1. Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario P. Moreau 1, M. Morvan 1 ; B. Bazin 2, F. Douarche 2, J-F. Argillier 2, R. Tabary 2 1 – Rhodia 2 – IFP Energies Nouvelles Neuquen EOR workshop - November 2010

2. 2 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 World-class geosciences public-sector research Global leader in specialty chemicals and formulation Independant E&P consulting and software editor (IFP subsidiary) Polymer technologies for IOR and well performance 2 Bring together the capabilities required for Chemical EOR…

3. 3 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Outline Introduction Chemical EOR (ASP/SP) – Basics Rhodia-IFP énergies nouvelles & partners An integrated workflow Process & material selection Chemical formulation optimization Coreflood validation Simulation An Illustrative Case study Conclusion & Perspectives

4. 4 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 After waterflood, oil remains trapped in reservoirs because of capillary trapping at Sor Oil displacement (typical Residual Oil Saturation  70%) Capillary trapping Mobility control to drive the surfactant slug and bank the oil to the production well Chemical EOR (ASP/SP) - Basics Water Oil Waterflood Illustration of capillary trapping in micromodels (developed at Rhodia LOF). The only realistic way is to drastically decrease the interfacial tension (  ) Optimized surfactant formulations Water Saturation  w =  oil  w = 0.1  oil Polymer Surfactant slug integrity is secured by controlling mobility ratio 100  m

5. 5 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 An integrated workflow... Expertises Chemistry & Reservoir engineer competencies for selecting appropriate process and chemicals High Throughput Screening (HTS) capabilities are critical to test large number of chemical combinations & provide optimized and robust formulations Increase in oil recovery and minimum adsorption must be demonstrated in cores. Lab-scale simulations are required before Up-scaling and injection strategy definition – Physics from SARIP CH implemented to full field simulators Step 2 Step 3 Step 4 Step 1 Towards pilot simulation with a commercial simulator A reservoir engineering approach from lab to pilot simulation

6. 6 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 …With integrated solutions EOR methods screening Integrated reservoir analysis Selection of EOR methods Laboratory design – A 4 steps methodology Process & Material selection Chemical formulation optimization Coreflood validation Lab-scale simulation Impact on water management Pilot design Numerical simulation at pilot scale Pilot economics Surface facility conceptual design Pilot implementation / Full field extension Field management and monitoring Expertise and assistance to operations Full-field surface facility design Dedicated supply-chains High-volume logistics Large-scale manufacturing 6

7. 7 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Step 1: Process and Material Selection The most promising EOR chemicals are pre-selected according to reservoir conditions Surfactants: Surfactant portfolio: olefin sulfonates, alkoxylated alcohols, sulfated/sulfonated alkoxylated alcohols, alkyl aryl sulfonates. Raw material selection and process are critical. Industrially representative samples are essential to guarantee pilot performances. Alkali: Different alkalis are available depending on salinity and temperature. Divalent ions concentration is critical for the use of alkali. Possible hurdles at very high temperature. Polymer: Polymer is a case by case selection with permeability, temperature and salinity limitations. Step 2 Step 3 Step 4 Step 1 Critical information for process selection from reservoir data Reservoir temperature Brine composition (divalent ions, TDS...) Salinity distribution inside the reservoir Oil properties (API, viscosity, acid number) Rock properties (clay content, permeability) Calcium concentration distribution calculated after waterflooding Ca 2+ (ppm)

8. 8 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Microemulsion phase behavior Winsor classification III I II Interfacial tension vs microemulsion Optimal formulation Variability for different reservoirs Oil (composition, viscosity) Reservoir parameters (T, P…) Heterogeneities in a given reservoir Salinity, temperature gradients Oil and rock properties Chemicals selection & Formulation optimization is necessary for each reservoir Robustness of the formulation must be evaluated Salinity (g/l) Step 2: Chemical formulation optimization 4000+ formulations are required for a small design study. HTS tools are necessary Step 2 Step 3 Step 4 Step 1

9. 9 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Automated formulation and analysis Automated formulation Imaging & Image processing Selection of the best formulations Further optimization of chemicals concentrations and ratios Step 2: Chemical Formulation Optimization Morvan et al. SPE113705 (2008) Step 2 Step 3 Step 4 Step 1 Salinity (g/L) Optimal Salinity Microemulsion Solubility A fully automated formulation and optimization workflow Data generation for improved simulations  water/microemulsio n  oil/microemulsion Morvan et al. SPE113705 (2008)

10. 10 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Adsorption tests Adsorption depends mainly on pH Alkali can be used in soft brines Compatibility with hard brines could be challenging A specific evaluation (pH vs. solubility) is necessary depending on reservoir conditions Step 2: Chemical Formulation Optimization Step 2 Step 3 Step 4 Step 1 Dynamic adsorption in sandpacks or cores Surfactant adsorption from breakthrough time Hydrodynamic retention from plateau chemicals concentration Surfactant adsorption profiles in different brines VV pH of hard brines with alkali Static adsorption of an olefin sulfonate on Na-Kaolinite as a function of pH

11. 11 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Step 3: Coreflood validation with dedicated tools Oil recovery experiments Characterization of core material (CT scan, RMN, HPMI...) Petrophysics data Relative permeabilities vs saturation Capillary desaturation curve Analysis Oil recovery efficiency Surfactant mass balance Alkali propagation Mobility control Pressure monitoring… Recovery experiments at reservoir conditions (live oil, pressure, temperature) Step 2 Step 3 Step 4 Step 1 1.05 cp solution 74 mD Formulation injectivity test Formulation injectivity/plugging is assessed Millifluidic setup with calibrated cores Single phase flow injectivity test prior to coreflood ΔPΔP

12. 12 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Step 3 : Core flood validation and strategy A specific injection strategy must be optimized for each pilot Design – Injection with Salinity Gradient A salinity window is defined in a range of salinity extending from the produced water to the injection water Surfactant formulation optimum salinity is optimized inside the salinity window to meet the three phase region during displacement. Additional advantages Surfactant desorption with salinity gradient at the rear Good mobility control at the rear of surfactant slug Preparation of the surfactant formulation in low salinity water improves solubility. The injection strategy depends on: Field conditions Brines & water management issues (river or sea water and production brine; water treatment) Available ground facilities Step 2 Step 3 Step 4 Step 1

13. 13 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 PumaFlow - Beicip Franlab commercial simulator for simulations at pilot scale Step 4: Simulation from Lab to Reservoir scale Oil cut Cumulative oil Sarip CH is a prototype simulator for chemical EOR Black oil simulator with mass balance equations for chemicals (Alkaline, Surfactant, Polymer) Physics implemented Capillary desaturation curve and Kr, Pc curves Surfactant IFT with salinity gradient Surfactant adsorption with salinity gradient and pH Polymer physics Additional options: ion exchange with clays,calcium carbonate dissolution/precipitation Sarip CH simulations at lab scale Modeling of coreflood experiments Model calibration prior to pilot simulations Optimization of injection strategy & sensitivity analysis Experimental tables or analytical expressions are validated with core displacements Step 2 Step 3 Step 4 Step 1 Validation of simplified physics

14. 14 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 SARIP TM simulation: comparison with other simulators SARIP TM UTChem PumaFlow EclipseStars Application Core / Pilot In house simulator Core / PilotFull field Main characteristics 3D, 2 phases (water, oil) heterogeneity (k, Pc) cartesian kr, Pc = f( ,Nc) 3 phases (oil, water, microemulsion) cartesian.... 3 phases (oil, water, gas) cartesian, CPG dual media in 2011... 3 phases (oil, water, gas) cartesian, CPG... 3 phases (oil, water, gas) surf in gas (foam) cartesian, CPG Physics of surfactant pseudo-surfactant (surfactant, in situ surfactant) IFT tables (pH, salt, conc) ads=f(conc,salt, pH) compositional IFT from phase diagram in situ surfactant from chemical reaction. ads=f(conc,salt, pH) as SARIP TM without alkali in 2010 alkali available in 2011 IFT tables (conc) ads=f(conc) IFT tables (pH, salt, conc) ads= f(conc, salt) Physics of Ions tracers salt variation ion exchange alkali precipitation idem SARIP TM constant salt no alkali no info Physics of polymer RM=f(shear rate, salt, rock, conc) Rk, RM, ads = f(salt) Tables/analytic effect of ads on kro and Swir Analytic Viscosity dispersion... as SARIP TM Analytic Effective viscosity.... as Eclipse prototype commercial

15. 15 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Model reservoir characteristics Temperature: 60°C Production brine: 50 g/L NaCl Injection brine: mixture production/fresh water Model oil: EACN 12 Rock: sandstone Permeability: medium An illustrative case study Formulation design Surfactants mixture: Olefin sulfonate Alkyl Ether Sulfonate Cosolvent: short chain alcohol Alkaline: Na 2 CO 3 (10 g/L) Polymer: HPAM (MW  6MD) Optimum salinity: 36 g/L Formulation performances Ultra-low interfacial tension (  10 -3 mN/m) Excellent solubility/injectivity Acceptable adsorption (  150  g/g) Formulation performances Ultra-low interfacial tension (  10 -3 mN/m) Excellent solubility/injectivity Acceptable adsorption (  150  g/g) Process & material selection Process: ASP Alkali: Sodium carbonate/metaborate Surfactants: Sulfonates Polymer: HPAM x1000 formulations

16. 16 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Formulation design for a salinity gradient strategy Injection is done with a salinity gradient in order to promote WII- WIII-WI transition during flooding The scenario is illustrated here An illustrative case study - Formulation Solubilization ratios Salinity Formation brine Polymer drive Surfactant slug Optimal salinity Microemulsion Solubility Surfactant slug salinity Polymer Chase water salinity Reservoir brine

17. 17 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Injection strategy in a salinity gradient Slug size (PV) Salinity NaCl (g/L) Surfactant Conc. (g/L) Alkaline Conc. (g/L) Polymer Conc. (g/L) Waterflooding -50--- Alkaline Surfactant 0.530810- Polymer 225-101 Chase water 525--- An illustrative case study – Core Flood Oil Recovery pH Surfactant conc. Oil cut Cumulative oil The oil bank occurs at 0.3 PV Oil saturation after surfactant flooding is 18% (65% of the oil remaining after waterflooding has been recovered) Excellent pH propagation No formation damage (mobility reduction compared to relative viscosity)

18. 18 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 An illustrative case study – Simulation at lab scale IFT = f (Composition) Accurate predictive simulations with a limited number of adjustable parameters Same physics implemented for pilot design Use of in-house Sarip CH simulator to reproduce coreflood results Input data Extensive data from petrophysics & formulation Simulation results Excellent oil recovery prediction Good surfactant adsorption profile

19. 19 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 An illustrative case study – Simulation at pilot scale Simulations at pilot scale with input data from lab steps Simulation Quarter 5-spot Grid: 75x75x3 (16875) Wells: 1 injector, 1 producer Injection - Input data Slug size (PV) Surfactant Conc. (g/L) Polymer Conc. (mg/L) Alkaline preflush 0.5-- SP formulation 0.52.5200 Polymer 0.3-500 Chase water 2.3-- Reservoir - Input data Geometry: 3 layers (layer cake) Reservoir Thickness: 13 m X-Y linear extension: 267.75 m Irreducible water saturation: 0.35 Residual oil saturation: 0.32

20. 20 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Sensitivity to slug size Base case: 0.3 PV with 20% ROIP recovery Low additional oil recovery with higher slug size: 22 % ROIP with 0.5 PV of ASP injection 25 % ROIP with 1.0 PV of ASP injection Sensitivity to slug size Base case: 0.3 PV with 20% ROIP recovery Low additional oil recovery with higher slug size: 22 % ROIP with 0.5 PV of ASP injection 25 % ROIP with 1.0 PV of ASP injection An illustrative case study – Simulation at pilot scale IFT = f (Composition) Optimization of a pilot injection Simulations at pilot scale – Sensitivity study Sensitivity to surfactant concentration Surfactant concentration is a critical parameter and must be optimized together with the surfactant slug size to achieve the best economical design Sensitivity to surfactant concentration Surfactant concentration is a critical parameter and must be optimized together with the surfactant slug size to achieve the best economical design Sensitivity to adsorption Surfactant consumption by adsorption is extremely costly in terms of oil recovery Sensitivity to adsorption Surfactant consumption by adsorption is extremely costly in terms of oil recovery

21. 21 Brigitte Bazin et al - Application of an Advanced Methodology for the Design of a Surfactant Polymer Pilot in Centenario - Neuquen EOR workshop November 2010 Conclusions The integrated workflow presented here is based on: A fast identification of the best chemicals for given field conditions An extensive optimization study thanks to robotized techniques Core flood experiments for adsorption and oil recovery determination Optimization at pilot scale with simulations using extensive experimental input data Methodology deployed for multiple customers worldwide The integrated workflow presented here is based on: A fast identification of the best chemicals for given field conditions An extensive optimization study thanks to robotized techniques Core flood experiments for adsorption and oil recovery determination Optimization at pilot scale with simulations using extensive experimental input data Next step: development at reservoir scale Chemical reservoir model available (PumaFlow) Sensitivity analysis Optimization of injection strategy

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