Downloaded 17 times
More Related Content
Similar to Simulation_Basic_1.pptx
Simulation_Basic_1.pptx
- 1. Reservoir Simulation Institute ofReservoir Studies
- 2. Overview 2 2 Model Building 3 Reservoir Simulation– Black Oil 4 History Matching 5 Performance Prediction #2 E&P Company in the world 1 Reservoir Engineering - Goal 6 Data Input Reservoir Simulation – Concept Reservoir Performance Analysis 7 8 Reservoir Simulation – Compositional & Thermal 9
- 3.
- 4. 4 Most valuable IndianPSU Reservoir Engineering ----- Goals Development of oil & gas fields in an optimal and economical manner Maximize hydrocarbon recovery at minimum cost • How much hydrocarbon is present? • How much can be recovered? • How fast can it be recovered? Hydrocarbon in-place Hydrocarbon Reserves (Producible quantity) Rate and duration of Production (field life) Reservoir performance analysis
- 5. 5 Most valuable IndianPSU Reservoir performance analysis Five methods, namely – Analogical, Experimental, Statistical, Analytical and Mathematical Analogical method • Using mature reservoir properties that are similar to the target reservoir to predict the behavior of the reservoir • This method is especially useful when there is a limited available data
- 6. 6 Most valuable IndianPSU Reservoir performance analysis Analogical method - case study Deeper reservoir- Assam Asset: Depth:>4000m, Rec: 6% of OIIP, Phi: 8-12%, Perm: 10-40 mD, Flowing strings: 7 • One probable reason for higher recovery - more wells drilled into deeper reservoir
- 7. 7 Most valuable IndianPSU Reservoir performance analysis Experimental method • Measure the reservoir characteristics in the laboratory models and scale these results to the entire hydrocarbon accumulations
- 8. 8 Most valuable IndianPSU Reservoir performance analysis Statistical Method • In this method, the past performance of numerous reservoirs is statistically accounted for to derive the empirical correlations which are used for future predictions • It may be described as a 'formal extension of the analogical method' The analytical approach • In most of the cases, the fluid flow inside the porous rock is too complicated to solve mathematically • Systematic and logical approaches are used to predict future performance
- 9. 9 Most valuable IndianPSU Reservoir performance analysis Mathematical method • Applied basic conservation of laws • The three basic equations: • Material balance equation or continuity equation • Equation of motion or momentum equation – Darcy’s Law • PVT or equation of state • These three equations are expressed for different phases of the flow in the reservoir and combine to obtain single equations for each phase of the flow • The mathematical method traditionally includes material balance equation and decline curve methods • The advanced mathematical model – reservoir simulation
- 10. 10 Most valuable IndianPSU Material Balance Calculations --- Tank model We N=OIIP Assumptions: • The material balance calculations are based on tank model • Homogeneous pore volume, gas cap, aquifer • Constant temperature • Uniform pressure distribution • Uniform hydrocarbon saturation distribution
- 11. 11 Most valuable IndianPSU Decline Curve Decline Curve • The rate of oil production decline generally follows one of the following mathematical forms: exponential, hyperbolic and harmonic. The following assumptions apply to the decline curve analysis • The past processes continue to occur in the future • Operation practices are assumed to remain same Major producing field of Assam, Ult Res: 38000 Mm3 Generated by OFM • Recovery: 42% of Ult Reserves • In 2047 recovery: 50% of Ult.Res
- 12.
- 13. 13 Most valuable IndianPSU What is Reservoir Simulation The process of mimicking and inferring the fluid flow behavior in a petroleum reservoir system through the use of physical and mathematical models
- 14. 14 Most valuable IndianPSU Why Reservoir Simulation Best estimate for development planning/performance review Understanding of present setup of field responsible for exploitation Justify investment decision, review expected/ pending profile Reduce uncertainties Best tools for Reservoir Engineers
- 15. 15 Most valuable IndianPSU Reservoir Simulation ------Process
- 16. 16 #2 E&PCompany in the world Reservoir Simulation ----- Concept
- 17. 17 #2 E&PCompany in the world Reservoir Simulation --- Equations
- 18. 18 Most valuable IndianPSU Darcy’s Law • Practically all reservoir simulation studies involve the use of Darcy's law • It is important to understand the assumptions behind this momentum balance equation • The fluid is homogenous, single-phase • No chemical reaction takes place between the fluid and the porous medium • Laminar flow condition prevails • Permeability is a property of the porous medium, which is independent of pressure, temperature and the flowing fluid L P Q kA 001127 . 0 Q = flow rate, bbl/d A = cross sectional area, ft2 μ = fluid viscosity, cp K = permeability, md P = pressure, psi L = length, ft
- 19. 19 #2 E&PCompany in the world Reservoir Simulation --- Equations
- 20. 20 #2 E&PCompany in the world Equation of State (EOS) Equation of state (EOS) or PVT behaviour The material balance in reservoir simulation is usually done on the following basis • For gas, the real gas law is used • The liquid phase has dissolved gas, which is a linear function of pressure (black oil) • Water is characterized as a liquid of low compressibility, which is a linear function of pressure
- 21.
- 22. 22 #2 E&PCompany in the world Reservoir Simulation Model build-up • Preparation of earth model – Static model • Up-scaling of static model - Coarsening • Preparation of dynamic model – Simulation model
- 23. 23 #2 E&PCompany in the world Reservoir Simulation --- Static model • Incorporate structural and fault framework into the model with gridding • Petrophysical modelling –property modelling • Volumetric calculation Structural modelling
- 24. 24 #2 E&PCompany in the world Reservoir Simulation --- Static model • Petrophysical modelling Porosity distribution
- 25. 25 #2 E&PCompany in the world Reservoir Simulation --- Static model • Petrophysical modelling Saturation distribution
- 26. 26 #2 E&PCompany in the world Reservoir Simulation --- Static model • Volumetric calculation
- 27. 27 #2 E&PCompany in the world Reservoir Simulation --- Static model After completion of static model ----- • Earth model prepared • Model with structure top-bottom & faults • Porosity distribution • SW (water saturation) distribution • NTG distribution • OWC/ GOC if present • Define FVF (PVT data for volume calculation) • Volumetric estimation - OIIP
- 28. 28 #2 E&PCompany in the world Up-scaling --- Static model • Scale up the structure and properties onto a coarser grid • Up-scaling is the process of creating a coarser (lower resolution) grid based on the geological grid which is more appropriate for simulation • Static model can contain tens of million cells • Simulation is usually suitable one lakh to one million cells • To prepare simulation grid as close to orthogonal
- 29. 29 A FORTUNE Global500 Company Up-scaling --- Static Model Up-scaled the model (Static to Dynamic) Up- scaled the model Static model with 1 m vertical thickness Dynamic model with 3 m vertical thickness
- 30. 30 A FORTUNE Global500 Company Up-scaling --- Static Model Up-scaled the model (Static to Dynamic) Static model 1m thick Dynamic model 3 m thick
- 31. 31 #2 E&PCompany in the world Up-scaling --- Static Model 0 100 0 Permeability, mD Stratigraph ic Model Dynamic model Static model Log scaled
- 32.
- 33. 33 #2 E&PCompany in the world Reservoir Simulator --- Black Oil Conventional “Black Oil” simulators Simulators (IMEX/ECLIPSE-100) • Oil & Gas phases are represented by one ‘component’ • Assumes composition of gas & oil components are constant with pressure & time • Assumes temperature is constant throughout the reservoir
- 34.
- 35. 35 #2 E&PCompany in the world Reservoir Simulation --- Dynamic modeling Preparation of dynamic model & Data Input • Permeability modelling • Define fluid properties – PVT of water, oil & gas • Define dynamic flow property – relative permeability • Define rock property - compressibility • Define capillary pressure • Define initial pressure of the model • Define aquifer – if present
- 36. 36 #2 E&PCompany in the world Dynamic Model ---Permeability modeling 1. Porosity-permeability correlation based on laboratory generated basic core data
- 37. 37 #2 E&PCompany in the world Dynamic Model --- PVT Data • PVT data of water, oil & gas • Laboratory generated PVT data of oil & gas • Water PVT data – water FVF, water compressibility & water viscosity • Surface density of water, oil & gas
- 38. 38 #2 E&PCompany in the world Dynamic Model --- Relative Permeability • Relative permeability of water, oil & gas system • Laboratory generated SCAL data is used • If different regions are defined in the model, region-wise rel-perm data have to incorporated – if available • If more than one set of rel-perm data are available, normalize will be done to average and again de-normalize is to be done
- 39. 39 #2 E&PCompany in the world Dynamic Model --- Capillary Preesure • Capillary pressure is used to define the fluid distribution in the reservoir • Laboratory generated capillary pressure data is used Transform lab capillary pressure data to reservoir conditions Pc (Reservoir conditions) = Pc (Lab) x (Sigma.Cos(theta))res /(Sigma.Cos(theta))lab Typical values of Sigma.Cos(Theta) are; Lab Air-Water: 72 Oil-Water: 42 Air-Mercury: 367 Air-oil : 24 Reservoir Water-oil : 26 Water-gas : 50
- 40. 40 #2 E&PCompany in the world Dynamic Model --- Aquifer • Define aquifers, describing the type, size and connections of the acting aquifer. • Aquifer modeling is a method of simulating large amounts of water (or gas) connected to the reservoir whereby it is not essential to know how the fluid moves in it, but rather how it affects our reservoir.
- 41. 41 #2 E&PCompany in the world Dynamic Model --- Aquifer modeling • Numerical aquifer: A set of cells in the simulation grid is used to represent the aquifer. Their position in the model is irrelevant • Fetkovich aquifer: The aquifer flow model is similar to the well inflow model. It is best suited for smaller aquifer that may approach a pseudo steady-state condition quickly • Carter Tracy Aquifer: It uses tables of dimensionless time versus a dimensionless pressure as influence function
- 42.
- 43. 43 #2 E&PCompany in the world Reservoir Simulation ---Initialization The purpose of initialization is to specify or obtain the initial conditions of the model – pressure, saturation and solution GOR Equilibrium condition has been assigned in the model considering • OWC and GOC • Initial pressure – region wise • Capillary pressure – if required • Run the model • If no error, compare the volume (OIIP) with static model • Dynamic model is ready
- 44. Data Input inDynamic Model
- 45. 45 #2 E&PCompany in the world Dynamic Model --- Well data Well Data • Well locations, trajectory, completions • Workover history – Z/T, squeeze, HF • Production rates of oil, water and gas as a function of time • Pressure history of the wells – bottom hole pressure (flowing & static), build-up pressures • Injection history – rates, fluids, pressure, etc
- 46. History Matching &Prediction
- 47. 47 #2 E&PCompany in the world Reservoir Simulation --History matching & prediction
- 48. 48 #2 E&PCompany in the world Reservoir Simulation ---History matching • Normally the most time-consuming phase of a simulation study • Used to demonstrate the validity of the simulation model • Input historical production rates of oil/gas then simulator calculates pressures and secondary products (GOR, WC, etc.) to be compared with history • If needed, compare calculated and actual performance of individual wells • Adjust model input parameters to achieve an acceptable match
- 49. 49 #2 E&PCompany in the world Reservoir Simulation ---History Matching Parameter Adjustment: History Matching • Adjust reservoir permeability to match field pressure gradients • Adjust permeability and areal extent of shales or other low-perm zones to match vertical fluid movement • Adjust relative permeability-saturation relationships to match dynamic saturation distributions and pressure gradients • Adjust aquifer size, thickness, and permeability to match the amount and distribution of natural water influx • Use pore volume multiplier to adjust OIIP of the model
- 50. 50 #2 E&PCompany in the world History matching & Uncertainty The following variables are often considered to be indeterminate (high uncertainty): - Pore volume - Permeability - Transmissibility - Kv/Kh ratio - Rel. perm. curves - Aquifer properties - Mobile oil volumes
- 51. 51 #2 E&PCompany in the world History matching & Uncertainty The following variables are often considered to be determinate (low uncertainty): - Porosity - Gross thickness - Net thickness - Structure (reservoir top/bottom/extent) - Fluid properties - Rock compressibility - Capillary pressure - Datum pressure - Original fluid contact - Production rates
- 52. 52 #2 E&PCompany in the world History Matching --- Case Study
- 53. 53 #2 E&PCompany in the world History Matching --- Case Study
- 54. 54 #2 E&PCompany in the world History Matching --- Case Study
- 55. 55 #2 E&PCompany in the world History Matching --- Sensitivity Analysis • Deeper reservoir of Assam • Initial run
- 56. 56 #2 E&PCompany in the world History Matching --- Sensitivity Analysis Tornado Plot Uncertainty & Optimization: Petrel-Eclipse CMOST: CMG
- 57. 57 #2 E&PCompany in the world History Matching --- Sensitivity Analysis • Deeper reservoir of Assam • Initial run
- 58. 58 #2 E&PCompany in the world History Matching --- Sensitivity Analysis Well- wise history match
- 59.
- 60. 60 Most valuable IndianPSU Prediction After satisfactory history matching, field performance is predicted Limiting Conditions • FBHP • Water Cut • Well abandonment rate • Variant-I: Base case (considering available producers and injectors) • Variant-II • Variant-III
- 61. 61 Most valuable IndianPSU Prediction ---- Base Case • Base case: Field performance is predicted with available OP (9) and WI (7)
- 62. Prediction Identification of NewInfill Locations Preparation of Development Scheme
- 63. 63 Most valuable IndianPSU Prediction --- New Infill Locations Conventional Method • New locations are generally identified based on average remaining oil saturation and current pressure map after history matching • Locations are predicted on history matched model with available producers and injectors
- 64. 64 Most valuable IndianPSU Prediction --- New Infill Locations Average So map after history Conventional Method
- 65. 65 Most valuable IndianPSU Prediction --- New Infill Locations Conventional Method
- 66. 66 Most valuable IndianPSU Prediction --- New Infill Locations Simulation Opportunity Index method, SPE 148103 • SOI is calculated on history matched model and identified 3 locations and subsequently predicted with other producers and injectors
- 67. 67 Most valuable IndianPSU Prediction --- New Infill Locations Simulation Opportunity Index method, SPE 148103 SOI Map
- 68. 68 Most valuable IndianPSU Prediction --- New Infill Locations Opportunity Index Method, SPE 122915
- 69. 69 Most valuable IndianPSU Prediction --- New Infill Locations Opportunity Index Method, SPE 122915 Opportunity Index Map
- 70. 70 Most valuable IndianPSU Prediction --- New Infill Locations Case:2: Available producers +3 new development locations Np: 2.130 MMm3, Recovery: 32.87% of model OIIP
- 71. 71 Most valuable IndianPSU Development Scheme Case-1: BAU case (Business as usual) – with existing OP and WI or GI Recovery: Case-2: With new development OP- depletion case Recovery: Case-3: With new development OP + WI – IOR Scheme Recovery: Case-4: With new development OP + WI + EOR – EOR Scheme Recovery:
- 72.
- 73. 73 #2 E&PCompany in the world Types of Reservoir Simulators Special-purpose simulators can model compositional, thermal, and chemical processes in EOR projects • Compositional simulators can model performance of volatile- oil and gas-condensate reservoirs in which phase compositions vary widely with pressure (GEM, Eclipse-300) • Thermal-process simulators can model steam cycling and steam flooding (STAR, Eclipse-500/Eclipse Thermal) • Chemical-processes simulators can model polymer injection, surfactant flooding, and flooding with alkaline solutions (STAR, ECLIPSE-100)
- 74. 74 #2 E&PCompany in the world Reservoir Simulation --- Compositional • It is useful when the behavior of the hydrocarbons is complex— condensate or volatile crude oil, or miscible gas injection developments fall in this category • In black oil simulation, flow is considered in terms of oil, water and gas where no mass transfer between the phases is considered (except that of gas between oil and gaseous phase). In Compositional simulation flow is considered in terms of oil, water and gas but mass transfer between phases is also considered. • In Black-oil simulation, summation of phase saturations is unity while in the compositional simulation summation of mole fraction of different chemical components is unity.
- 75. 75 #2 E&PCompany in the world Reservoir Simulation --- Thermal • It is used to simulate thermal EOR processes like In-situ combustion, Steam injection, etc. • Here, heat energy conservation is also performed. • Thermal recovery methods are typically used in heavy oil reservoirs where the oil viscosity is high at reservoir temperatures, but reduces as the temperature increases A number of thermal recovery processes can be simulated • Steam injection, such as cyclic steam injection (huff and puff), steam flood, or steam • Hot fluid or gas injection • Well bore heaters • Combustion
- 76.