Time-dependent Inversion of Surface Subsidence due to Dynamic Reservoir Compaction

Muntendam-Bos, A.G.; Kroon, I. C.; Fokker, P.A.

doi:10.1007/s11004-007-9135-3

Cited by 19 publications

(24 citation statements)

References 22 publications

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“…One way to do this is to extend elastic solutions so that they include viscoelasticity (Fokker & Orlic 2006). Muntendam-Bos et al (2008) have used Fokker & Orlic's (2006) viscoelastic solution superposition method with a suitable inversion scheme to find the set of sources that provides the best possible match to a specific time-dependent subsidence measurement. These techniques work well but the focus is on matching already-observed response.…”

Section: P R E V I O U S At T E M P T S T O M O D E L L I N G P Ro D mentioning

confidence: 99%

Ground motions induced by a producing hydrocarbon reservoir that is overlain by a viscoelastic rocksalt layer: a numerical model

Marketos¹,

Govers²,

Spiers³

2015

Geophys. J. Int.

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S U M M A R YHydrocarbon reservoir pressure depletion leads to stress changes inside the reservoir and ground deformation which is registered at the surface as subsidence. As reservoirs are often overlain by layers of rocksalt (or other evaporites), which are materials that flow so as to relax stresses inside them, there is the potential for time-varying surface subsidence. This work focuses on understanding the macroscopic mechanisms that lead to rocksalt flow-induced ground displacements. A Finite Element Model is used for this purpose in which the rocksalt layer is represented by a viscoelastic Maxwell material. Two distinct mechanisms that lead to displacement are observed. These are active during different stages of the deformation and have different timescales associated with them. An important observation is that the timescale for deformation that is measured at the ground surface is not equal to the timescale for deformation of a viscoelastic material element, but can be many times larger than that. The sensitivity of the response to the thickness and location of the rocksalt layer is also presented. Conclusions are drawn which allow for the relative importance of the presence of the rocksalt layer to be assessed and for a framework for understanding time-dependent subsidence above producing hydrocarbon reservoirs to be developed. Finally the changes in stress distribution around a producing reservoir are also briefly discussed.

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Section: P R E V I O U S At T E M P T S T O M O D E L L I N G P Ro D mentioning

confidence: 99%

Ground motions induced by a producing hydrocarbon reservoir that is overlain by a viscoelastic rocksalt layer: a numerical model

Marketos¹,

Govers²,

Spiers³

2015

Geophys. J. Int.

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“…In this case, the global bias could be incorporated into the model by co-estimating an offset between the model and the InSAR displacement [52] (case A). Alternatively, the mean phase of each image is again used as the reference phase for InSAR (case B).…”

Section: Modeling Subsidence In Gudao Oilfieldmentioning

confidence: 99%

Land Subsidence over Oilfields in the Yellow River Delta

Liu

et al. 2015

Remote Sensing

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Subsidence in river deltas is a complex process that has both natural and human causes. Increasing human activities like aquaculture and petroleum extraction are affecting the Yellow River delta, and one consequence is subsidence. The purpose of this study is to measure the surface displacements in the Yellow River delta region and to investigate the corresponding subsidence source. In this paper, the Stanford Method for Persistent Scatterers (StaMPS) package was employed to process Envisat ASAR images collected between 2007 and 2010. Consistent results between two descending tracks show subsidence with a mean rate up to 30 mm/yr in the radar line of sight direction in Gudao Town (oilfield), Gudong oilfield and Xianhe Town of the delta, each of which is within the delta, and also show that subsidence is not uniform across the delta. Field investigation shows a connection between areas of non-uniform subsidence and of petroleum extraction. In a 9 km 2 area of the Gudao Oilfield, a poroelastic disk reservoir model is used to model the InSAR derived displacements. In general, OPEN ACCESSRemote Sens. 2015, 7 1541 good fits between InSAR observations and modeled displacements are seen. The subsidence observed in the vicinity of the oilfield is thus suggested to be caused by fluid extraction.

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“…Muntendam-Bos et al [18] recently introduced an inversion scheme that utilizes all available geological information to derive a time-dependent model estimate for the reservoir compaction. The method uses both the prior model covariance matrix and the data covariance matrix, which incorporate the spatial and temporal correlations between model parameters and data, respectively.…”

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confidence: 99%

“…Taking these relationships into account through the model covariance matrix enhances the influence of the data on the inverted model estimate. Therefore, unlike more common inversion procedures, this method is able to properly resolve the characteristics of dynamic reservoir compaction (see [18] for details).…”

mentioning

confidence: 99%

“…The synthetic model that Muntendam-Bos et al [18] use as an example takes only one uncertain parameter (the transmissibility of the free water level) into account, thus assuming that all other parameters are perfectly known. In order to apply the procedure to real field cases, the behavior of the inversion procedure with respect to multiple uncertain parameters needs to be evaluated.…”

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Unraveling reservoir compaction parameters through the inversion of surface subsidence observations

Muntendam-Bos¹,

Fokker²

2008

Comput Geosci

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In an attempt to derive more information on the parameters driving compaction, this paper explores the feasibility of a method utilizing data on compactioninduced 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.

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Time-dependent Inversion of Surface Subsidence due to Dynamic Reservoir Compaction

Cited by 19 publications

References 22 publications

Ground motions induced by a producing hydrocarbon reservoir that is overlain by a viscoelastic rocksalt layer: a numerical model

Ground motions induced by a producing hydrocarbon reservoir that is overlain by a viscoelastic rocksalt layer: a numerical model

Land Subsidence over Oilfields in the Yellow River Delta

Unraveling reservoir compaction parameters through the inversion of surface subsidence observations

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