1887

Abstract

Summary

Computational requirements may be one of the most relevant parameters in model-based decision analysis process of giant and complex reservoirs. This may make probabilistic studies very time consuming. One proposal to work around this problem is to divide the reservoir model into sectors and use them as isolated models (Sector Modeling approach) during the decision analysis processes, assuming that isolated sectors representativeness is acceptable. The study case is a benchmark of giant offshore carbonate reservoir, analogous to pre-salt reservoirs in Brazil, which was divided into four sectors, representing four production regions with separate production systems (platforms), each one starting in different periods.

A probabilistic study is performed to evaluate if the behavior of the combination of the Isolated Sectors models (ΣSisolated) is representative of Full Field models (FF). It is also compared the behavior of Sector 1 using its Isolated Sector models (S1) and FF models. This study considers the use of 100 geological scenarios of the UNISIM-III model, combined with scalar uncertainties (relative permeability curves, faults transmissibility, PVT, well productivity/injectivity).

In this paper, it is proposed a methodology to evaluate differences between the two sets of models. Results show good correlation between the behavior of Sector 1 in S1 and FF models. ΣSisolated models are representative of the overall behavior of the FF models, presenting great correlations between both model sets. However, it is a bias indication conservative scenarios since cumulative oil production and Net Present Value (NPV) are lower, compared to the FF models. The average NPV relative difference is 13%, and thirteen models present considerable relative differences between the two sets of models (higher than 20%). A deeper study is performed using the models where highest and lowest NPV relative differences are observer to identify the main reasons of those differences. Also, it is evaluated if the behavior of the ΣSisolated models are representative of the FF models performing risk analysis quantification and selection of representative models.

To apply the Sector Modeling approach in the study case, it is necessary to consider that there is a considerable computational gain when using the Isolated Sector models, but there are models with considerable relative differences. Thus, if one chooses to adopt this methodology in the decision-making process, isolated sector models can be used during optimization processes that require a high number of simulations. Moreover, the decision making should be based on the results observed for the FF models.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202035102
2020-09-14
2024-04-24
Loading full text...

Full text loading...

References

  1. BOTECHIA, V. E., CORREIA, M. G., SCHIOZER, D. J.
    2017. A model-based decision analysis comparing water and polymerflooding inthe development of a heavy oilfiel.Journal of Petroleum Science and Engineering, Vol 157 (917–929). http://dx.doi.org/10.1016/j.petrol.2017.08.014
    [Google Scholar]
  2. DZYUBA, V. I., LITVINENKO, YU.V., BOGACHEV, K.YU., MIGRASIMOV, A.R., SEMENKO, A.E., KHACHATUROVA, E.A., EYDINOV, D.A.
    2012. Application of Sector Modeling Technology for Giant Reservoir Simulations.SPE Russian Oil & Gas Exploration & Production Technical Conference and Exhibition held in Moscow, Russia, SPE-162090-MS. https://doi.org/10.2118/162090-MS
    [Google Scholar]
  3. CHAVES, J. M. P.
    2018. Multiscale Approach to Construct a Carbonate Reservoir Model with Karstic Features and Brazilian Pre-Salt Trends using Numerical Simulation, Dissertation presented to the Mechanical Engineering Faculty and Geosciences Institute of the University of Campinas in partial fulfillment of requirements for the degree of Master in Petroleum Sciences and Engineering in the area of Reservoirs and management, University of Campinas.
    [Google Scholar]
  4. CORREIA, M. G., BOTECHIA, V. E., PIRES, L. C. O., RIOS2, V. S., SANTOS, S. M. G., RIOS, V.S., HOHENDORFF FILHO, J. C. V., PLATA CHAVES, J. M., SCHIOZER, D. J.
    “UNISIM-III: Benchmark Case Proposal Based on a Fractured Karst Reservoir”, ECMOR XVII, 14–17 Setembro, Edimburgo, Reino Unido, 2020
    [Google Scholar]
  5. FLORIS, F.
    1996. Direct Conditioning of Gaussian Random Fields to Dynamic Production Data. 5th Eur. Conf. Math. Oil Recover.
    [Google Scholar]
  6. MEIRA, L.A.A., COELHO, G.P., SANTOS, A.A.S., SCHIOZER, D.J.
    2016. Selection of representative models for decision analysis under uncertainty.Computational. Geoscience88 (67–82).
    [Google Scholar]
  7. MEIRA, L.A.A., COELHO, G.P., SILVA, C. G., SCHIOZER, D.J., SANTOS, A.S.
    2017. RMFinder 2.0 - An Improved Interactive Multi-Criteria Scenario Reduction Methodology.SPE Latin America and Caribbean Petroleum Engineering Conference, 17–19 May, Buenos Aires, Argentina, SPE185502. https://doi.org/10.2118/185502-MS
    [Google Scholar]
  8. MEIRA, L. A. A., COELHO, G. P., SILVA, C. G., ABREU, J. L. A., SANTOS, A. A. S., SCHIOZER, D. J.
    “Improving Representativeness in a Scenario Reduction Process to aid Decision Making in Petroleum Fields”, Journal of Petroleum Science and Engineering, v. 184, pp. 1–19, Janeiro, 2020.
    [Google Scholar]
  9. PIRES, L. O., BOTECHIA, V. E., SCHIOZER, D.
    Feasibility of Sector Modeling Approach in a Giant Petroleum Field.SPE Europec featured at 82nd EAGE Conference and Exhibition to be held 8–11 June2020 in Amsterdam, the Netherlands, SPE-200628-MS.
    [Google Scholar]
  10. SCHIOZER, D.J., SANTOS, A.A.S., SANTOS, S.M.G., HOHENDORFF FILHO, J. C. V.
    2019. Model-based decision analysis applied to petroleum field development and management.Oil & Gas Science and Technology - Rev. IFP Energies nouvelles74, 4.
    [Google Scholar]
  11. THIELE, M. R.
    2005. Streamline Simulation.8th International Forum on Reservoir Simulation, Stresa/Lago Maggiore, Italy
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202035102
Loading
/content/papers/10.3997/2214-4609.202035102
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error