The Rumaila field is in South East Iraq contains multiple reservoir intervals, including the Upper Cretaceous Mishrif carbonate reservoir, one of the major reservoirs in the world, that has been producing at considerable oil rates for more than 50 years. With billions of barrels yet to be recovered it is expected to play a significant role in sustaining Rumaila production for decades. Reservoir pressure has dropped due to historical production and, therefore, large scale water injection is planned to support and enhance future production rates and oil recovery.
One of the key subsurface challenges in carbonate reservoirs is to understand and characterise reservoir complexity and heterogeneity, with permeability being one of the key factors in understanding sweep behavior and predicting production and injection rates. Rumaila has extensive surveillance programs and production and saturation logs in particular are used to refine static and dynamic models and to better characterise individual well performance. With more than 1,000 well penetrations to date, efficient management of wells is key to optimising production.
It was recognized several years ago that the available log and core datasets at that time did not enable a fully characterised model of the pore system, resulting in a large uncertainty in the permeability model. As a result, four new wells were cored, and advanced modern logs acquired to expand the datasets to support a rebuilding of rock typing and permeability models to better understand pore system distributions and the extent and impact of heterogeneity in the Mishrif reservoir.
This paper presents a workflow that utilises NMR logs, NMR core analysis and FZI techniques to predict permeability. The approach is focussed on distinguishing between different pore types by estimating the relative proportion of large pores (Large
Pores Index - LPI) from NMR data and using this as an input to enhance the prediction of FZI rock types and subsequently the prediction of permeability. The results show a significant improvement in permeability estimates compared to more traditional approaches.
The improvement in permeability prediction has been reflected in better predictions of production and injection indexes, improved understanding of sweep behaviour and the prediction of timing for water breakthrough, leading to more optimal management of reservoir performance. Moreover, at the well level, the new model has resulted in enhanced completion decisions for newly drilled wells, as well as ongoing well-work operations (additional perforation and re-perforation campaigns) on existing producers and injectors.
