Integration From Multiple Disciplines in Horizontal Well Evaluations to Increase Production in Organic Rich Shales by Kevin Fisher
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Drilling horizontal wells is the common mode of operation for field development in permeability-challenged unconventional reservoirs such as an organic shale. Assumptions are made regarding the homogeneity of the reservoir as wells are drilled away from the vertical pilot well. It is assumed that the reservoir characteristics remain uniform and that the structure is known to remain in a constant orientation based on the dip information at the pilot wellbore. Experience tells us that these assumptions can lead to wells placed out of zone and in rocks with much different reservoir quality and stress magnitude, which can adversely affect the well’s production potential. Lateral measurements and petrophysical interpretations can be used to define variations in reservoir and completion quality, which can be used to optimally place perforation clusters in similar rock to increase production vs. peer geometric wells. A methodology to integrate data from many sources enables a better understanding of the variability and structural challenges of these complex reservoirs. This integrated methodology has been refined using learnings from various case studies that show increased production compared with results from geometric completions. Kevin is currently the Chief Petrophysicist at Rock Oil Company. Recently, Kevin retired from Schlumberger as a Senior Petrophysicist based in Houston, TX with nearly 27 years of experience in petrophysics and rock physics, after graduating from the University of Tulsa with a degree in Petroleum Engineering. While at Schlumberger, he worked in the Production Technology Integration Center focusing on unconventional resource plays, mainly in the Eagle Ford and Permian basins. Additional areas of expertise have been deep water and shelf structures in the Gulf of Mexico, tight gas sands in South TX and Rockies, Alaska, Permian Basin, Unconventional Gas & Oil shales, Coal Bed Methane and international (Australia, Brazil, Argentina, United Kingdom, France, Nigeria, Angola, Turkey and Saudi Arabia). Kevin is a guest lecturer since 2012 at Rice University for a graduate level petroleum geology class entitled “Economic Geology – Petroleum”.
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Integration From Multiple Disciplines in Horizontal Well Evaluations to Increase Production in Organic Rich Shales by Kevin Fisher
- 1. Primary funding is provided by The SPE Foundation through member donations and a contribution from Offshore Europe The Society is grateful to those companies that allow their professionals to serve as lecturers Additional support provided by AIME Society of Petroleum Engineers Distinguished Lecturer Program www.spe.org/dl
- 2. Society of Petroleum Engineers Distinguished Lecturer Program www.spe.org/dl Kevin Fisher Multi-Discipline Approach to Increasing Production in Organic Rich Shales
- 3. Agenda • Reality • Workflow: Integration – Geology Quality: GQ – Reservoir Quality: RQ – Completion Quality: CQ • Results (multiple basins) • Lessons learned 3
- 4. Reality – Lateral Lengths 4204 2910 4064 3556 2485 6908 3536 4516 5677 5290 5384 4882 5712 9050 5479 8379 0 2000 4000 6000 8000 10000 Haynesville Marcellus Fayetteville Barnett Eagle Ford Bakken Montney Horn River Lateral Length (ft) Average Lateral Length (ft) 2013 2008 10 8 5 6 10 14 6 11 15 22 11 10 23 32 17 22 0 5 10 15 20 25 30 35 Haynesville Marcellus Fayetteville Barnett Eagle Ford Bakken Montney Horn River Number of fracturing stages Average Frac Stage Count 2013 2008 4
- 5. Reality – Production Source: IHS B3 = Best 3 months production 5 Haynesville Barnett Bakken Eagle Ford
- 6. Production is Not Uniform 6 Production Log Examples Only 64% of the Perforation Clusters are contributing All wells were completed Geometrically 61% 62% 67% 59% 69% Miller-SPE-144326-MS-P 2011
- 7. Horizontal Production Log • Evaluation of Production Log Data from Horizontal wells Drilled in Organic Shales – Miller-SPE-144326-MS-P-2011 • Designed specifically for horizontal wells 88 degrees 90 degrees 92 degrees 7
- 8. Fiber Optics Geometric Design Engineered Design 8Anifowoshe, et al, SPE-184051-MS 5 5 5 5 4 4 5 5 Clusters Clusters Time Time
- 9. Case Study: Eagle Ford Consortium Original Hypothesis: 1. “In a horizontal well placed in good Reservoir Quality rock with lateral variation in stress, a more effective stimulation can be achieved by grouping similarly stressed rock for treatment.” 2. “This will be characterized by a reduced number of perforation clusters showing no productivity, leading to better overall recovery and drainage” 9Slocombe, et al, SPE 13ATCE-P-166242 2013
- 10. Unconventional Reservoir Optimized Completion (U-ROC) Field Development Well Optimization Asset performance Petroleum systems modeling Reservoir quality Well design Stimulation design Production simulation Drilling and Completion Quality Seismic interpretation Geological framework Geomechanics Completion optimization Microseismic monitoring 10 Geology Quality Reservoir Quality Completion Quality The keys to Completion Optimization
- 11. Geology Quality: GQ • Analog – Outcrop • Landing Point • “Like Rock” • Pilot to Lateral correlations 11
- 12. Analog – Outcrop Eagle Ford example 12 Donovan, URTeC 1580954, 2013
- 13. Know your Geology • Members • Units • Issues – Clay – Ash beds – Fractures – Faults • Identify on logs 13 Donovan, URTeC 1580954, 2013
- 14. UV Core Photos - B3/B4/B5 14 (Ash Beds are fluorescent)
- 15. UV Core Photos - B1/B2 15 (Ash Beds are fluorescent)
- 16. ClusterAnalysis Correlating Science Pilot well to Lateral with “like rock” types 16 40 feet 30feet Eagle Ford Outcrop
- 17. Lateral Measurements and Deployment • Openhole • Casedhole • LWD • Cuttings 17 Reischman, R., SPE-143963-MS, 2011
- 18. Sort “rock groups” based on petrophysical parameters Apply geological meaning to “rock group” clusters Propagate “rock groups” from pilot to lateral. Verify “rock groups with logs & interpretation Perform cluster analysis to determine optimal number of “rock groups” IPSOM Rock Quality 1 High TOC marl 2 High TOC marl 3 Low TOC argillaceous shale 4 Limestone 5 Low TOC marl Reservoir Quality: RQ “Like Rock” Workflow 18 Grouping “like rock” Color/Rock Type Clay Volume Fraction (v/v) 0.134 0.294 0.434 0.055 0.21 Effective Porosity (v/v) 0.074 0.068 0.034 0.039 0.016 Permeability (nD) 245 133 23 24 10 Total Organic Carbon (weight %) 4.90% 4.30% 2.20% 3.00% 1.90% Thermal Neutron Porosity (v/v) 0.162 0.208 0.212 0.086 0.102 Bulk Density (g/cc) 2.422 2.449 2.565 2.519 2.579 Gamma Ray (gAPI) 67.9 87 99.4 49.9 69.6
- 19. Pilot 19
- 20. Lateral 20
- 21. Pilot and Lateral Integration 21 Lateral curtain 73 boepd per stage 18 boepd per stage 15 feet
- 22. Case Study: RQ vs. Rock Groups Time Lapse Production Log • 2 production logs run 6 weeks apart • Delta Hydrocarbon 22 Good RQ -5 bpd Bad RQ -14 bpd
- 23. Completion Quality: CQ 23 Stress Lithology NPHI DPHI GR Clusters Sonic Wigger, E., et al, SPE 14UNCV-167726-MS, 2014
- 24. Optimizing Completion integrating RQ and CQ 24 RQ CQ Composite VClay Stress Gradient Porosity Mineralogy Geometric Geometric 1000 950 900 850 800 750 700 650 600 550 500 450 400 350 300 250 200 150 100 50 0 460 psi Engineered Engineered
- 25. Frac Stage Pressure Differential 25 480 psi 160 psi 245 psi 35 psi 455 psi 595 psi 115 psi -10 psi 205 psi 635 psi 450 psi 225 psi 1280 psi 405 psi 470 psi 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 StageClosurePressureVariation(psi) Frac Stage Difference in Average Stage Pressure Differential between Geometric and Engineered Completion = 385 psi
- 26. Engineered Completion Results: 940 bopd / 375 bwpd 26 85.3% Perforation Efficiency 64% Average Perforation Efficiency for Geometric Designs
- 27. Production Comparison 27 2 5 10 20 30 40 50 60 70 80 90 95 98 - 2. 33 - 1. 83 - 1. 33 - 0. 83 - 0. 33 0. 17 0. 67 1. 17 1. 67 2. 17 10 100 1,000 10,000 CumulativeProbability Max Month Average BOE, BOE/D Max Month Average 799 BOE/D 48.5% increase in production 20 Offset Wells Cum GOR: 0 – 3,000 scf/bbl 1 BOE = 1 bbl oil or 6 Mscf gas
- 28. Increased Production – Engineered vs. Geometric Well Best 1 month bpd P50 of Offsets bpd % Production Increase Well A 799 538 48.50% Well B 1258 499 152.10% Well G 950 798 19.00% Well H 560 392 42.90% Well I* 730 789 -7.50% Well J 1100 392 180.60% Well K 771 495 55.80% Average 881 558 58.0% * 1/3 of lateral out of zone
- 29. Eagle Ford Consortium Results • Increased perforation efficiency from 64% to 82% (28% increase in lateral contribution) • Increased well performance by an average of 58% vs. average offsets • 28% increase in lateral contribution yields a 58% increase production (Not Linear) 29Slocombe, et al, SPE 13ATCE-P-166242 2013
- 30. Eagle Ford Results 30 86% Kreimeier, et al, URTeC: 2461822, 2016
- 31. Permian Wolfcamp Results (Clean out issues) 31 0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0 10,0 Engineered Well Offset 1 Offset 2 Offset 3 90DaysCum.BOE/LateralLength Wells Engineered has 54.4% increase Geometric = 5.93 BOE/ft average
- 32. Niobrara Results 32Pirie, et al, URTeC: 2154958, 2015 Engineered stages outperformed geometric stages by 2 – 3 times
- 33. Marcellus Results 33 Engineered outperformed geometric by 33% & 40% on initial production Well A – Geometric Well B – Engineered Well C – Engineered
- 34. Lessons Learned • Geology Quality (GQ) – Layers and landing point is critical to production. • Reservoir Quality (RQ) – Near wellbore has influence in the over flushed stimulated fracture zone. • Completion Quality (CQ) – Perforations in similar stress rock initiate simultaneously. – Fracture modeling 34
- 35. Conclusion Integrating Geology Quality (GQ), Reservoir Quality (RQ) and Completion Quality (CQ) in the engineered designed completion leads to increased production when compared to peer wells with geometric designed completions. 35
- 36. Society of Petroleum Engineers Distinguished Lecturer Program www.spe.org/dl 36 Your Feedback is Important Enter your section in the DL Evaluation Contest by completing the evaluation form for this presentation Visit SPE.org/dl
- 37. References • Miller, SPE-144326-MS-P, 2011 • Slocombe, et al, SPE 13ATCE-P-166242, 2013 • Donovan, URTeC 1580954, 2013 • Anifowoshe, et al, SPE-184051-MS, 2016 • Kreimeier, et al, URTeC 2461822, 2016 • Xu, et al, SPE-179110-MS, 2016 • Calvin, et al, SPE-175961-MS, 2015 • Wigger, et al, SPE 14UNCV-167726-MS, 2014 37
- 38. Thank You For Attending! Question & Answer Session 38