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LEVERAGING SHALE INSIGHTS FOR OPERATIONAL EFFICIENCY AND MAXIMUM PROFIT
- 1. Decision-Making Technology for Oil and Gas Using the industry's only genuinely coupled hydraulic fracturing, wellbore, and reservoir simulator November 2, 2022
- 2. 2 Quantitative Optimization Market conditions, company objectives, and operational constraints are constantly evolving Drilling inventory is a finite resource The subsurface is complex and hard to predict Optimization must be multifaceted Trial and error is an inefficient optimization method Computational models are now highly predictive
- 3. 3 McKinsey Vaca Muerta Report – 2022
- 4. 4 Tripling Production in < 10 Years Vaca Muerta United States Source: MarcoTrends 3x 2.5x
- 5. 5 It’s Not Just Oil Price Free Cash Flow by Year
- 6. 6 It’s Not Just Oil Price Free Cash Flow by Year
- 7. 7 Well Design Should be Reactive to Commodity Pricing
- 8. 8 Design Varies as Function of Price Well spacing Absolute NPV/section Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl
- 9. 9 Design Varies as Function of Price Well spacing Absolute NPV/section Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl
- 10. 10 Rising Oil Price Lifts All Scenarios Well spacing Absolute NPV/section Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl
- 11. 11 Rising Oil Price Lifts All Scenarios Well spacing Absolute NPV/section Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl
- 12. 12 Optimal Design is a Function of Oil Price Well spacing Absolute NPV/section Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl
- 13. 13 Why Optimal Design Matters Well spacing Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl Absolute NPV/section
- 14. 14 Why Optimal Design Matters Well spacing Well spacing Well spacing Well spacing $40/bbl $55/bbl $80/bbl $100/bbl Absolute NPV/section 8% loss in NPV/section
- 15. 15 Need the Ability to Forecast Performance From Inputs Kaufman et al., 2019
- 16. 16 Who is ResFrac? • ResFrac was founded in 2015 to support science-based decision making • Leveraged years of research of co-founder Dr. Mark McClure at Stanford and UT at Austin • Rapid adoption across the shale patch with 80%+ YoY growth since inception • Only commercial modeling software that fully couples fracture, reservoir, and geomechanics dynamics Case studies in every major basin co-authored with operators
- 17. 17 ResFrac Provides a Holistic Modeling Software Fracture Propagation Geomechanics Reservoir Flow Economics 1 2 3 4 Cumulative Discounted Cash Only commercial solution to fully-couple fracturing, geomechanics, and reservoir
- 18. 18 Why is Now Different? Distance to gauge Pressure Albrecht et al., 2022 Raterman et al., 2019 Cipolla et al., 2022 The last five years have yielded unprecedentedly detailed, in-situ measurements of hydraulic fractures
- 19. 19 Why ResFrac? Albrecht et al., 2022 Shahri et al., 2021 Numerical models can replicate and predict these behaviors Shahri et al., 2021 Ratcliff et al., 2022 Rate per stage
- 20. 20 Coupled-Physics Unveils Parameter Dependencies Cluster spacing Proppant loading 3
- 21. 21 Negative Returns to Increased Well Spacing Proppant loading Well spacing Well spacing NPV NPV 500 lb/ft 5000 lb/ft 100 ft 2000 ft • Wells too close suffer from adverse interference • Wells too far apart leave unexploited resource behind
- 22. 22 Diminishing Returns to Increase Proppant Proppant loading Well spacing Well spacing NPV NPV 500 lb/ft 5000 lb/ft 100 ft 2000 ft • Too little proppant and wells are under-stimulated • Too much proppant and additional cost does not recover incremental
- 23. 23 Coupled Model Reveals Symbiotic Relations Proppant loading Well spacing Well spacing NPV NPV 500 lb/ft 5000 lb/ft 100 ft 2000 ft • Colored circles identify corresponding cases • As well spacing is increased, optimizer tries to compensate by pumping more proppant
- 24. 24 Collaborative Study Demonstrated Results Driven by Physics 7 Operators 10 High-fidelity data sets 4 Basins Results and behaviors consistent within basins, different by basin
- 25. 25 Examples of Data Sets Included • Paper presents three Permian data sets (two Midland Basin, one Delaware basin) • Each data set contained multiple wells of different generations and high fidelity diagnostics • Each data set history matched and optimized, and differences/ similarities compared
- 26. 26 Midland Basin Frac Hit Before During Aperture Pressure Saturation
- 27. 27 Well Productivity Affected by Parent Age and Distance • The older the parent, the lower the productivity of the first-order child • The closer the child, the lower the productivity
- 28. 28 STACK – Additional Damage From Frac Hits A. All child frac’ed with same design B. Child well furthest from parent produces on par with parent C. Parent well productivity declines substantially after frac hit
- 29. 29 Large Productivity Declines From Frac Hits • Primary production, hit, production decline, and child production captured in single, continuous model • Fracture conductivity damage matched production decline and child well order
- 30. 30 Conductivity (“Gummy Bear”) Damage in the STACK HVFR mass fraction Hydrocarbon saturation Fracture conductivity Conductivity damage
- 31. 31 Comparing Parent-child Interactions Across Basins • Similar to STACK, chemical damage occurs in Montney frac hits. Chemical damage not observed in Midland/Delaware • Increase child offset is more valuable in the Montney than in Permian Child offset Montney Type Well 70% max parent degradation Time (yrs) 20 0 Normalized cumulative gas 0 10 Child offset Permian Type Well 24% max parent degradation Time (yrs) 0 20 Normalized cumulative oil 0 5
- 32. 32 Opportunity to iIprove NPV and DROI by 25% to 60% • Blue line represents design prior to the ResFrac study • Study identified significant opportunities to improve both NPV/section and ROI • Vertical growth exhibited in both Midland and Delaware; however, vertical growth is neutral in Midland, while detrimental in Delaware, manifesting in different frac order recommendations
- 33. 33 Quantitative Optimization Cumulative oil Time (years) Optimal design is a function of fracturing, reservoir, operational, and economic considerations Modeling workflows empower operators to accelerate their innovation cycle Computational models are now highly predictive
- 35. Appendix
- 36. 36 ResFrac was Founded in 2015 to Support Science-Based Decision Making Dr. Mark McClure CEO and Co-founder Stanford PhD UT at Austin Professor Fracture and geothermal expert Harts 40 Under 40 Dr. Charles Kang CTO and Co-founder Stanford PhD Hank Ramey Award Optimization and hydraulic fracturing expert Dr. Mark Zoback Sr. Executive Advisor Stanford Professor World-renowned geomechanics expert Countless awards Joe Frantz Sr. Executive Advisor Previous executive roles at Range Resources and CEO of Unbridled Resources Garrett Fowler COO Stanford MS Operator/service company background SPE Regional Technical Award
- 37. 37 Chart showing point at which optimization released Optimization capabilities released • Steady growth across the all markets • Optimization and automation workflows now make up more than half the usage
- 38. 38 Applied Optimizations – HFTS 2 • Consortia of 16 operators and DOE funded most detailed analysis of subsurface to- date • Detailed characterization and modeling of • Fracture propagation • Depletion and productive zones • Communication between wells
- 39. 39 Optimization Identified 60% Uplift in NPV/Section Pudugramam et al., 2022 • Optimized: landing zone, well spacing, cluster spacing, proppant loading • Cluster spacing shows plateau then decreasing NPV/section • Proppant loading shows returns to higher volumes until plateauing
- 40. 40 Nuanced and changing objectives • Each point is a specific design scenario
- 41. 41 Nuanced and changing objectives • Each point is a specific design scenario
- 42. 42 Nuanced and changing objectives • NPV is not the only performance objective • NPV is in competition with other metrics, like ROI