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Feature classification.ppt
- 1. Carbonate heterolithic classification/1 1 km 100 m 200 microns Scales of carbonate reservoir heterogeneity
- 2. Carbonate heterolithic classification/2 Image log & dipmeter analysis course Characterisation of carbonate reservoir heterogeneity using borehole image logs
- 3. Carbonate heterolithic classification/3 • Fractures – Closed or open – Natural or drilling induced – Orientation, spacing and frequency • Faults – Determine strike and dip of the fault – Determine rock displacement along the fault – Reservoir compartmentalisation • In-situ stresses – Borehole breakout – Drilling induced fractures – Potential & artificial fracturing • Input to fracture modeling Static Dynamic 36 72 N Structural heterogeneities
- 4. Carbonate heterolithic classification/4 • Borehole imaging tools • Heterogeneities – Structural – fractures/faults – Depositional and diagenetic – Pore system evaluation • Reservoir rock typing • Conclusions Outline
- 5. Carbonate heterolithic classification/5 channels reefs slide blocks 0.1 mm 100 m 1 km 10 km 1 m 10 m 1 cm 10 cm 1 mm CORE (Limited Coverage) BOREHOLE IMAGES 3D SEISMIC (Limited Resolution) fracture width ripples dish structures/dewatering bioclasts soft sediment deformation scours/erosion surfaces grain size/bed thickness trends bedforms channel lags slumps Scales of investigation
- 6. Carbonate heterolithic classification/6 Micro-resistivity Acoustic Fracture Bedding Feature classification and characterisation
- 7. Carbonate heterolithic classification/7 CBILsm ACOUSTIC EARTH Imagersm GR HEXDIPsm 5m Fracture identification in oil based mud systems
- 8. Carbonate heterolithic classification/8 • For resistivity images: – Conductive (dark image) =/= Open? – Resistive (light) =/= Closed? • For Acoustic Images – low amplitude (dark) =/= Open? – high amplitude (light) =/= Closed? • Core calibration can be used to confirm – Image logs can only provide an interpretive insight only • Only dynamic data provide true insight into fracture “producibility” Open versus closed fractures
- 9. Carbonate heterolithic classification/9 Micro-resistivity images in horizontal well displayed as pseudo-core sticks Feature classification
- 10. Carbonate heterolithic classification/10 Flowmeter data Conductive (open) fractures Acoustic Calibration of image log data with core
- 11. Carbonate heterolithic classification/11 BIU 1 BIU 3A BIU 2 BIU 3B Formation Test Data (psi) 110.3 26.2 26.2 25.5 10.4 11.8 9.5 12.8 8.9 8.6 7.9 BIU 3B BIU 2 BIU 1 Bedding contact WSW ENE MINOR FAULT B MINOR FAULT A MAJOR FAULT A BIU 3A Fault compartmentalisation
- 12. Carbonate heterolithic classification/12 • Increased compartmentalisation – Permeability barriers • Increased communication – Permeability conduits • Overall objective - producibility – Fracture model inputs – Fault seal predictions – Production enhancement – Completion strategy – Selection of perforation intervals GO Fracture characterisation
- 13. Carbonate heterolithic classification/13 • Well and fracture orientation • Fracture density • Core density calibration • Borehole corrected fracture density • Fracture spacing • Fracture length? • 3D modelling Schematic path dow n boreho le (69* / 210*) Schematic path down bo reho le (69* / 210*) Mesozoic carbonate Oil staining OBLIQUE-SLIP Fracture distribution
- 14. Carbonate heterolithic classification/14 Stylolitic seams Conductive, tension gashes Resistive cemented limestone Dissolution seam Stylolites and dissolution seams
- 16. Carbonate heterolithic classification/16 • Image facies assigned on basis of image character, open hole log response • Image response is related to electrical or acoustic properties, responds to rock texture, fluid saturation and mineralogy • Not possible to distinguish all core lithofacies • Calibration with core allows a meaningful geological interpretation of image logs Image facies
- 17. Carbonate heterolithic classification/17 0 10 20 30 40 50 60 % B-Zone Image facies 0 10 20 30 40 50 60 % B-Zone Image facies 0 10 20 30 40 50 60 % B-Zone Image facies 0 2 4 6 8 Average thickness (ft) Image facies 0 2 4 6 8 Average thickness (ft) Image facies 0 2 4 6 8 Average thickness (ft) Image facies 0 2 4 6 8 Average thickness (ft) Image facies Well 4 - uncored Well 3 Well 2 0 10 20 30 40 50 60 % B-Zone Image facies Well 1 IF1 IF2 IF3 IF4 IF5 IF6 IF7 IF8 IF9 IF10 IF11 Image facies statistics
- 18. Carbonate heterolithic classification/18 •Identification, orientation and analysis of primary stratification surfaces/heterogeneities •Identification of key stratal surfaces •Borehole image facies analysis •Depositional modelling •Sequential analysis •Pore fabric analysis •porosity and permeability distribution •Palaeotransport/reservoir geometry analysis Depositional heterogeneities
- 19. Carbonate heterolithic classification/19 Thin bed identification below the resolution of openhole logs STAT DYN MINIPERM PROFILE High resolution image log response
- 20. Carbonate heterolithic classification/20 Resistivity Image Resistivity Image Acoustic Image Acoustic Image Resistivity Image Resistivity Image Acoustic Image Acoustic Image Reef core Back-reef lagoon Image log facies analysis – reef facies
- 21. Carbonate heterolithic classification/21 Oil based mud Facies stacking patterns and dip analysis
- 22. Carbonate heterolithic classification/22 Image facies show an overall coarsening/ shoaling- upward trend with increasing stacking pattern in upper part of reservoir Stacked fining-upward grain/pack/ wackestone units Mostly trendless succession of mudstone/ wackestones Interpretation Coarse, vuggy rudist float to rudstones Image facies prediction in uncored wells
- 23. Carbonate heterolithic classification/23 Reservoir architecture
- 24. Carbonate heterolithic classification/24 Unit A Unit B Breccia Image facies Lateral facies variations in horizontal wells
- 25. Carbonate heterolithic classification/25 Porosity classification
- 26. Carbonate heterolithic classification/26 Porosity classification Fenestral Shelter Growth framework Interparticle Intraparticle Intercrystalline Mouldic Fracture Channel Vug Cavern* Breccia Boring Burrow Shrinkage Fabric-selective Non-fabric-selective Fabric-selective or not * Cavern applies to human sized or larger pores of channel and vug shapes
- 27. Carbonate heterolithic classification/27 Pore fabric analysis
- 28. Carbonate heterolithic classification/28 15 20 Ft Elongate conductive patches represent secondary mouldic porosity after bioclasts filled by conductive drilling mud. Conductive (open?) fracture Micro-resistivity Mouldic and vuggy porosity
- 29. Carbonate heterolithic classification/29 Vuggy carbonates seen in both acoustic and resistivity images Image analysis can be used to threshold the image and determine the % vuggy macroporosity and degree of interconnectivity Acoustic Micro-resistivity Vuggy porosity
- 30. Carbonate heterolithic classification/30 _ 3.41 _ 1.64 _ 2.35 _ 0.21 _ 0.75 _ 2.81 _ 1.81 Log K Permeability map Thin section Core Microporous nodular limestones
- 31. Carbonate heterolithic classification/31 STATIC Cemented tight limestone Microporous high permeability limestone Porosity distribution from images
- 32. Carbonate heterolithic classification/32 A RRT has a unique reservoir quality but not necessarily lithofacies. • Typically established in cored wells on basis of thin section and SCAL data. • Extrapolation into uncored wells using openhole logs and used to predict permeability. – fine scale permeability heterogeneity below resolution of standard openhole logs. – subtle changes in pore system can result in similar porosities but permeability can vary by several orders of magnitude. • High resolution image logs used for Image Rock Type (IRT) identification and permeability prediction. Reservoir rock typing
- 33. Carbonate heterolithic classification/33 Conductive, high K vuggy skeletal grainstones at base of units Resistive, low K wackestones at top of units Stacked small- scale fining- upward units, with high K grainstones at base grading up into low K wackestones Image facies
- 34. Carbonate heterolithic classification/34 Calculate K statistics and define K rank Organise core poro-perm data by image facies (cross-plots) Group image facies into K classes: “image rock types” Assign image image rock types using porosity from openhole log data as guide to ‘background’ rock type. Assign K rank and value along- side image rock types interpretation QC predicted K against measured core K RRT/ permeability prediction workflow
- 35. Carbonate heterolithic classification/35 0.01 0.1 1 10 100 1000 10000 0 5 10 15 20 25 30 35 40 Helium porosity (%) Horizontal permeability (mD) Poroperm coded by image facies Poroperm calibration Image facies grouped into image rock type 0.01 0.1 1 10 100 1000 10000 0 1 2 3 4 5 6 7 8 9 Image Rock Type Horizontal permeability (mD)
- 36. Carbonate heterolithic classification/36 Results from blind test showing predicted permeability against permeability from core analysis data RRT and permeability prediction
- 37. Carbonate heterolithic classification/37 Permeability prediction - dipmeter data
- 38. Carbonate heterolithic classification/38 RRT/permeability variations
- 39. Carbonate heterolithic classification/39 IRT IRT RRT & permeability prediction
- 40. Carbonate heterolithic classification/40 Conclusions • Borehole image logs provide high resolution, oriented data sets – Provide key information on nature, orientation and scale of fracture and fault systems, and compartmentalisation – Provide information on texture, lithofacies and reservoir rock types. – Porosity and permeability distribution – Identification of small-scale heterogeneity below resolution of standard openhole logs • Make more effective use of uncored wells to build, constrain & validate 3D reservoir model realisations