Integrating consistent streamline regionalization and multi-local distribution functions into geostatistical history matching: A real case application(Conference Paper)

SEG/AAPG/EAGE/SPE Research and Development Petroleum Conference and Exhibition 2018, RDP 2018

Conference Paper

This paper introduces the application to a real field case of an automatic iterative geostatistical history matching technique, integrating geological and engineering consistency. Current trends in the industry reflect a growing interest towards the development of workflows that simultaneously integrate petrophysical modeling with dynamic calibration of reservoir models to historical production data. Contrary to manual history matching techniques, where model perturbation often disregards geological or physical realism, the proposed history matching approach introduces geological consistency through geostatistical simulation and physical realism by using streamline regionalization while holding the predictive capability of resulting petrophysical models. In the proposed methodology, the reservoir static properties are iteratively updated by stochastic sequential simulation and co-simulation, constrained to production data, while streamline information is used for electing preponderant flow production regions of the model, as the focus for property perturbation. In order to capture the complex subsurface heterogeneities of the reservoir, petrophysical property realizations were obtained using the Direct Sequential Simulation and co-Simulation algorithm, with Multi-local Distribution Functions (Nunes et al, 2017). The location and proportion of reservoir facies is also automatically updated throughout the iterative procedure, using Bayesian Classification. The proposed approach was successfully applied to a real case study, located in NorthEast onshore Brazil, resulting in multiple history matched models that better reproduce historic data. © 2018 Society of Exploration Geophysicists.

Publication

Year of publication: 2018

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DOI: 10.1190/RDP2018-35367099.1

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