1. Brazil-Norway R&D workshop Agustinho Plucenio Laboratory for Smart Fields Automation Department of Automation and Systems Engineering Federal University of Santa Catarina Rio de Janeiro, May 26, 2011

2.  Who we are  PRH-ANP Program – PRH34  Research Projects  LACI  INPetro  Ongoing R&D Project  NTNU Cooperation DAS-UFSC R&D Efforts for the oil industry

4. The Federal University of Santa Catarina Located in Florianopolis (pop. 600,000) 25,000 undergraduates 3,500 graduates ≃ 2,000 faculty members

5. Department of Automation and Systems Engineering http://www.das.ufsc.br/das/index.php  24 faculty members  360 undergraduates (1st of its kind in Brazil)  40 M.Eng. students  50 Ph.D. students

6.  Control theory and applications  Linear and nonlinear control  Discrete event systems  Predictive control  Robotics  Industrial informatics  Real-time embedded systems  Industrial networks  General computing  Fault tolerance  Secure network systems  Algorithms  Optimization

7. Program PRH- ANP34 20012006 20092010 1 R&D Project with Petrobras- CENPES Construction Distilation column Multiphase Flow Lab Construction (CNPQ) 2004 2 R&D Project with Petrobras-CENPES 3 R&D Project with Petrobras-CENPES LACI Project with Petrobras-CENPES 2008 NW Control Lab (CNPQ)

8. Program financed by the National Agency of Petroleum, Gas and Bio fuels for Human Resources Development with the theme Automation and Control for the Oil and Gas Industry.

9. Main objective: To complement the education of engineers at the under- graduate and graduate levels in the area of automation, control and instrumentation to work in the petroleum industry. Chem. Eng. C&A Eng. Mech. Eng.

11.  Automation and Control of wells with elevation by gas-lift,  Optimization of gas-lift operations,  Drilling bit wear prediction using neural networks,  Oscillation control using switched systems applied to severe slug control,  Variable Structure Control for the suppression of oscillations in oil well drilling systems,  ARMAX and NARMAX model identification of oil wells operating by gas-lift,  Model Predictive Control for nonlinear systems,  Low cost water fraction meter based on micro-wave,  Multiphase flow meter based on online partial separators,  Development of New Drilling control techniques based on the theory of non-smooth dynamical systems,  Nonlinear Model Predictive Control applied to a water injection development project,  Gas-lift optimization with constraints on transportation and handling facilities of produced fluids,

12.  Development of control algorithms for artificial lift methods (Petrobras-CENPES) (2006-2009)  Multiphase Flow meter for heavy oil phase 1 (CNPQ-CTPetro) (2008-2010)  LACI – Laboratory for the Automation of Intelligent oilfields (Petrobras-CENPES) (2008-2011)  Advanced control systems and production real time optimization (Petrobras-CENPES) (2010-2013)  Intelligent agents for distributed control of complex system (Petrobras-CENPES) (2009-2010)

13. One feature of the project is the utilization of Programmable Logic Computers connected with the well simulators and running the control algorithms (HIL concept). Objective: To develop solutions for the automation of oil wells that optimize production using online surface and down hole measurements.

14. For continuous gas lift:  Use of different WPC models  pwf steady state detection via MPA  Automatic procedure via MPA for model parameter update  Automatic procedure for gas re-allocation due to: gas flow rate availability well model changes well put in forced operation separation capacity constraints  Introduction of control and optimization algorithms in LAPLACE and MPA  Automatic procedures to re-start gas lift wells  Study of a a solution based on NMPC

19. Main Laplace screen Screen for variables configuration

20. During the project 3 approaches were studied for automatically re-starting gas lift wells with:  Classical control algorithms  Switching Control  Fuzzy Logic

21. Control of gas lift wells with NMPC  optimize gas allocation  stabilize GLM pressure  minimizes wellhead flow rate oscillations during gas lift flow rate changes GLM Setup GL Hammerstein dynamic model

22. Sucker rod pump well Developments:  Development of a dynamic simulator  Development of control strategies using down hole pressure measurements  Fault detection techniques using down hole measurements

23. Conventional fluid pound level detection used to update Down hole pressure set-point

24. Fault patterns a) Normal operation b) Leak in the standing valve c )Leak on the traveling valve d) Fluid pound PCA approach

25. Main objective: To initiate research on low cost measurement techniques for multiphase flow for heavy oil.

26. Other objectives:  installation of a multiphase flow laboratory for teaching purpose,  to study sensors for water in oil content, flow-rate measurements of gas flow, gas-liquid flow,  to test techniques for the control of severe slug flow,  to study new separation techniques.

27. Prototype being developed in the LEEM

29. Gas Oil-water Control system In line gas-liquid separator Water cut meter Liquid flow-rate measurement Gas flow-rate measurement Second stage separator Gas treatment (scrubber- compression, etc.) Output values of oil, water and gas flow-rates Level measurement

30. Motivation: What is needed to develop and test reliable, catastrophic failure proof automation systems to control remote offshore production facilities like unmanned platforms? Is simulation enough? To build a laboratory to test automation and control of production facilities including oil wells is similar to what was done in the airplane industry with the construction of Wind Tunnels.

31. The facility should be designed for testing optimization algorithms, fault detection and control algorithms conceived to a remote operation scenario. It should allow:  To test new down hole instruments  To test fault detection (real induced fault)  To test new control and automation surface instruments  To test constraint handling like gas injection flow rate, leaks, etc.

33. Fluid level controlled to simulate different depletion levels

34. Gravel with 4 grain sizes were investigated: Gravel 1: 0,59mm a 1,00mm Gravel 2: 0,71mm a 1,41mm Gravel 3: 1,00mm a 2,00mm Gravel 4: 2,00mm a 3,36mm.

35. Simulations with OLGA™ confirm expected dynamic behavior

36. The wellheads are installed inside a pit

37. Created by Research groups from Mechanical, Automation and Systems and Chemical Engineering with financing of Petrobras.

38. Localization in Florianopolis Island INPetro in the Sapiens Park – art. view INPetro – art. view

39. Main building outside view Main building inside view

40. Research Goals: Develop systems for real-time optimization, control and automation of production units and oil fields.

41.  Modeling  Control strategies  Optimization  Fault detection

42. GL - density wave behavior GL - heading behavior

44. Without control With control applied

46. Research goals  Models for mathematical optimization of equipment and production processes  Efficient algorithms for real-time optimal operation  Frameworks for system-wide optimization

47. Current research topics  Piecewise-linear models for optimal lift-gas allocation and separator alignment  Piecewise-linear models of multidimensional functions for pressure constraints  Models for compressor allocation and scheduling

48. Using simulators SENSOR ™ and ECLIPSE™ Our initial strategy is to use the knowledge existent in the simulator to build the dynamic representation of the process variables as function of the manipulated variables. Challenge: Is the solution the global optimum?

49. Prof. Dr. Ricardo Rabelo, Chief of the Automation and Systems Engineering Department-DAS UFSC talks minutes before signing an academic cooperation term with NTNU. Since 2007 researchers of DAS-UFSC, NTNU and Petrobras-CENPES have had academic meetings in congress and workshops. COPPE-UFRJ - February 18/2011.

51. Takk Thank you Obrigado