Abstract

Production history is an important reflection of reservoir properties. One of our major goals in reservoir description is to increase production. If we can integrate production data into the building of the reservoir model, we can build a more realistic model and have greater confidence in our predictions. In addition, when reservoir simulation is performed with such a reservoir model, cycle time for history matching can be reduced.

Production data can be applied in reservoir description in three aspects: as soft data in geostatistical gridding, as constraints in gridding, or in post-processing of the reservoir model. The conventional approach of history matching is in the third aspect, which is indirect and time consuming. Our attempt is in the first two aspects. The key is in calculating an attribute from production data that can be calibrated to reservoir properties such as permeability. One such attribute is productivity index. The most difficult task is to normalize the attribute to compensate for differences in starting time, pressure, saturation, mechanical problems, and so on. After verification with synthetic data, the methodology is applied to producing fields with primary production data. The results are consistent with the geological description of the field and can be used in reservoir description. For fields with many wells and lots of data, when the history matching approach is more costly, this approach can be effectively used to map permeability trends and improve the reservoir description model, providing a better tool for optimization of hydrocarbon production.

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