Time-lapse (4D) seismic data can be integrated into history matching by comparing predicted and observed data in various domains. These include the time domain (time traces), seismic attributes, or petro-elastic properties such as acoustic impedance. Each domain requires different modelling methods and assumptions as well as data handling workflows. The aim of this work is to investigate the degree to which the choice of domain influences theoutcome of history matching on the choice of best model and associated uncertainties. Another aspect of history matching is that long simulations often pose an obstacle for an automatic approach. In this study we use appropriately upscaled models manageable in the automatic history matching loop.We apply manual and assisted seismic history matching to the Schiehallion field. In the assisted approach, the optimization loop is driven by a stochastic algorithm, while the manual workflow is based on a qualitative comparison of 4D seismic maps. By upscaling we obtained an order of magnitude gain in performance. Accurate upscaling was ensured by thorough volume and transmissibility calculation within regions. The parameterisation of the problem is based on a pattern of seismically derived geobodies with specified transmissibility multipliers between the regions. Seismic predictions are made through petroelastic modelling, 1D convolution, coloured inversion and calculation of different attributes.We were able to achieve a reasonable match of production and 4D seismic data using coarse scale models in manual and assisted approaches. We observed that the misfit surfaces are different when working in the various seismic domains considered. Use of equivalent domains for observed and predicted data was found to give a more unique misfit response and better result.Accurate comparison of predicted and observed 4D seismic data in different domains is necessary for tackling nonuniqueness of the inverse problem and hence reducing the uncertainty of field development predictions.

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History matching by integrating time-lapse seismic with production data can become a more complex process. The additional constraints make it harder to find good models and this is made more difficult due to the nonlinearities encountered when predicting seismic behavior. A key aspect of this is the choice of domain in which to compare seismic data such as time domain or domain of inverted petro-elastic properties. We extend previous work where we examined the misfit surface from various domains by adding quantitative measures of nonlinearity in function of seismic on model parameters and analysing uncertainties in parameter estimates. In this study we apply history matching to the models on the Schiehallion field. We compare the attributes of acoustic impedance derived from coloured inversion products to predicted acoustic impedance from a petro-elastic model. We call this a cross-domain comparison. To perform an alternative same-domain comparison, seismic prediction is based on the 1D convolution method. We then derive predicted pseudo impedance attributes, equivalent to those observed, using ’coloured inversion’. Models obtained in history matching using these two schemes are then examined. Our results show that the outcome of history matching to seismic data is affected by the underlying static model conditioned to baseline 3D seismic in different domains which makes comparison of domains more difficult. It was demonstrated that cross-domain comparison of predicted impedances to observed seismic data increases non-uniqueness of parameter estimates. On the other hand, comparison in the same domain requires more modeling steps which adds to the nonlinearity because of narrowing frequency band. Accurate reconciliation of predicted and observed seismic and production data via history matching is necessary for maximising the forecast capability of a simulation model. This significantly improves decision making by reducing risks and uncertainties in a field development.

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