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Geoconvention 2011 by Kelli Meyer
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Geoconvention 2011 by Kelli Meyer

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Using a seismically-derived density volume and facies characteristics to optimize the thermal well trajectories in the clearwater formation, Alberta. …

Using a seismically-derived density volume and facies characteristics to optimize the thermal well trajectories in the clearwater formation, Alberta.

By Kelli Meyer of Osum Oil Sands, Robert McGrory of TerraWRX Exploration Consultants Ltd. and Shawna Christensen of Throndson Energy Ltd.

Published in: Technology, Business

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  • Introduce myself and Osum Oil Sands Corp. Introduce Rob McGrory and TerraWRX; Created the velocity model, depth surfaces and inversion model. Introduce Shawna Christensen and Throndson Energy; Facies characterization of the Clearwater and Grand Rapids Disclaimer about being a geologist and any detailed inversion questions will be answered by Rob in the audience.
  • Have over 20m of net pay in areas of the Taiga lease – hot colours denote thicker pay These types of reservoirs are what the future will be for oil sands We are planning both SAGD and CSS, but the talk will only concentrate on SAGD well planning
  • Talk through the Clearwater formation – three stacked sands, 2 oil saturated across our field and make up our current development plan including the Lower Grand Rapids (not talked about in this presentation), S3 is oil saturated in the west of Taiga and is part of our future development plans There is a gas cap and basal water and M1 mudstone – so we really need to know where we are placing our wellbore
  • You will have to use all available data including seismic, logs, core and 3D modelling to economically produce emerging oil sands plays 12-3 o’clock represents the first and most traditional way of planning SAGD wells. The continuation of the flower in a clockwise motion describes the additional steps that we have incorporated to optimize our SAGD well placements
  • Blue outlines Taiga lease Black outlines our Phase 1 SAGD Purple outlines continuing phases for SAGD pads (34 pads total) Red outlines CSS pads (16 total) Red dashed outlines our S1 gas cap Grey dashed denotes middle mustone greater than 1m Blue dashed outlines basal water Green dashed denotes 3D seismic outline Lighter pink were dipole sonic not used in inversion
  • Blue outlines Taiga lease Black outlines our Phase 1 SAGD Purple outlines continuing phases for SAGD pads (34 pads total) Red outlines CSS pads (16 total) Red dashed outlines our S1 gas cap Grey dashed denotes middle mustone greater than 1m Blue dashed outlines basal water Green dashed denotes 3D seismic outline Lighter pink were dipole sonic not used in inversion
  • Where M1 is greater than 1m, we do not consider the S1 as thermal net pay for SAGD SAGD pads, where: M1<1 meter, pay = S1+S2 M1>1 meter, pay = S2 only CSS pads, pay = S1+S2 The next slide is closeup of the core photos form this well
  • We are not showing all facies, just facies within the Phase 1 area that affect well placement Start stratigraphically with the oil saturated M2 Place wellbore above the nodular zone where appropriate Place wellbore below M1 The majority of the reservoir facies is F1
  • In between wells, we decided that we needed a better way to model porosity and facies instead only using a statistical algorithm, so we incorporate seismic data which will be the focus of this next section Our 3D seismic has a bandwidth of over 200 Hz – so we have a great seismic dataset to work with Data Quality: Excellent with a frequency range 10 Hz  190 Hz at 30db down. Acquisition Parameters Geophones : 3C Source Type: Dynamite Source Line Interval: 80 meters Receiver Line Interval: 80 meters Source interval: 20 meters Receiver Interval: 20 meters
  • Example of well tie to Near Angle Stack. Well correlations had correlation coefficients in excess of 60% after data conditioning. Seismic interpretation Correlation of wells to Seismic Map horizon and produce 2-way time structure maps.
  • Generalized work flow for depth conversion!
  • How Inversion: How Pre-stack Inversion Preconditioned AVO compliant gathers 3 angle stacks (0 o -12 o , 12 o -24 o , 24 o -36 o ) Initial Model (4 wells with DT, DTS, Den) Statistical Wavelets for each angle stack Pre-stack seismic inversion requires several inputs: Image 1 avo-compliant seismic Angle gathers (color is angle of incidence derived from rms velocities), Image 2 synthetic Angle stacks derived from well logs Image 3 Extracted wavelets for each angles stack over the zone of interest Image 4 rock-physics relationships to equate lithology to observed density (for example). Starting with an initial model, the HR-Suite inversion software uses these constraints to invert the input seismic into basic rock properties… the most useful that we have found to date is the density property. Requires Pre-stack data conditioned for AVO or angle stacks Logs for initial model Low Frequency model Wavelets for each angle stacks Output Vp/Vs, P-imp, S-imp, Density etc
  • Tracks 1-2 Panel showing well logs (GR, Vshl (track 1), Bulk density (blue), inverted density (red) (Track2) Tracks 3-5 Inverted density, Inverted P-Impedance, Inverted Vp/Vs Tracks 6 Near Angle Stack (0-12 degrees)
  • Low correlation error at wells
  • CW gas on this section 6-26 is projected
  • Left Image: Density and Lithology (GR/Vshl) are well correlated (Upscaled GR vs Upscaled Density) – match frequency content Right Image: Lithological classification based on Vp/Vs vs Density crossplot (upscaled) colored by Vshl Calcite, Shale and sand separate nicely in this cross-plot This cross-plot could be used for lithology classification (was not done in this instance) – Coloured Calculated Vshale Cross Plotting one or more seismic attributes (Ip, Is, Vp/Vs, Den, λρ and μρ ) against reservoir attributes of importance PHIT Vshl Sw Provides a framework to interpret inverted seismic in terms of reservoir properties.
  • This is not an incised valley fill play Clearwater shale is transgressive and is an excellent caprock and caps the full Clearwater sequence
  • Transcript

    • 1. Osum Oil Sands Corp | Using a Seismically-Derived Density Volume and Facies Characterization to Optimize Thermal Well Trajectories in the Clearwater Formation, Alberta Kelli Meyer* Osum Oil Sands Corp. Robert McGrory TerraWRX Exploration Consultants Ltd. Shawna Christensen Throndson Energy Ltd.
    • 2. Intro Map
      • Cold Lake Oil Sands
      • Clearwater and
      • Grand Rapids
      • Reservoirs
      • Planned SAGD and
      • horizontal CSS
    • 3. Importance of Well Placement
      • Thermal Net Pay
        • >27% porosity
        • >10 ohm.m
      • Taiga Clearwater net pay averages 12m and is laterally continuous
    • 4. Importance of Well Placement
      • Taiga Clearwater net pay averages 12m and is laterally continuous
      • Well placement at the base of the reservoir maximizes producible pay
      6.4 km West East M2 S2 S1 M1 S3
    • 5. Importance of Well Placement
      • Taiga Clearwater net pay averages 12m and is laterally continuous
      • Well placement at the base of the reservoir maximizes producible pay
      • Accurate mapping of the base of the reservoir using seismic, core and logs is key to optimal well placement
      Integrated Model Seismic Inversion Rock Physics 3D Geologic Model Velocity Model Seismic Horizons Stratigraphic Model Facies Model Logs Core Data Grain Size SAGD Well Trajectories
    • 6. Dataset
      • 60 delineation wells
      • -logged and cored
      • -5 wells FMI
      • -6 wells dipole sonic
      • -viscosity measurements
      • -grain sizes, XRD, SEM
      • 32.5km 2 3D seismic
      • 5 - 2D seismic lines
      • Model software:
      • -Petrel TM
      • -Hampson-Russell TM
      • Facies analysis, 3D geological model, reservoir simulations and seismic inversion
    • 7. Reservoir Summary Phase 1 SAGD Pads Additional SAGD Pads CSS Pads S1 Gas Cap Basal Water M1 > 1m
    • 8. Clearwater Shale regional caprock Clearwater Sand 1 upper sand Clearwater Mud 1 bioturbated mudstone Clearwater Sand 2 lower sand cemented nodule Clearwater Mud 2 Interlaminated sands and muds Lost core Net Pay (12m)
    • 9. Facies F2b F2b F1 (Shoreface): Vf-f ss, homogeneous, hz-low angle parallel lams, low bioturbation = RESERVOIR F3a (Distal Delta Front): 50% vf-f sandstone and 50% sandy medium gray mudstone interbeds, moderate bioturbation = M2 Cemented F2b (Distal Delta Front): Ss, with 10-50% mudstone, hz parallel lams, low-mod. bioturbation = RESERVOIR F4a (Distal Pro-Delta): med. gray mudstone intermixed with 50% vf ss, extensive bioturbation = M1
    • 10. Seismic Integration Hz Porosity
    • 11. Well Synthetic Tie: example 2-5-66-1 W4M CC > 70% Near Angle Stack Synthetic Sonic Density Gamma Ray Zone of Interest
    • 12. Velocity Model for tying wells and surfaces Velocity model converts horizons and inverted models from time to depth
    • 13. Pre-stack Seismic Inversion
    • 14. Seismic Inversion Results CW Shale CWS1 CWS2 CWM2 CWM1
    • 15. Inversion Error QC Excellent correlation Testing control logs against inverted volume Geologic Model Geophysical Model
    • 16. West East 06-26-65-02W4 VE=10x
    • 17. VE=10x 3D Petrel model of 120 Lower Grand Rapids and Clearwater well trajectories with seismic and inverted density volumes
    • 18. Conclusions
      • Seismic inversion helps visualize basal nodules and middle mudstones
      • The fully integrated model allows;
      • -predictable reservoir facies
      • -minimization of stranded pay zones
      • -optimized placement of SAGD wellbores
      • The fully integrated model allows rapid updating and adaptability as new wells are drilled and 4D seismic is acquired
      • This result will provide input to modelling steam chamber growth
      • Planning of infill wells
      • Further work on fluid contacts and placement of Lower Grand Rapids wells above basal water
      Future Applications
    • 19. Acknowledgements
      • Ken Gray,
        • Senior Staff Geophysicist
      • Jen Russel-Houston,
      • Manager, Geosciences
      • Elizabeth Earl
      • Hartmut Janssen & Peter Carey
    • 20. Rock Physics GR Density Shale Calcite Sand Vp/Vs Density Density is the key attribute!
    • 21. Stratigraphy Clearwater Shale Lower Grand Rapids Shoreface Stacked Clearwater Shorefaces Lower Grand Rapids Channel Fill Lower Grand Rapids Lateral Accretion Very Fine to Fine Sand Fine to Medium Sand Intermixed Sand, Silt and Shale – Non Reservoir Shale The Clearwater Formation is laterally continuous across the Taiga field West East S3 S2 S1