Vita

EDUCATION

• PhD Petroleum Engineering - The University of Tulsa, Aug. 2008 to Feb. 2012.

• Petrobras’ training course: Petroelum Engineering - Universidade Petrobras, Jan. 2003 to Feb. 2004.

• M.Sc. Structures - Universidade de Brasília. Aug. 2000 to Mar. 2002.

• B.S. Civil Engineering - Universidade de Brasília, July 1995 to Aug. 2000

BOOKS & CHAPTERS

• Book chapter: "Aplicações de Pesquisa Operacional na Indústria Internacional de Petróleo" (in Portuguese), Chapter 4, Elsevier, 2015.

• Book chapters: "Intelligent Systems in Oil Field Development under Uncertainty", Chapters 1, 3 and 6, Springer Berlin/Heidelberg, 2009.

• Book: "Projeto e Execução de Lajes Protendidas" (in Portuguese), Editora Interciência, 2005.

HONORS

• Outstanding Service as SPE Journal Technical Editor in 2014.

• Outstanding Service as SPE Journal Technical Editor in 2013.

• Member of Phi Kappa Phi National Honor Society, 2010.

• Award of best student of civil engineering July 2000, Universidade de Brasília.

PROFESSIONAL EXPERIENCE

• Senior Advisor - Petrobras Research and Development Center - CENPES, Rio de Janeiro (Brazil). 2023 - present. 

• Techincal Advisor - Petrobras Research and Development Center - CENPES, Rio de Janeiro (Brazil). 2017 - 2023. 

• Petroleum Engineer - Petrobras Research and Development Center - CENPES, Rio de Janeiro (Brazil). 2003 - 2017.

• Professor at Universidade Gama Filho, Rio de Janeiro (Brazil). 2006 - 2008.

• Civil Engineer - Company: Impacto Protensão, (Construction supervision and quality control of prestressed concrete slabs, 14 builds), Brasilia (Brazil). 2002. 

• Professor at Faculdade de Ciências Sociais e Tecnológicas - FACITEC, Brasília (Brazil). 2002.

• Professor at União Educacional do Planalto Central - UNIPLAC, Brasília (Brazil). 2002.

• Civil Enginner - Company: MCM Engenharia,  Design of structures. Brasilia (Brazil). 2000 - 2002.

AREAS OF INTEREST

• Data assimilation

• Reservoir simulation.

• Reservoir characterization and history matching.

• Ensemble Kalman Filter (EnKF) and ensemble smoother (ES).

• 4D seismic (time-lapse seismic).

• Uncertainty quantification.

• Optimization.

• Machine learning.

PUBLICATIONS

PhD Dissertation

• History Matching and Uncertainty Characterization Using Ensemble-based Methods - The University of Tulsa, 2012. Download

Peer Reviewed

1. Exterkoetter, R.; Figueiredo, L.P.; Bordignon, F.L.; Emerick, A.A.; Roisenberg, M. and Rodrigues, B.R.: Ensemble smoother with fully convolutional VAE for seismic facies inversion, Computers & Geosciences, 2024 DOI: 10.1016/j.cageo.2024.105619

2. Emerick, A.A. and Neto, G.M.S.: Projection of 4D seismic onto the ensemble observation subspace for data assimilation, Geoenergy Science and Engineering, 2024, DOI: 10.1016/j.geoen.2024.212835

3. Exterkoetter, R.; Dutra, G.R.; Figueiredo, L.P.; Bordignon, F.; Neto, G.M.S.; Emerick, A.A.: Feature Extraction in Time-Lapse Seismic Using Deep Learning for Data Assimilation, SPE Journal, 2023 DOI: 10.2118/212196-PA   

4. Emerick, A.A. and Neto, G.M.S.: Investigation on the production data frequency for assimilation with ensemble smoother, Geoenergy Science and Engineering, 2023, DOI: 10.1016/j.geoen.2023.212356

5. Leeuwenburgh, O.; Emerick, A.A.; Jafarpour, B.; Zhang, D. and Luo, X.: Data Science Applications to Inverse and Optimization Problems in Earth Science, Frontiers in Applied Mathematics and Statistics, 2021, DOI: 10.3389/fams.2021.756949 

6. Lacerda, J.M; Emerick, A.A. & Pires, A.P.: Using a machine learning proxy for localization in ensemble data assimilation, Computational Geosciences, 2021, DOI: 10.1007/s10596-020-10031-0

7. Canchumuni, S.W.A.; Castro, J.D.B.; Potratz, J.; Emerick, A.A. & Pacheco, M.A.C.: Recent developments combining ensemble smoother and deep generative networks for facies history matching, Computational Geosciences Vol. 25, 2021, DOI: 10.1007/s10596-020-10015-0

8. Fonseca, R.M.; Della Rossa, E.; Emerick, A.A.; Hanea, R.G & Jansen, J.D.: Introduction to the special issue: Overview of OLYMPUS Optimization Benchmark Challenge, Computational Geosciences, Vol. 24, 2020, DOI: 10.1007/s10596-020-10003-4

9. Lima, M.M., Emerick, A.A., Ortiz, C.E.P., Data-Space Inversion with Ensemble Smoother, Computational Geosciences, 2020. DOI: 10.1007/s10596-020-09933-w  

10. Emerick, A.A., Analysis of Geometric Selection of the Data-Error Covariance Inflation for ES-MDA, Journal of Petroleum Science and Engineering, Vol. 182, 2019. DOI: 10.1016/j.petrol.2019.06.032 

11. Canchumuni, S.A.; Emerick, A.A. and Pacheco, M.A.C., Towards a Robust Parameterization for Conditioning Facies Models using Deep Variational Autoencoders and Ensemble Smoother, Computers & Geosciences, Vol. 128, 87-102, 2019. DOI: 10.1016/j.cageo.2019.04.006 

12. Canchumuni, S.A.; Emerick, A.A. and Pacheco, M.A.C., History Matching Geological Facies Models Based on Ensemble Smoother and Deep Generative Models, Journal of Petroleum Science and Engineering, Vol. 177, 941-958, 2019. DOI: 10.1016/j.petrol.2019.02.037

13. Lacerda, J.M.; Emerick, A.A. and Pires, A.P., Methods to Mitigate Loss of Variance Due to Sampling Errors in Ensemble Data Assimilation with Non-local Model Parameters, Journal of Petroleum Science and Engineering, Vol. 172, 690-706, 2019. DOI: 10.1016/j.petrol.2018.08.056

14. Emerick, A.A., Deterministic Ensemble Smoother with Multiple Data Assimilation as an Alternative for History Matching Seismic Data, Computational Geosciences, Vol. 22(5), 1175-1186, 2018. DOI: 10.1007/s10596-018-9745-5

15. Abreu, A.C.A.; Booth, R.; Prange, M.; Bailey, W.J.; Bertolini, A.; Teixeira, G.; Romeu, R.; Emerick, A.A.; Pacheco, M.A.C. and Wilkinson, D., A Decision Support Approach to Value Flexibility Considering Uncertainty and Future Information, Journal of Petroleum Science and Engineering, Vol. 167, 88-99, 2018. DOI: 10.1016/j.petrol.2018.03.077

16. Silva, V.L.S.; Emerick, A.A.; Couto, P. and Alves, J.L.D., History Matching and Production Optimization Under Uncertainties -- Application of Closed-loop Reservoir Management, Journal of Petroleum Science and Engineering, 2017, Vol. 157, 860-874, 2017, DOI: 10.1016/j.petrol.2017.07.037

17. Camacho, A.; Talavera, A.; Emerick, A.A.; Pacheco, M.A.C. and Zannia, J., Uncertainty Quantification in Reservoir Simulation Models with Polynomial Chaos Expansions: Smolyak Quadrature and Regression Method Approach, Journal of Petroleum Science and Engineering, Vol. 153, 203-211, 2016. DOI: 10.1016/j.petrol.2017.03.046

18. Emerick, A.A., Investigation on Principal Component Analysis Parameterizations for History Matching Channelized Facies Models with Ensemble-Based Data Assimilation, Mathematical Geosciences, Vol. 49, Issue 1, 85-120, 2017. DOI: 10.1007/s11004-016-9659-5

19. Emerick, A.A., Estimating uncertainty bounds in field production using ensemble-based methods, Journal of Petroleum Science and Engineering, Vol. 145, 648-656, 2016. DOI: 10.1016/j.petrol.2016.06.037

20. Le, D.H, Emerick, A.A. and Reynolds, A.C., An Adaptive Ensemble Smoother with Multiple Data Assimilation for Assisted History Matching, SPE Journal, Vol. 21, Issue 6, 2195-2207, 2016. DOI: 10.2118/173214-PA

21. Shirangi, M.G and Emerick, A.A., An Improved TSVD-based Levenberg-Marquardt Algorithm for History Matching and Comparison with Gauss-Newton - Journal of Petroleum Science and Engineering, Vol. 143, 259-271, 2016. DOI: 10.1016/j.petrol.2016.02.026

22. Emerick, A.A., Analysis of the Performance of Ensemble-based Assimilation of Production and Seismic Data, Journal of Petroleum Science and Engineering, Vol. 136, 219-239 2016. DOI: 10.1016/j.petrol.2016.01.029

23. Emerick, A.A., Towards a Hierarchical Parametrization to Address Prior Uncertainty in Ensemble-based Data Assimilation, Computational Geosciences, Vol. 20, Issue 1, 35-47, 2016. DOI: 10.1007/s10596-015-9545-0

24. Emerick, A.A., Estimation of Pressure and Saturation Fields from Time-Lapse Impedance Data Using the Ensemble Smoother , Journal of Geophysics and Engineering, Vol. 11, 2014. DOI: 10.1088/1742-2132/11/3/035007

25. Emerick, A.A. and Reynolds, A.C., Investigation on the Sampling Performance of Ensemble-based Methods with a Simple Reservoir Model, Computational Geosciences, Vol. 17, Issue 2, 325-350, 2013. DOI: 10.1007/s10596-012-9333-z

26. Emerick, A.A. and Reynolds, A.C., Ensemble Smoother with Multiple Data Assimilation, Computers & Geosciences, Vol. 55, 1-15, 2013. DOI: 10.1016/j.cageo.2012.03.011.

27. Emerick, A.A. and Reynolds, A.C., History Matching Time-lapse Seismic Data Using the Ensemble Kalman Filter with Multiple Data Assimilations, Computational Geosciences, Vol. 16, Number 3, 2012. DOI: 10.1007/s10596-012-9275-5

28. Emerick, A.A. and Reynolds, A.C., Combining the Ensemble Kalman Filter with Markov-Chain Monte Carlo for Improved History Matching and Uncertainty Characterization, SPE Journal, Vol. 17, Issue 2, 418-440, 2012. DOI: 10.2118/141336-PA

29. Emerick, A.A. and Reynolds, A.C., History Matching a Field Case Using the Ensemble Kalman Filter with Covariance Localization, SPE Reservoir Evaluation & Engineering-Reservoir Engineering, Vol. 14, Number 4, 2011. DOI: 10.2118/141216-PA

30. Emerick, A.A. and Reynolds, A.C., Combining Sensitivities and Prior Information for Covariance Localization in the Ensemble Kalman Filter for Petroleum Reservoir Applications, Computational Geosciences, Vol. 15, Number 2, 251-269, 2011. DOI: 10.1007/s10596-010-9198-y

Conference Proceedings

1. Piccinini, R.B.; Kubota, L.K.; Galvão, M.R. and Emerick, A.A.: Application of an Ensemble Based Method for Pressure-Rate Deconvolution,  SPE-220707-MS, SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, USA, September, 2024.. DOI:10.2118/220707-MS

2. Emerick, A.A.: Practical Considerations in the Application of Ensemble Smoother for Assimilating Production and 4D Seismic Data, ECMOR, 2024. DOI: 10.3997/2214-4609.202437027

3. Ribeiro, P.M..; Gildin, E. and Emerick, A.A.: Assessing the Value of in-Well Fiber Optics Deployment in Pre-Salt Projects for Real-Time Reservoir Monitoring, SPE-214863-MS, SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 2023, DOI: 10.2118/214863-MS 

4. Exterkoetter, R.; Dutra, G.R.; Figueiredo, L.P.; Bordignon, F.L.; Emerick, A.A.; Neto, G.M.S. Roisenberg, M.:  Deep Feature Extraction for Data Assimilation with Ensemble Smoother ,  2023 International Joint Conference on Neural Networks (IJCNN), DOI: 10.1109/IJCNN54540.2023.10191130

5. Exterkoetter, R.; Dutra, G.R.; Figueiredo, L.P.; Bordignon, F.; Emerick, A.A.; Neto, G.M.S.: Feature Extraction in Time-Lapse Seismic Using Deep Learning for Data Assimilation, SPE-212196-MS, SPE Reservoir Simulation Conference, Galveston, Texas, USA, March 2023, DOI: 10.2118/212196-MS   

6. Santos, E.S.B.; Felipe, V.E.S.; Casagrande, j.; Del Rey, A.C.  Emerick, A.A.: Kalman Filter, An Automation Tool Used for Integration of Dynamic and Static Data Model, Campos Basin Example, Brazil,  Fourth HGS/EAGE Conference on Latin America, 2022, DOI: 10.3997/2214-4609.202282009

7. Potratz, J; Canchumuni, S.W.A.; Castro, J.D.B; Emerick, A.A.; Pacheco, M.A.C.: Large Dimension Parameterization with Convolutional Variational Autoencoder: An Application in the History Matching of Channelized Geological Facies Models, 20th International Conference on Computational Science and Its Applications (ICCSA), 2020, DOI: 10.1109/ICCSA50381.2020.00016 

8. Moyen, R.; Peiro, M.; Gentilhomme, T. & Emerick, A.A.: Petrophysical Inversion Using Adaptive Ensemble-Based Optimization Method,  81st EAGE Conference and Exhibition 2019, DOI: 10.3997/2214-4609.201900795

9. Canchumuni, S.A.; Emerick, A.A. and Pacheco, M.A., History Matching Channelized Facies Models using Ensemble Smoother with a Deep Learning Parameterization, Proceedings of the 16th European Conference on the Mathematics of Oil Recovery (ECMOR XVI), Barcelona,Spain, 3--6 September, 2018. DOI 10.3997/2214-4609.201802277

10. Lima, A.; Gentilhomme, T.; Riffault, D.; Allo, F.; Anyzewski, A.S.; Emerick, A.A. and Santos, M.S., Multi-Scale Ensemble-Based Data Assimilation for Reservoir Characterization and Production Forecast: Application to a Real Field - OTC-28002-MS, Proceedings of the Offshore Technology Conference, Rio de Janeiro, Brazil, 24-26 October, 2017

11. Hidalgo, D.M.; Emerick, A.A.; Couto, P. and Alves, J. L. D., Closed-Loop Field Development Under Geological Uncertainties: Application in a Brazilian Benchmark Case - OTC-28089-MS, Proceedings of the Offshore Technology Conference, Rio de Janeiro, Brazil, 24-26 October, 2017

12. Canchumuni, S.A.; Emerick, A.A. and Pacheco, M.A., Integration of Ensemble Data Assimilation and Deep Learning for History Matching Facies Models - OTC-28015-MS, Proceedings of the Offshore Technology Conference, Rio de Janeiro, Brazil, 24--26 October, 2017

13. Emerick, A.A., Estimating Uncertainty Bounds in Model-Based Production Forecasts Using Ensemble Data Assimilation  - IBP 1976_16, Rio Oil & Gas Expo and Conference 24-27 October 2016, Rio de Janeiro, Brazil.

14. Abreu, A.C.A; Booth, R.; Bertolini, A.; Prange, M.; Bailey, W.J., Teixeira, G.; Romeu, R.K.; Emerick, A.A. and Pacheco, M.A.C., Proactive and Reactive Strategies for Optimal Operational Design: An Application in Smart Wells - OTC 26209 - Offshore Technology Conference Brasil held in Rio de Janeiro, Brazil, 27-29 October 2015.

15. Le, D.H, Emerick, A.A. and Reynolds, A.C., An Adaptive Ensemble Smoother with Multiple Data Assimilation for Assisted History Matching - SPE 173214 - SPE Reservoir Simulation Symposium, Houston, Texas, 23-25 February 2015.

16. Reynolds, A.C.; Le, D.H and Emerick, A.A., Ensemble-Based Methods for Data Integration and Uncertainty Quantification, Integrated Modeling Workshop, Dubai, 2014

17. Abreu, A.C.A; Booth, R.; Bertolini, A.; Prange, M.; Bailey, W.J., Teixeira, G.; Romeu, R.K.; Emerick, A.A. and Pacheco, M.A.C., Maximizing the Value of Operational Flexibility: An Application to Smart Wells - IBP 1258_14, Rio Oil & Gas Expo and Conference 15-18 September 2014, Rio de Janeiro, Brazil.

18. Emerick, A.A. and Reynolds, A.C., History Matching Production and Seismic Data in a Field Case Using Ensemble-based Methods - SPE 163675 - SPE Reservoir Simulation Symposium, The Woodlands, Texas, 18-20 February 2013.

19. Emerick, A.A. and Reynolds, A.C., Combining the Ensemble Kalman Filter with Markov Chain Monte Carlo for Improved History Matching and Uncertainty Characterization - SPE 141336 - SPE Reservoir Simulation Symposium, The Woodlands, Texas, 21-23 February 2011.

20. Emerick, A.A. and Reynolds, A.C., History Matching a Field Case Using the Ensemble Kalman Filter with Covariance Localization - SPE 141216 - SPE Reservoir Simulation Symposium, The Woodlands, Texas, 21-23 February 2011.

21. Brito, D.U; Moraes, R.J. and Emerick, A.A., The Marlim Field: Incorporating Time-Lapse Seismic in the Assisted History Matching - SPE 137763, SPE Latin American and Caribbean Petroleum Engineering Conference, Lima, Peru, 1 - 3 December 2010.

22. Coutinho, E.J.R.; Emerick, A.A.; Li, G. and Reynolds, A.C., Conditioning Multilayered Geologic Models to Well-Test and Production-Logging Data Using the Ensemble Kalman Filter - SPE 134542, SPE Annual Technical Conference and Exhibition, Florence, Italy, 19-22 September 2010.

23. Emerick, A.A. and Reynolds, A.C., EnKF-MCMC - SPE 131375, SPE EUROPEC/EAGE Annual Conference and Exhibition, Barcelona, Spain, 14-17 June 2010.

24. Emerick, A.A.; Silva, E.; Messer, B.; Almeida, L.F; Szwarcman, D.; Pacheco, M.A. and Vellasco, Marley M.B.R.: Well Placement Optimization Using a Genetic Algorithm with Nonlinear Constraints - SPE 118808, 2009 SPE Reservoir Simulation Symposium Texas, USA, 2-4 February 2009.

25. Emerick, A.A.; Moraes, R.J. and Rodrigues, J.R.P., History Matching 4D Seismic Data with Efficient Gradient Based Methods - SPE 107179, SPE EUROPEC, London, UK, 11 - 14 June 2007.

26. Emerick, A.A. and Portella, R.C.M., Production Optimization with Intelligent Wells - SPE 107261, SPE Latin American and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina, 15 - 18 April 2007.

27. Emerick, A.A.; Moraes, R.J. and Rodrigues, J.R.P., Calculating Seismic Attributes Within a Reservoir Flow Simulator - SPE 107001, SPE Latin American and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina, 15 - 18 April 2007.

28. Silva, L.C.F.; Portella, R.C.M.; Emerick, A.A. and Ebecken, N.F., Predictive Data-Mining Technologies for Oil-Production Prediction in Petroleum Reservoir - SPE 107371, SPE Latin American and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina, 15 - 18 April 2007.

29. Portella, R.C.M. and Emerick, A.A., Use of Quantitative 4D-Seismic Data in Automatic History Match - SPE 94650, SPE Latin American and Caribbean Petroleum Engineering Conference, Rio de Janeiro, Brazil, 20 - 23 Junho 2005.

CONFERENCE AND INVITED PRESENTATIONS

1. Feature Extraction in Time-Lapse Seismic Using Deep Learning for Data Assimilation, SPE Reservoir Simulation Conference, Galveston, Texas, USA, March 2023

2. Combining Deep Learning and Ensemble Smoother for Data Assimilation in Models of Geological Facies, 3rd BR InterPore Conference on Porous Media, Petrópolis, Brazil, August 6, 2019.

3. Recent Ensemble Smoother Applications: Data-Space Inversion and Deep Learning for Facies Models, 14th International EnKF Workshop, Norway, June 2019.

4. History Matching Channelized Facies Models using Ensemble Smoother with a Deep Learning Parameterization, ECMOR XVI, 5 September, 2018, Barcelona, Spain.

5. Uncertainty Quantification with Ensemble Data Assimilation, Mini-Simpósio Modelagem em Quantificação de Incertezas, 9 February, 2017, LNCC, Petrópolis, Brazil.

6. Estimating Uncertainty Bounds in Model-Based Production Forecasts Using Ensemble Data Assimilation, Rio Oil & Gas Expo and Conference October 25 2016, Rio de Janeiro, Brazil.

7. Assimilation of Production and Seismic Data Using ES-MDA. 10th EnKF International Workshop. June 9, 2015.

8. Ensemble Smoother with Multiple Data Assimilation. 7th EnKF International Workshop, June 20, 2012.

9. History Matching Seismic and Production Data Using EnKF and ES-MDA, a Field Case. TUPREP Advisory Board Meeting, University of Tulsa. May 4, 2012.

10. Assessment of Data Assimilation Procedures in Terms of their Ability to Correctly Characterize Uncertainty. TUPREP Advisory Board Meeting, University of Tulsa. May 4, 2012.

11. Ensemble Smoother with Multiple Data Assimilation for Improved History Matching. TUPREP Advisory Board Meeting, University of Tulsa. May 4, 2012.

12. History Matching Marlim Field Using the Ensemble Kalman Filter. SPE-ATW – Use of 4D Seismic and Production Data for History Matching and Optimisation – Application to Norne (Norway), Trondheim, Norway, June 15, 2011.

13. Adaptation of the Ensemble Kalman Filter for History Match Field Data. TUPREP Advisory Board Meeting, University of Tulsa. May 9, 2011.

14. An Algorithm for Combining the Ensemble Kalman Filter and Markov Chain Monte Carlo for Improving Data Match, Sampling and Future Performance Predictions. TUPREP Advisory Board Meeting, University of Tulsa. May 9, 2011.

15. A Linear Parametrization based on an Ensemble of Unconditional Realizations for History Matching and Uncertainty Characterization using RML. TUPREP Advisory Board Meeting, University of Tulsa. May 9, 2011.

16. Combining the Ensemble Kalman Filter with Markov Chain Monte Carlo for Improved History Matching and Uncertainty Characterization - SPE 141336. SPE Reservoir Simulation Symposium, The Woodlands, Texas, 21-23 February 2011.

17. History Matching a Field Case Using the Ensemble Kalman Filter with Covariance Localization - SPE 141216. SPE Reservoir Simulation Symposium, The Woodlands, Texas, 21-23 February 2011.

18. 4D Seismic Interpretation on a Heavy-oil Offshore Reservoir in Brazil. Statoil Research Summit, Statoil Reseach Centre, Trondheim, Norway. Sep. 27, 2010.

19. Evaluation of Techniques to Reduce Loss of Variance Due to Sampling Errors in the Ensemble Kalman Filter. TUPREP Advisory Board Meeting, University of Tulsa. May 7, 2010.

20. Using Ensemble Square Root Filter with Markov Chain Monte Carlo for Sampling. TUPREP Advisory Board Meeting, University of Tulsa. May 7, 2010

21. Combining Sensitivities and Prior Information for Covariance Localization. TUPREP Advisory Board Meeting, University of Tulsa. May 7, 2010

22. Combining Sensitivities and Prior Information for Covariance Localization. EnKF Joint Workshop, Tulsa. Oct.30, 2009

23. In Search of Optimal Covariance Localization. TUPREP Advisory Board Meeting, University of Tulsa. May 8, 2009

24. Well Placement Optimization Using a Genetic Algorithm with Nonlinear Constraints. TUPREP Advisory Board Meeting, University of Tulsa. May 8, 2009

25. History Matching and 4D Seismic. Uncertainty Analysis and Optimization Workshop, Calgary. Feb. 26, 2008

26. Well placement optimization using Genetic Algorithms. Uncertainty Analysis and Optimization Workshop, Calgary. Feb. 26, 2008

27. History Matching 4D Seismic Data with Efficient Gradient Based Methods - SPE 107179. SPE EUROPEC, London. June 12. 2007

28. Production Optimization with Intelligent Wells - SPE 107261. SPE Latin American and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina. Apr. 16, 2007

29. Calculating Seismic Attributes Within a Reservoir Flow Simulator - SPE 107001. SPE Latin American and Caribbean Petroleum Engineering Conference, Buenos Aires, Argentina. Apr. 16, 2007

30. History Matching Using Time-lapse Seismic - Evaluation of the Softwares SimOpt/Huts. Petrobras/Statoil 4D Seismic Meeting - Macae, Brazil. Jan. 12, 2005.

OTHER PROFESSIONAL ACTIVITIES

• Member of the Editorial Committee of JPT (Journal of Petroleum Technology) - Feature: History Matching and Forecasting (2013 - 2022).

• Occasional reviewer for Computational Geosciences, Computer & Geosciences, SPE Journal, SPE Reservoir Evaluation & Engineering, Energy Exploration & Exploitation.

UNDERGRADUATE COURSES TAUGHT (in Portuguese)

• Universidade Gama Filho, Rio de Janeiro (Brazil). Civil, Mechanical and Petroleum Engineering. Feb/2006 - Jun/2008.  Courses: Solid Mechanics, Multiphase Flow in Pipes

• União Educacional do Planalto Central - UNIPLAC, Brasília (Brazil). Information Systems. Feb/2002 - Dec/2002. Courses: Introduction to Computer Sciences, Sorting and Searching Algorthms, Probability and Statistics.

• Faculdade de Ciências Sociais e Tecnológicas - FACITEC, Brasília (Brazil). Information Systems. Aug/2002 - Dec/2002. Courses: Logics and Boole’s algebra.

REFERENCE LINKS

• Google Scholar

• ResearchGate

• Academia.edu

• ORCID