Author: Muntendam-Bos, A.G. · Kroon, I.C. · Fokker, P.A.
Type:article
Date:2008
Institution: TNO Bouw en Ondergrond
Source:Mathematical Geosciences, 2, 40, 159-177
Identifier: 241240
Keywords: Geosciences · Compaction · Covariance · History matching · Inversion · Subsidence · Computer simulation · Covariance matrix · Mathematical models · Monte Carlo methods · Pressure drop · Subsidence · compaction · correlation · covariance analysis · data inversion · estimation method · matrix · model validation · Monte Carlo analysis · nonlinearity · numerical model · subsidence · uncertainty analysis

Abstract

We introduce a novel, time-dependent inversion scheme for resolving temporal reservoir pressure drop from surface subsidence observations (from leveling or GPS data, InSAR, tiltmeter monitoring) in a single procedure. The theory is able to accommodate both the absence of surface subsidence estimates at sites at one or more epochs as well as the introduction of new sites at any arbitrary epoch. Thus, all observation sites with measurements from at least two epochs are utilized. The method uses both the prior model covariance matrix and the data covariance matrix, which incorporates the spatial and temporal correlations between model parameters and data, respectively. The incorporation of the model covariance implicitly guarantees smoothness of the model estimate, while maintaining specific geological features like sharp boundaries. Taking these relations into account through the model covariance matrix enhances the influence of the data on the inverted model estimate. This leads to a better defined and interpretable model estimate. The time-dependent aspect of the method yields a better constrained model estimate and makes it possible to identify non-linear acceleration or delay in reservoir compaction. The method is validated by a synthetic case study based on an existing gas reservoir with a highly variable transmissibility at the free water level. The prior model covariance matrix is based on a Monte Carlo simulation of the geological uncertainty in the transmissibility. © International Association for Mathematical Geology 2008.