Applied Optimal Reservoir Management: A Field Case Experience in Campos Basin
- Diego Felipe Barbosa de Oliveira (Petrobras S.A.) | Diogo Ferreira Alves Pereira (Petrobras S.A.) | Gustavo Echenique Silveira (Petrobras S.A.) | Pedro Andrade Lima Sá de Melo (Petrobras S.A.)
- Document ID
- Offshore Technology Conference
- Offshore Technology Conference, 6-9 May, Houston, Texas
- Publication Date
- Document Type
- Conference Paper
- 2019. Offshore Technology Conference
- 0.2.2 Geomechanics, 1.7.5 Well Control, 1.6 Drilling Operations, 3 Production and Well Operations, 7.2.1 Risk, Uncertainty and Risk Assessment, 1.7 Pressure Management, 5.5.5 Evaluation of uncertainties, 5.4 Improved and Enhanced Recovery, 5 Reservoir Desciption & Dynamics, 7 Management and Information, 0.2 Wellbore Design, 7.2 Risk Management and Decision-Making, 5.5 Reservoir Simulation
- Optimal well control, Decision under uncertainty, Field Pilot, Reservoir management
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Reservoir management in offshore fields is a challenging task, particularly for mature fields because of a typical excessive production of water and/or gas. Due to several constraints on facilities capacity, assisted reservoir management process can deliver solutions to operate properly offshore fields, seeking for increasing oil production with better assessment of water and gas production and injection. Optimal Reservoir Management (ORM) can be applied aiming to maximize reservoir performance and to deliver well controls applicable to field operations. In this work, we implemented an assisted optimization procedure to maximize overall oil production for a field offshore Brazil in Campos Basin.
We applied our ORM technique in an important field offshore Brazil, where cumulative oil production is maximized by optimally controlling water rates through injecting wells. Injection rates can vary in time, honoring operational requirements of smoothness. Geomechanical limits on injection pressures are considered to avoid loss of rock integrity and platform constraints on overall production and injection are imposed all times. Our approach deals with reservoir uncertainties described within a large set of calibrated simulation models to decide on optimal injection rates, taking into account possible risks.
The model-based ORM under uncertainty that we developed has shown gains in total oil production over 20 years of operation up to 7.2% with respect to the base strategy currently applied. On average, results show an increase around 4% in oil production, with concomitant reduction in total water production and in the overall water injection.
A pilot test in the actual field has been implemented to verify the consistency between modeling and reality (data observation), in order to guarantee that the gains forecasted by our study are feasible. We have chosen an area in the field to proceed an optimal injection control pilot, aiming to check the quality of the uncertain models in comparison with the observed data in practice. The pilot area has been selected based on aspects related with geological description, connectivity expected in the reservoir and operational constraints. The results of 8 months of pilot show clear coherence between models and reality within the uncertainty range expected to the reservoir of interest.
To the best of our knowledge, it is the first time that an offshore field is actually operated based on a set of controls obtained by an assisted optimal reservoir management procedure, although it was performed still in a pilot scale. Results suggest robust benefits under reservoir uncertainties consideration and large-scale application shall take place soon, but it is out of the scope of this work. The pilot provided more confidence on field applications, leading to broader perspective for full-field implementations.
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