Subsidence caused by extraction of hydrocarbons and solution salt mining is a sensitive issue in the Netherlands. An extensive legal, technical and organisational framework is in place to ensure a high probability that such subsidence will stay within predefined limits. The key question is: how much subsidence is acceptable and at which rate? And: how can it be reliably assured that (future) subsidence will stay within these limits? To address the issue for the Wadden Sea area, the concept of ‘effective subsidence capacity’ is used. To determine the ‘effective subsidence capacity’, the maximum volumetric rate of relative sea-level rise, that can be accommodated in the long term, without environmental harm, is established first. The volume of sediment that can be transported and deposited by nature into the tidal basin where the subsidence is expected, ultimately determines this ‘limit of acceptable average subsidence rate’. The capability of the tidal basins to ‘capture’ sediment over the lunar cycle period of 18.6 years is the overall rate-determining step. Effective subsidence capacity is then the maximum average subsidence rate available for planning of human activities. It is obtained by subtracting the subsidence volume rate ‘consumed’ by natural relative subsidence in the area (sealevel rise plus natural shallow compaction) from the total long-term acceptable subsidence volume rate limit. In the operational procedure for mining companies, six-years-average expectation values of subsidence rates are used to calculate the maximum allowable production rates. This is done under the provision that production will be reduced or halted if the expected or actual subsidence rate (natural + man induced) is likely to exceed the limit of acceptable subsidence. Monitoring and management schemes ensure that predicted (6-year average) and actual (18.6-year average) subsidence rates stay within the limit of acceptable subsidence rate and that no damage is caused to the protected nature. A GPS based early warning system is used for early detection of unexpected behaviour. In support of SSM (State Supervision of Mines, the government regulator), TNO-AGE (an independent government advisory group) applies an independent Bayesian statistical analysis of all data, as they become available, to calculate the probability of scenario's under which future subsidence will exceed the defined limits. It is external to the operator's annual measurement and control loop and ensures that preventive actions can be taken in time in case such scenarios emerge. Regular communication keeps the authorities and the general public informed on the use of the effective subsidence capacity to demonstrate that the actual average subsidence rate stays strictly within the defined bounds and that, from a scientific point of view, there is no reasonable doubt that damage to the tidal system will not occur now or in the future.@en

Understanding and predicting surface movement is important both technically and for social reasons. The shallow processes contributing to subsidence include construction works, peat oxidation, clay compaction, and groundwater withdrawal; deep causes are hydrocarbon and salt production. We describe an inversion procedure we have devised to disentangle the deep and shallow causes of surface movement. It employs a Bayesian inversion scheme, using forward models and other ‘a priori’ information about shallow and deep compaction. Parameter estimation thus takes place at two different depths, thereby disentangling the deep and shallow compaction processes responsible for surface movement. The uncertainty in the surface measurements and ‘a priori’ estimates is naturally incorporated. Furthermore, spatial and temporal correlations can be taken into account through inclusion of the covariance matrix. The inversion scheme is demonstrated for two synthetic cases. The first combines a compacting gas field and a compacting shallow peat layer. We demonstrate that assumptions on the shape of the subsidence bowl are not necessary. We also show how neglecting either deep or shallow causes of subsidence can produce spurious results. The advantage of using the ‘a priori’ estimates of the compaction and the covariance matrix obtained by Monte Carlo simulations is demonstrated with a second synthetic example involving two polders and different depths of their water table. A robust solution is obtained for each polder unit, while a simpler (and faster) ‘a priori’ estimate based on the expected average clay thickness fails to reproduce the actual compaction. Monte Carlo simulations can also be applied to compaction in depleting gas reservoirs. Information on spatial correlations is often available, even when the absolute values of the ‘a priori’ compaction data are quite uncertain. Explicitly incorporating such ‘a priori’ known spatial correlations improves the result significantly.@en

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.@en

Surface subsidence can have major repercussions. A classic example is the seabed above the Ekofisk field, offshore Norway, where excessive subsidence made it necessary to raise the drilling platform by 6 m in the 1980s. On land, subsidence may significantly increase the risk of damage to buildings and infrastructure. But, there is more to say about subsidence. Observations of subsidence can also give us a better handle on the subsurface processes like compaction behaviour of a reservoir, and can tell us more about the reservoir itself: about undrained compartments or the strength of the aquifer. However, to get the information from subsidence data, you have to carefully follow an inver-sion procedure. This inversion exercise is a big challenge, in which all the available knowledge has to be used to the fullest possible extent. In this article we report on the work we have recently performed in this area. @en