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Geostatistical facies simulation with geometric patterns of a petroleum reservoir

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Abstract

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.

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Notes

  1. RedHat Linux 5.5 64-bit running in a HP Z800 workstation with 12 Intel Xeon X5680 3.33 GHz cores; 12.3 MB total CPU cache; 64 GB of RAM.

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Acknowledgments

The authors thank Petrobras S.A. for supporting the development of this work.

Author information

Author notes

  1. Luiz Gustavo Rasera

    Present address: Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, 1015, Switzerland

Authors and Affiliations

  1. Petróleo Brasileiro S.A. – Petrobras, Av. República do Chile, 330, Torre Leste, 13º andar. Centro, Rio de Janeiro, RJ, 20031-170, Brazil

    Paulo Roberto Moura de Carvalho & Luiz Eduardo Seabra Varella

  2. Federeal University of Rio Grande do Sul – UFRGS, Av. Bento Gonçalves, 9500, Bloco IV, Prédio 75, Sala 104. Bairro Agronomia, Porto Alegre, RS, 91501-970, Brazil

    João Felipe Coimbra Leite da Costa & Luiz Gustavo Rasera

Authors
  1. Paulo Roberto Moura de Carvalho
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  2. João Felipe Coimbra Leite da Costa
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  3. Luiz Gustavo Rasera
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  4. Luiz Eduardo Seabra Varella
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Corresponding author

Correspondence to Paulo Roberto Moura de Carvalho.

Appendices

Appendix 1: Python script to categorize values

figure a

Appendix 2: Python script used to convert the secondary data into facies probabilities

figure b

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de Carvalho, P.R.M., da Costa, J.F.C.L., Rasera, L.G. et al. Geostatistical facies simulation with geometric patterns of a petroleum reservoir. Stoch Environ Res Risk Assess 31, 1805–1822 (2017). https://doi.org/10.1007/s00477-016-1243-5

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  • DOI: https://doi.org/10.1007/s00477-016-1243-5

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