Comparing Time-Lapse Seismic and Reservoir Model Predictions in Producing Oil and Gas Fields

Updating of reservoir models by history matching of 4D seismic data along with production data gives us a better understanding of changes to the reservoir, reduces risk in forecasting and leads to better management decisions. This process of seismic history matching requires an accurate representation of predicted and observed data so that they can be compared quantitatively when using automated inversion. Observed seismic data is often obtained as a relative measure of the reservoir state or its change, however. The data, usually attribute maps, need to be calibrated to be compared to predictions. In this paper we describe an alternative approach where we normalize the data by scaling to the model data in regions where predictions are good. To remove measurements of high uncertainty and make normalization more effective, we use a measure of repeatability of the monitor surveys to filter the observed time‐lapse data. We apply this approach to the Nelson field. We normalize the 4D signature based on deriving a least squares regression equation between the observed and synthetic data which consist of attributes representing measured acoustic impedances and predictions from the model. Two regression equations are derived as part of the analysis. For one, the whole 4D signature map of the reservoir is used while in the second, 4D seismic data is used from the vicinity of wells with a good production match. The repeatability of time‐lapse seismic data is assessed using the normalized root mean square of measurements outside of the reservoir. Where normalized root mean square is high, observations and predictions are ignored. Net: gross and permeability are modified to improve the match. The best results are obtained by using the normalized root mean square filtered maps of the 4D signature which better constrain normalization. The misfit of the first six years of history data is reduced by 55 per cent while the forecast of the following three years is reduced by 29 per cent. The well based normalization uses fewer data when repeatability is used as a filter and the result is poorer. The value of seismic data is demonstrated from production matching only where the history and forecast misfit reductions are 45% and 20% respectively while the seismic misfit increases by 5%. In the best case using seismic data, it dropped by 6%. We conclude that normalization with repeatability based filtering is a useful approach in the absence of full calibration and improves the reliability of seismic data.

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Overview of global 4D seismic implementation strategy

Waal

Calvert²

2003

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For many Shell-operated fields around the world, time-lapse reservoir monitoring (4D) is now an integral part of field management and some 25 dedicated 4D surveys were acquired for this purpose by the end of 2002. This widespread application is the result of a focused implementation effort aimed at global deployment to maximize the value extracted from the surveys in terms of saved costs, increased production, increased recovery and improved HSE management, where effective implementation is achieved through a combination of global operatorship and technology capability. Apart from ensuring global deployment, there is the challenge to extend the range of 4D applicability. To achieve this the project has three application portfolios: today's‘ proven’ 4D technology portfolio, which is about monitoring fluid movements in thick clastic oil reservoirs offshore. Results come largely from comparing reservoir simulator output with difference maps derived from repeat 4D streamer surveys; a‘ stretch’ portfolio where the technology is applied to gas reservoirs, land data, stacked reservoirs, carbonate fields and to the monitoring of pressure changes; a‘ tomorrow's technology’ portfolio, which has the potential to increase the application base even further. The new technologies are about the use of permanent arrays, downhole acquisition, passive listening and ‘smart fields’ where semi-continuous 4D monitoring provides eyes and ears between the wells. More and more value is realized as 4D becomes fully integrated with subsurface work flows and modelling tools. Benefits from 4D technology for individual fields can be in the tens or hundreds of millions of dollars. A large fraction of these come from 4D surprises, illustrating that we tend to underestimate our uncertainties and suggesting different approaches to field management.

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Comparing Time-Lapse Seismic and Reservoir Model Predictions in Producing Oil and Gas Fields

Cited by 14 publications

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Time-lapse seismic

Time-lapse seismic

Improved normalization of time‐lapse seismic data using normalized root mean square repeatability data to improve automatic production and seismic history matching in the Nelson field

Overview of global 4D seismic implementation strategy

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