Grizzly Oil Sands

Modeling Lateral Accretion in the McMurray Formation at Grizzly Oil Sands Algar Lake SAGD Project

Duncan Findlay1, Thomas Nardin1, Andrew Couch2, Alex Wright1

1Grizzly Oil Sands ULC, 2EON

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Introduction

• Laterally accreting channel systems are important reservoirs in the

McMurray Formation.

• These reservoirs are by their nature stratigraphically complex and

heterogeneous – Inclined Heterolithic Strata.

• SAGD performance (SOR, RF, Oil Rate) is strongly dependent on

the distribution of permeability within these depositional systems.

• Therefore, realistically representing the stratigraphic architecture in

geological models is required to accurately predict reservoir

performance.

• Here we present a geomodel which incorporates geometries of the

reservoir with outcrop observations, core, log and 3D seismic data at

Grizzly Oil Sands Algar Lake property.

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Grizzly Oil Sands Land Holdings

800,000+ Net Acres of Alberta Oil Sands Leases

Algar Lake - 56,960 contiguous acres of oil sands leases at the center of the

Athabasca region

Grizzly Oil Sands Lease

Other Oil Sands Lease

Alberta Oil Sands Areas

Producing Thermal Project

Under Construction Thermal Project

May River - 46,720 contiguous acres of oil sands leases

Windell Rail Terminal

Cadotte - ~50,000 contiguous acres of oil sands leases

Thickwood Hills – 38,400 contiguous acres of oil sands leases

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Algar Lake Location and Regional Setting

From Nardin et al 2013 Isopach truncated at 40 m contour

McMurray-Wabiskaw Isopach

Project Area

T88

T87

T86

T85

T84

T83

T82

T81

R8W4 R10 R11 R12 R13 R14

Algar Lake

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Algar Lake Data Base

• Algar Lake Phase 1 McMurray Reserves • 114 mmbls 2P Reserves • 35 mmbls BE Contingent Resource

• GOS submitted a 11,300 bopd SAGD

development application in 2010

• Phase 1 to provide 6,000 bbls/d of long-term bitumen production

• 4x10 well pads in the development area

• Approval received in Nov 2011

• First steam achieved in January 2014 from the ARMS prototype plant

• Total of 48 wells in the model area (~1580 hectares)

• 3D seismic covers most of the model area

Grizzly May River OSL 3D Seismic

Model Area

Project Area

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ARMS SAGD Facility

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Algar Lake McMurray Formation Reservoir

• Algar Lake Reference Well AB/16-10-85-12W4

• Reservoir Characteristics - Excellent quality, multi-darcy

McMurray fluvial sands - Avg por = 33%, So = 80% - Net pay up to 22 m directly

overlying Devonian limestone - No associated bottom water or

gas - Capped by 40 m thick

Clearwater shale section

McMurray C Net Pay

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Algar Lake Stratigraphic Model

Sand Sand

Sand

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Algar Analogue - DPP

Abandonment

Inclined Fluvial Deposits

Sandy Base

S

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Modern Analogue – El Sira Point Bars, Peru

10km

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Wabiskaw

McMurray Fm Clast Associated Mudstones

McMurray Fm

Bioturbated Muddy IHS

Outcrop examples of McMurray IHS

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3D Seismic Interpretation

NW SE

• 3D Seismic tied to available well control • Major stratigraphic surfaces and differential compaction

within the McMurray can be resolved : Abandonment • Dipmeter data is required to determine the direction of

lateral accretion

Devonian

SE

NW

1-14 7-14 6-14

McMurray

Wabiskaw

Wabiskaw D

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Dipmeter Analysis 3-14-085-12

Pad B Devonian Structure with Dip Azimuth

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IHS revealed in the Injectors

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Dip Surface Map

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Variograms Analysis in IHS

• At a 400m well spacing,

you will have a

maximum of 2 data

points on a single lateral

accretion surface.

• Not enough for a good

variogram.

• Outcrop measurements

indicate that individual

facies bed lengths are

generally less than this.

• Need another way –

why not use outcrop

bed length statistics?

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Variogram Analysis in IHS

• Select major and minor variogram directions from field observations of mud bed length

• Often smaller in extent than could be calculated from well data

• Using a local varying azimuth function, orientation can be controlled on a curved surface

• Results in geomodels that resemble outcrops

Nardin et al 2013

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Core examples of the McMurray B lithofacies used in the Algar Lake geologic model.

Lithofacies

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McMurray Outcrop Vs Algar Model

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Algar Lake Facies Model

20

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PSD to Permeability

• As core expands with retrieval, complicating permeability and porosity

measurement, it would be useful to measure permeability from a

dilation independent variable

• Several equations available in the literature for calculating permeability

from PSD data

• Possible applications in the McMurray Formation?

d10

d50

d90

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r2=0.83 n=67

• d10 vs. horizontal permeability for Sand • Highest correlation coefficient from the d10 value • Best described by a complex polynomial curve

• d10 vs. horizontal permeability for Sand15 • d10 value provides the strongest correlation • Best described by a simple 2 degree polynomial

May River Calibration Dataset

r2=0.94 n=10

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• All previous trends can be combined in a nested “If” function

• Provides good results for the calibration dataset

• Occasional busts

• Promising initial results

• To be applied to Algar dataset for further evaluation and refinement

May River Calibration Dataset

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May River Calculated Perm Model

May River Porosity Perm Model

May River Grain Size Perm Model

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Conclusions

• It is important to realistically capture stratigraphic architecture

• Populate lithofacies into the stratigraphic architecture using

quantitative outcrop data

• Reservoir parameters keyed to this realistic lithofacies model, i.e.

permeability, gives a better representation of the reservoir

• There is a good relationship between permeability and the D10 of

the particle size distribution

• Investigation of PSD utility is ongoing

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References

Alberta Energy and Utilities Board, 2003, Athabasca Wabiskaw-McMurray regional geological study report 2003-A:

Calgary, Alberta Energy and Utilities Board, 187 p.

Deschamps, R., Guy, N., Preux, C., and Lerat, O., 2012, Analysis of Heavy Oil Recovery by Thermal EOR in a

Meander Belt: From Geological to Reservoir Modeling; Oil & Gas Science and Technology V 67, No. 6, p. 999-1018.

Hubbard, S. M., D. G. Smith, H. Nielsen, D. A. Leckie, M. Fustic, R. J. Spencer, and L. Bloom, 2011, Seismic

geomorphology and sedimentology of a tidally influenced river deposit, Lower Cretaceous Athabasca oil sands, Alberta,

Canada: AAPG Bulletin, v. 95, p. 1123–1145.

Jablonski, B.V.J., Process sedimentology and three-dimensional facies architecture of a fluvial dominated, tidally

influenced point bar: middle McMurray Formation, lower Steepbank River area, northeastern Alberta, Canada: Master’s

thesis, Department of Geological Sciences and Geological Engineering, Queen’s University, Kingston, Ontario, Canada,

356 p.

Nardin, T.R., Feldman, H.R., and Carter, B.J., 2013. Stratigraphic Architecture of a Large-Scale Point Bar Complex in

the McMurray Formation: Syncrude’s Mildred Lake Mine, Alberta, Canada. in F.J Hein et al (Eds.). Heavy-oil and Oil-

sand Petroleum Systems in Alberta and Beyond. AAPG Studies in Geology 64, p. 273-311.

Su, Y., Wang, J.Y. and Gates, I.D., 2013, SAGD well orientation in point bar oil sand deposit affects performance;

Engineering Geology 157, p. 79-92.

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Algar Horizontal Perm Model