Unconventional Reservoirs Flow modelling challenges

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Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.

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  • Welcome, my name KP,a support engineer in Houston office and I have been with CMG for 6 years. The title of our presentation today is Shale Gas/Liquid reservoir simulation. Whenever any body asks me, Why CMG, I point out three of our greatest strengths, The Physics, we actually model the physics, we do not try and use tricks to get around hard problems; Ease of Use, and our demonstration today will illustrate our user friendliness; and our Technical Support, all we do is dynamic reservoir modeling and we are very passionate and focused on our technology and enabling our customers use of that technology.
  • Before, changes in fracture conductivity required a formula in Builder.Now, you may specify the fracture conductivity at the origin (center), and at the tips in Builder, and these may be selected as CMOST parameters .Picture micro-seismic data. Each color represents a different fracture stage.The round dots, which vary in size, represent the micro-seismic amplitude.Before MS generated SRV could be filtered manually in Builder.Now, this filtering can be done automatically with CMOST.
  • Before, changes in fracture conductivity required a formula in Builder.Now, you may specify the fracture conductivity at the origin (center), and at the tips in Builder, and these may be selected as CMOST parameters .Picture micro-seismic data. Each color represents a different fracture stage.The round dots, which vary in size, represent the micro-seismic amplitude.Before MS generated SRV could be filtered manually in Builder.Now, this filtering can be done automatically with CMOST.
  • Before, changes in fracture conductivity required a formula in Builder.Now, you may specify the fracture conductivity at the origin (center), and at the tips in Builder, and these may be selected as CMOST parameters .Picture micro-seismic data. Each color represents a different fracture stage.The round dots, which vary in size, represent the micro-seismic amplitude.Before MS generated SRV could be filtered manually in Builder.Now, this filtering can be done automatically with CMOST.
  • With the new Automated Work Flow, the HF Wizard in Builder can be directly tied to CMOST for assisting with:SAHMOptimization
  • With the new Automated Work Flow, the HF Wizard in Builder can be directly tied to CMOST for assisting with:SAHMOptimization
  • With the new Automated Work Flow, the HF Wizard in Builder can be directly tied to CMOST for assisting with:SAHMOptimization
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Matrix_Perm: Matrix PermeabilityMatrix_Poro: Matrix Porosity SW_Nat_Frac: Water Saturation in Natural native fractureXF: Fracture Half LengthPropped_Frac_Perm: Permeability of Hydraulically fracture blockPropped_Frac_Spacing: Spacing between the propped hydraulic fractureSW_Propped: Water saturation in Hydraulically propped blockRock_Compaction: Compaction table
  • Logarithmic Plot as a function of pressure
  • With the new Automated Work Flow, the HF Wizard in Builder can be directly tied to CMOST for assisting with:SAHMOptimization
  • Unconventional Reservoirs Flow modelling challenges

    1. 1. Unconventional Reservoirs Flow modelling challenges Victor Salazar victor.salazar@cmgl.ca November, 2013
    2. 2. Agenda 1. CMG products 2. Unconventional Reservoir Modelling Physics 3. Using CMG’s Reservoir Simulation products to Determine EUR from Limited Data 4. Using CMG’s Reservoir Simulation products to Optimize Well Completion Design & Well Spacing 5. SPE Unconventional Reservoir papers that feature the use of CMG’s Reservoir Simulation products
    3. 3. CMG Software Products Superior physics EOR advanced processes leader (+95%)  Project Manager LAUNCHER  Reservoir Numerical Simulators Black Oil/Condensate simulator GEM Equation of State Compositional Simulator STARS  Pre & Post Processors IMEX K value compositional, thermal, chemical, geomechanical simulator BUILDER RESULTS 3D RESULTS GRAPH RESULTS REPORT  Converter ECL 100 IMPORT ASSISTANT  Assisted history match, Optimization, Sensitivity and Uncertainty analysis CMOST  Phase behavior, PVT modelling WINPROP
    4. 4. Unconventional reservoirs physics Diffusion Desorption Fractured system Non-Darcy effects Low porosity/permeability Typical Shale Adsorption Curve Gas Adsorption (ft3/ton)      700 600 500 400 300 200 100 0 Shale 0 1000 2000 Pressure (psi) 3000 4000
    5. 5. CMG Simulator Physics Physics IMEX GEM PVT BO, VO, GC, WG EOS Adsorbed Comp Gas Comp Any Comp Diffusion No Any Comp Natural Fracs DP or DK DP or DK Non-Darcy (turbulent) Flow Yes Yes Klinkenberg (slip) Flow No Yes Krel/Pc by Rock Type Yes Yes Propped Fracs Explicit Grids Explicit Grids Press-dependent Compaction Yes (& w/ time) Yes (& w/ time) Stress-dependent Compaction No Yes (w/ GEOMECH) LS-LR-DK gridding Yes (& w/ time) Yes (& w/ time)
    6. 6. CMG Frac’d Well Modelling History
    7. 7. Microseismic Results Possible trend visible in blue stage Possible interaction with pre-existing fractures? Trend visible in red stage Shmax direction? In-situ stress will influence dominant hydraulic fracture orientations Williams-Stroud, Microseismic, 2008
    8. 8. Propped Frac Gridding is EASY BUILDER can create LS-LR-DK (tartan) grids around fractures automatically Single Plane Geometry Complex Geometry
    9. 9. Varying Propped Frac Properties & SRV Size with CMOST is EASY Propped Frac Properties Half-length, Width, Perm, Spacing, Height & Perm Gradient Stimulated Natural Frac Properties: Width, Perm SRV Size & Shape # MS events per gridblock MS Moment Magnitude MS Confidence Value Etc.
    10. 10. Geomechanics  Independent geomechanic grid  Hydraulic fracture closure  New fractures opening  Permeability vs Stress kf C kfmax D kfmin B Crack occurs Beginning A / σ fn
    11. 11. 3 key Questions about Unconventional Reservoirs 1. How can I determine the EUR with limited data? 2. What is the Optimum Well Completion Design? 3. What is the Optimum Well Spacing?
    12. 12. Physics-based EUR Calculation 1. Choose CMG simulator with required physics Engineer builds base model, decides which parameters to allow CMOST to vary, and CMOST does the rest 2. Build base model 3. Perform SA & AHM 4. Forecast EUR using best HM models
    13. 13. Physics-based EUR Calculation • 4000 ft Eagle Ford “Oil Window” well • 41-stage frac job pumped • 7 months of production (222 days) • Oil, gas & water rates, and flowing BHP measured daily • Task: Determine Oil & Gas EURs • Solution: Match 7 months of history & Forecast 30 years of future production
    14. 14. Physics-based EUR Calculation Known Reservoir, Well & Fluid Properties Property Value Unit Depth at top of reservoir Reservoir thickness Initial Reservoir Pressure Initial Reservoir Temperature Oil Bubble Point Pressure Oil Gravity Initial Solution GOR Lateral Length Number of Frac Stages Pumped 10,800 150 8,100 270 3010 43 950 4000 10 feet feet psi F psi API scf/stb feet
    15. 15. Physics-based EUR Calculation Ranges for uncertain reservoir & frac properties Property Min Value Max Value Unit Matrix Porosity Matrix Permeability Natural Fracture Effective Porosity Natural Fracture Effective Permeability Natural Fracture Areal Spacing Propped Fracture Spacing Propped Fracture Half-Length Propped Fracture Permeability Swi in Propped & Natural Fractures 0.04 10 0.0006 40 50 100 50 1 0.15 0.10 1000 0.0006 40 50 400 400 30 0.45 fraction nD fraction nD feet feet feet D fraction
    16. 16. Physics-based EUR Calculation Krel, Pc & PV Compaction Assumptions Property Matrix Krel Natural Fracture Krel Propped Fracture Krel Matrix Pc Natural Fracture Pc Propped Fracture Pc Matrix PV Compaction Natural Fracture PV Compaction Propped Fracture PV Compaction Assumptions Corey Functions are sufficient Straight Line behavior Straight Line behavior Can ignore during primary depletion Zero Zero Constant Compressibility Constant Compressibility Changes with Pressure
    17. 17. Physics-based EUR Calculation 2D Areal View of Simulation Grid
    18. 18. Physics-based EUR Calculation 3D Perspective View of Simulation Grid
    19. 19. Physics-based EUR Calculation  CMOST     Assisted HM Optimization Sensitivity and Uncertainty analysis
    20. 20. Physics-based EUR Calculation Discrete Values used in Sensitivity Analysis Matrix Perm (md) Nat Matrix Frac Por Swi (frac) (frac) Rock Comp Table # Prop’d Frac Xf (ft) Prop’d Frac Perm (md) Prop’d Frac Spacing (ft) Prop’d Frac Swi (frac) 0.00001 0.04 0.15 ctype1.inc 50 1000 100 0.15 0.0001 0.06 0.25 ctype2.inc 150 10000 200 0.25 0.0005 0.08 0.35 ctype3.inc 250 20000 300 0.35 0.001 0.1 0.45 ctype4.inc 400 30000 400 0.55
    21. 21. Physics-based EUR Calculation Propped Frac PV Compaction Curves Permeability Multiplier 1 0.1 ctype1 0.01 ctype2 ctype3 ctype4 0.001 0.0001 0 1000 2000 3000 4000 5000 Pressure, psia 6000 7000 8000 9000
    22. 22. Physics-based EUR Calculation Cumulative Oil Tornado Plot
    23. 23. Physics-based EUR Calculation Cumulative Water Tornado Plot
    24. 24. Physics-based EUR Calculation Discrete Values used in History-Match Nat Prop’d Prop’d Prop’d Prop’d Matrix Matrix Frac Rock Frac Frac Frac Frac Perm Por Swi Comp Xf Perm Spacing Swi (md) (frac) (frac) Table # (ft) (md) (ft) (frac) 0.00001 0.04 0.15 ctype1.inc 50 1000 100 0.15 0.00005 0.05 0.16 ctype2.inc 100 5000 150 0.20 0.0001 0.06 0.17 ctype3.inc 150 10000 200 0.25 0.0002 Total Search Space: 6.22 million15000 0.07 0.18 ctype4.inc 200 250 combinations 0.30 0.35 0.0003 0.08 0.20 250 20000 300 0.09 25000 350 0.40 0.0004 0.25 300 0.10 400 30000 400 0.45 0.0005 0.30 0.0007 0.35 0.40 0.001
    25. 25. Physics-based EUR Calculation History-Match Run Progress Plot Engineer only has to monitor History-Match progress….. so is free to work on other projects!
    26. 26. Physics-based EUR Calculation Oil Phase History-Match
    27. 27. Physics-based EUR Calculation Gas Phase History-Match
    28. 28. Physics-based EUR Calculation Water Phase History-Match
    29. 29. Physics-based EUR Calculation Flowing BHP History-Match
    30. 30. Physics-based EUR Calculation 30-yr Oil EUR using 15 best HM models Maximum Minimum Average Median Std Dev Oil EUR (stb) 724,059 571,847 654,125 649,323 45,162
    31. 31. Physics-based EUR Calculation 30-yr Gas EUR using 15 best HM models Maximum Minimum Average Median Std Dev Gas EUR (MMscf) 981 851 926 922 44
    32. 32. Time to do Physics-based EUR Task ENGINEER’s time 100 CMOST SA runs* 446 CMOST AHM runs* 15 x 30-year forecast runs** TOTAL COMPUTE Time Time (hr) 8 2.8 8.5 0.6 11.9 Time/Run (min) 1.7 1.1 2.5 - * 4 simultaneous 4-way parallel IMEX runs on a Dell Precision T5600 ** Sequential 16-way parallel IMEX runs on a Dell Precision T5600
    33. 33. Physics-based Well Optimization 1. Choose CMG simulator with required physics Engineer builds base model, decides which parameters to allow CMOST to vary, and CMOST does the rest 2. Build base model 3. Perform SA 4. OPT Completion Design 5. OPT Well Spacing
    34. 34. Physics-based Well Optimization Assumed Reservoir, Well & Fluid Properties Property Natural Fracture Relative Permeability Propped Fracture Relative Permeability Matrix Capillary Pressure Natural Fracture Capillary Pressure Propped Fracture Capillary Pressure Matrix Pore Volume Compaction Natural Fracture PV Compaction Propped Fracture PV Compaction Data Straight Line data from EUR calc. Straight Line data from EUR calc. Assumed to be zero Assumed to be zero Assumed to be zero Constant Constant “ctype4.inc” from EUR calc.
    35. 35. Physics-based Well Optimization Assumed Economic Parameters Economic Parameter Oil Price Gas Price Well Drilling Cost Frac Cost Forecast Period Value 100 3 3,000,000 250,000 30 Unit $US/bbl $US/Mscf $US/well $US/Stage years
    36. 36. Physics-based Well Optimization Proposed Well Completion/Spacing Options Property Proposed Well Spacing Proposed Well Lateral Length Min Value Max Value 128 640 (5 wells) (1 well) 4000 4000 Unit acres feet Proposed Propped Fracture Spacing 200 800 feet Proposed Propped Fracture Half-Length 50 400 feet Proposed Propped Fracture Permeability 1 20 D
    37. 37. Physics-based Well Optimization Discrete Values used for Completion Optimization Propped Frac Propped Frac Propped Frac Spacing Permeability Half-Length (feet) (Darcies) (feet) 200 1 50 300 3 100 400 6 200 Total Search Space: 240 combinations 500 9 300 600 12 400 800 15 18 20
    38. 38. Physics-based Well Optimization Optimization Run Progress Plot Engineer only has to monitor Optimization progress….. so is free to work on other projects!
    39. 39. Physics-based Well Optimization Optimum Parameter Histograms
    40. 40. Physics-based Well Optimization Cum Oil after 30 years vs # of Wells # of Wells 1 2 3 4 5 NPV (MMUSD) 49 97 145 191 230
    41. 41. Physics-based Well Optimization Matrix Pressure @ 30 years with 4 & 5 wells
    42. 42. Time to do Physics-based Well Completion & Spacing Optimization Task ENGINEER’s time Time (hr) 8.0 Time/Run (min) - 55 CMOST OPT runs* 5 IMEX 30-year Forecast runs** TOTAL COMPUTE Time 2.2 0.85 3.05 1.9 10.2 - * 4 simultaneous 4-way parallel IMEX runs on a Dell Precision T5600 ** 5 Sequential 16-way parallel IMEX runs on a Dell Precision T5600
    43. 43. SPE References Used GEM to model DFITs and concluded: • Greatly enhances our ability to efficiently design DFIT's for tight shale reservoirs • Shows the validity of the Nolte analysis technique for tight rocks and provides guidelines for the shut-in time duration required to generate a reasonable estimate of reservoir properties from DFIT pressure response • Shows that geomechanics-coupled reservoir flow simulation of DFITs can provide estimates of fracture dimensions that compare reasonably with those from more traditional fracture design tools • Demonstrate that geomechanics-coupled reservoir flow simulation provides an additiona advantage over traditional fracture design tools in that is can numerically model the system response even after fracture closure • Shows significant fracture tip extension, both vertically and horizontally, for a significant period after the end of the shut-in period
    44. 44. SPE References SPE 166279 Estimation of Effective Fracture Volume Using Water Flowback and Production Data for Shale Gas Wells Ahmad Alhkough (TAMU), Steve McKetta (Southwestern Energy) and Robert Wattenbarger (TAMU) Used IMEX to model water flowback and long-term production, and concluded: • Used to simulate production of gas and water from a shale gas well • Water production analysis can provide effective fracture volume estimates, which were confirmed by cumulative water produced, which in turn can evaluate fracture-stimulation treatments. • Water production analysis can show the pitfalls of ignoring flowback data (i.e. in some cases the time-shift on diagnostic plots changes the apparent flow regime indentification of the early gas production data, as well as water production data, which leads to different (incorrect) interpretation of the fracture/matrix system.
    45. 45. SPE References URTeC 1575448 Marcellus Well Spacing Optimization – Pilot Data Integration and Dynamic Modeling Study Deniz Cakici, Chris Dick, Abhijit Mookerjee, Shell Exploration & Production; Ben Stephenson, Shell Canada Used GEM & CMOST to Match production history
    46. 46. 36 E&P Companies are using CMG for Unconventional Reservoir Modelling • • • • • • • • • • • • Anadarko Apache BG Group BHP Billiton Birchcliff Bonterra BP Chesapeake Chevron Devon Encana Enerplus • • • • • • • • • • • • EOG ExxonMobil Harvest Marathon Matador Nexen Noble Energy PennWest Perpetual Petrobakken Reliance Rosetta Resources • • • • • • • • • • • • Samson Sasol Seven Generations Shell Sinopec Daylight Southwestern Energy Statoil Talisman Taqa North Total Vitruvian XTO “Physics-based” EUR & Well Optimization in hours using CMG software
    47. 47. VISION: To be the Leading Developer and Supplier of Dynamic Reservoir Technologies in the World info@cmgl.ca www.cmgl.ca

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