This paper presents a real field study, based on experimental design methodology, to manage and quantify the reservoir uncertainties during production forecasting, taking into account all the available dynamic data.
The oil field (named PBR), which is located in the Campos basin (offshore Brazil), consists of a complex lithology, including mainly turbiditic sandstones interbedded by shales and marls. The data set includes about 40 wells and 15 years of production history with water injection scheme. The workflow of the PBR reservoir modeling from the geostatistical lithofacies model, built using the non-stationary truncated Gaussian method, to the flow model has been implemented in a fully integrated chain.
Based on the traditional experimental design methodology, the joint modeling method allows to model the production recovery as a function of both deterministic uncertain parameters, such as petrophysical and production parameters, as well as stochastic parameters such as geostatistical realizations and equiprobable matched models. In this approach, the dispersion due to the non-continuous uncertainties is modeled in a rigorous statistical framework through the variance of the production recovery.
The joint modeling method was applied for the following scenarios: - The PBR field is an appraisal case therefore without production history, - The PBR field has its 15 years of production history. In that case the starting point of the method consists in several equiprobable matched models, obtained by automatic history match process.
Results show that this innovative methodology can successfully be applied on complex real cases to quantify the risk associated with the main reservoir uncertainties, either deterministic or stochastic, during production forecasts. Moreover the uncertainty reduction in production forecasts while taking into account the production history was also quantified.