Background. The study performed by Rosneft employees shown in this paper demonstrates approach and analytical methods that allows to forecast oil production at the level of minimal infrastructure units. These approaches are used to forecast long-term oil production and predict infrastructure blockage. The approach was partially automated by the authors. This made it possible to testing at giant Krasnoleninskoye oilfield.
Aim. The study was performed in order to develop and test an approaches to forecast oil production of large oil fields with high detail levels.
Materials and methods. Common methods of decline curve analysis and water-into-oil curve analysis were used in this work to analyze the precondition. The main feature of the approach is the analysis of precondition at the level of large well clusters and transfer it to the level of wells. Some of the actions were automated by new proprietary software and were tested at the giant brown field. The software was integrated with the corporate database.
Results. An author’s approach has been developed. The approach allows to forecast oil production at the level of infrastructure units using analytical methods. Oil production of the giant brown field with high detail levels were forecasted using the proposed approaches and developed software.
Conclusions. The results show that the developed approaches and software can be used to forecast mediumand long-term performance of producing oil fields in the conditions of existing external and infrastructural constraints.
Approaches to forecast oil field performance at the well pads level and beta testing on oilfields of RN-Nyaganneftegaz (ROSNEFT)
