Day 2 Pm - Probabilistic Evaluations

7/28/2019 Day 2 Pm - Probabilistic Evaluations

1/44

PROBABILISTIC RESERVE

ESTIMATIONS

DAY 2 AFTERNOON


2/44

WHY PROBABILISTIC EVALUATION

Volumetrically we can easily calculate

the OOIP/OGIP from the followingevaluation:

But we are uncertain about:

Gross volume, porosity, NTGR,

hydrocarbon saturation, drainage,recovery factor

Due to

+ Lack of data

+ Lack of confidence

+ Irreducible uncertainty

Especially true in exploration G&Gactivities (pre-drill studies) without wellcontrol or very limited data

grossHA

A

Hgross

NTG, PHI,

Sw, Boi

Gross bulk volume

Net bulk volume

Total Pore volume

Hydrocarbon volume

Hydrocarbon-in-place

NTGHA gross

grossHA

PHINTGHA gro ss

)1( wgr os s SPHINTGHA

oiwgross BSPHINTGHA /)1(

Probabilistic Reserve Evaluations2


3/44

DRILLING CERTAINTY/UNCERTAINTY

Do we know what it looks like underground?



4/44


A Porosity Map

But we do not know it is indeed

porosity

We do not know what range the

porosity has

Nor do we know what fills theseporous rocks

Nor do we know the structural

quality

Nor do we know the areal

quality of the rock



5/44


Therefore, we need to assess all possible scenarios in any pre-drill prospect, & more importantly, various probable scenarios

Explore full range of Knowns and Unknowns

Specify the known values for some variables

List all possible values of other variables

Perform sensitivity studies with the input matrix Understand the range of outcome

Such a process allows us to look at not just one single number(only if we are certain), but an array of possibilities witheducated assessment

Probabilistic Assessments

Use all values in calculations



6/44


Objectives of Probabilistic Methods Quantify range and distribution of hydrocarbon in-place due

to ranges of input parameters

Min (downside), Max (upside), Most likely

Assess key variables which contribute significantly touncertainty and appraisal process

Uncertain variables vs. consequent risks

Identify interventions to mitigate risks

Defend on downsides and exploit upsides

Evaluate reservoir development plans, production lifecycle

and capital investment profitability



7/44

COMMON PROBABILISTIC PRACTICE

Volumetric Assessment OOIP/OGIP

Monte Carlo simulation with distributional inputs

Acreage drainage

Pore volume

Net-to-gross ratio

Pay column Porosity

Hydrocarbon saturation

Fluid properties

Recovery factor

Performance/Analog Studies

Similar analogy field/pool/reservoir/formation/well performance

Regional analogy performance

IP rate, cum production, recovery factor, EUR



8/44

Select all possible ranges of input variables in volumetricequation

Calculate a full range of hydrocarbon in-place (HIP)

Low end, high end, mean/medium

Advantages

Quick and easy

Disadvantages

Slot-machine game

WHY PROBABILISTIC EVALUATIONS

p

HIP

low mean high



9/44

PROBABLISTIC EVALUATIONS

NTGR

PHI

A

Hgross

Boi

Hnet

Sw

p

p

OOIP

p: probability, or relative frequency



10/44

PROBABLISTIC EVALUATIONS: MODELS

Normal

Triangular

Uniform

Histogram

Lognormal

Bi-model



11/44

HOW TO USE EXCEL TO DO IT

MS Excel has numerous features that allow geoscientists andreservoir engineers to perform proper & reliable probabilistic

evaluations of oil/gas reserves/resources

Excel Data Analysis contains 19 applications:

Description Statistics Histogram

Random Number Generation & Rank & Percentile

Various math functions, macro & solver



12/44

HOW TO USE EXCEL TO DO IT

Descriptive Statistics

Historgram

Rank and Percentile

Regression



13/44

PROBABILISTIC DISTRIBUTIONS

Triangular Distribution

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

71 75 79 83 87 91 95 99 103

107

111

115

119

123

127

Net Pay, ft

Probability

Uniform Distribution

0.00

0.01

0.02

0.03

0.04

0.05

71

75

79

83

87

91

95

99

103

107

111

115

119

123

127

Net Pay, ft

Probability

Normal Distribution

0.00

0.02

0.04

0.06

0.08

0.10

71

75

79

83

87

91

95

99

103

107

111

115

119

123

127

Net Pay, ft

Pro

ba

bility

Lognormal Distribution

0

20

40

60

80

100

120

140

160

180

415

26

37

48

59

70

82

93

104

115

126

137

148

159

170

181

192

203

214

225

236

247

258

269

280

Net Pay, ft

P

robability

Bounded

Uniform

Triangular

Unbounded

Normal

Lognormal



14/44

PROBABILISTIC EVALUATION: ANALOGY

Open the excel file histogram petrophysical exercises.xls, perform descriptive analysis

and construct histogram of the field petrophysical parameters.



15/44

EXCEL HISTOGRAMPorosity vs. Core Permeability

0.01

0.1

1

10

0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19

Porosity

CorePermeability(md)

Core Permeability vs. Water Saturation

0.01

0.1

1

10

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Water Saturation

Permea

bility(md)

Porosity vs. Water Saturation

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20

Porosity

WaterSaturation

Regional Wells Porosity Distribution of Notikewin Target

0

10

20

30

40

50

60

70

0.075 0.082 0.088 0.095 0.101 0.108 0.114 0.121 0.128 0.134 0.141 0.147 0.154 0.160 0.167 0.173 0.200

Porosity

WellCounts

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%



16/44

MONTE CARLO EVALUATIONS

Monte Carlo simulation method basically generates many

possible outcomes from (almost) all the possibilities of the

input matrix. The greater the number of the simulation runs,

the more reliable of the outcome

Practically 400~500 runs on Excel spreadsheet are ok for the

basic Monte Carlo simulations

If you have a desktop computer from 2007-2008, you can generate 1000

runs in 5 minutes

Remember, the reliability of the results will not increase dramatically.

According to the centre limit theorem, the accuracy of the result is:

N

1



17/44

DISTRIBUTION ANALYSIS PROCEDURES

You have to start from somewhere

Past experience

Analog data

You can generate theoretical distribution by selecting a

distribution type and/or setting a range for each parameter

understanding of geology, geophysics, petrophysics, reservoir concepts

is necessary:

You do not allocate the reservoir pressure range at [14.7, 5000] psi, unless

you are convinced the pool is possibly depletedso your lower bound does

not make sense

Find and ensure the range and the distribution make sense



18/44

DISTRIBUTION ANALYSIS PROCEDURES3050

3051

3052

3053

3054

3055

3056

3057

3058

3059

3060

3061

3062

3063

3064

3065

3066

3067

3068

3069

3070

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Porosity

MeasuredDepth(m)

3057.7 m

3069.3 m

H=11.6 m

3060

3061

3062

3063

3064

3065

3066

3067

3068

3069

3070

3071

0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16

Porosity (fraction)

Depth(m)

0

5

10

15

20

25

30

35

40

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20

Porosity

Frequency

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

CumulativeProbability

Frequency

Cumulative %

0

100

200

300

400

500

600

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20

Porosity

Frequency

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Frequency

Cumulative %

composite N/D porosity log

verified by core analysis

The displayed porositydistribution of the maininterval

The displayed porositydistribution for all thegas column from top to

base



19/44

19

Input

Bulk Rock Volume lognormal distribution

Drainage Area lognormal

Gross Pay normal or lognormal

Petrophysics normal distribution

Porosity normal

Water Saturation normal

NTGR normal

FVF (Bo or Bg) normal

Recovery Factor generally normal but complicated Drive mechanism

Infill drilling / downspacing

PROBABILISTIC EVALUATIONS



20/44

MONTE CARLO SIMULATION RUNS



21/44

HOW TO READ THE RESULTS

Mean

Mean

1.064

1.064

2.527

2.527

0.474

0.474

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00

Raw Recoverable Reserve (bcf)

Probability(%)



22/44

PROBABLISTIC EVALUATIONS

PROVED

Min. Max.P90

Median P50

P10Mode Mean

Reserves

Relative

Frequ

ency

PROVED +PROBABLE +

POSSIBLE

PROVED +PROBABLE

Upside Potential



23/44

PROBABILITY

The extent to which an event is likely to occur, expressed as a ratio of the

number of favourable cases to the total number of cases

BEST ESTIMATE

A general term with no definitive statistical meaning

When a single discreet value with no optimism or conservatism is used thisrepresents the expected outcome

It may often be considered to be the mean.

In deterministic usage, it may be the mean, median, or mode (or some other

value).

Widely used and meant to represent the Proved Plus Probable reserves

CONFIDENCE OR CONFIDENCE LEVEL

The qualitative degree of certainty associated with an estimate

UNCERTAINTY AND STATISTICAL CONCEPTS



24/44


MEAN

Synonymous with expected value

Arithmetic mean MEDIAN

The value for which there is an equal probability that the outcome will be higher

or lower

The definition of Proved Plus Probable corresponds with the statistical median

MODE

Synonymous with most likely

In statistics, the mode is the value that occurs most frequently Avoid the use of this term, not particularly useful in reserves estimationPete

Rose MOST LIKELY

Synonymous with the mode



25/44

UNCERTAINTY-BASED RESERVES ESTIMATES

A discrete value for each parameter is selected based on the evaluators

determination of the value that is most appropriate for the reserves

category

The resulting range of estimates prepared for the various reserves

categories reflects the associated degree of uncertainty Proved (1p) = high degree of confidence

Proved plus Probable (2p)= best estimate

Proved plus Probable plus Possible (3p) = Upside Case

This is a scenario based approach to deterministic reserves

Most commonly used internationally




26/44


MINIMUM, BEST ESTIMATE AND MAXIMUM VALUES USING DETERMINISTIC

METHODS

REMINDER:

The use of most conservative parameters for proved will result in unrealistically low

estimates

Aggregating them results in even further conservatism

Conversely, use of most optimistic parameters for Proved plus Probable plus Possible

will result in unrealistically high estimates

In general, when reserves are estimated as a product of several

parameters, BEST ESTIMATE (neither conservative or optimistic),

should first be determined for all parameters

Appropriate constraints should then be imposed (i.e. LKH, or drainage)

1 or 2 of the key parameters may be varied from the BEST ESTIMATE as

appropriate.



27/44


DETERMINE BEST ESTIMATE AS PROVED PLUS PROBABLE (2p)

Determine practical minimum and practical maximum that brackets the

quantities the evaluator believes with high confidence (P90 and P10)

The above order is unimportant is left to the particular evaluator

The proved estimate should generally lie in the range of 1/3 to 2/3 of the

difference between the Proved plus Probable estimate and the minimum The Proved plus Probable plus Possible estimate should generally lie in

the range of 1/3 to 2/3 of the difference between the Proved plus

Probable estimate and the maximum



28/44

28

ORMEN LANGE VOLUMETRICS

Pressure 4263 psia

Depth 2750 m

Temp 62.8 C

145.04 F

Acre 302 million m2

Gross Pay 36.3 m

NTGR 0.909

Phi 0.281

Sg 0.704

Bg 266

RF 0.7

V= 1971.317 mm m3

Gas-in-plac 18609901 mm scf

Reserve= 13026931 mmcf

13026.93 bcf

13.0 tcf

Class Exercise:

Use the above reservoir parametersas the mean values and performprobabilistic estimates of IGIP &Reserves



29/44

DETERMINISTIC VS. PROBABILISTIC

6-28-2

9-10

4-14

2-11

8-912-10

6-35

14-36

13-11

6-28-2

9-10

4-14

2-11

8-912-10

6-35

14-36

13-11

RESOURCE/RESERVE ESTIMATES

Volumetric MatrixNet Pay: 12.4 m

Porosity: 10.4%

Sw: 49.6%

Pressure: 8.3 MPa (1200 psi)

Bg: 72 scf/rescf

RF: 75%

Drainage: ~ 1/2 sect. (160 ~ 320 acres)

OGIP: 1.1 ~ 2.2 bcf

Reserves:Analogy/Probabilistic Estimates

Net Pay: 4 ~ 18 m

Porosity: 8.6% ~ 13.2%

Sw: 32% ~ 67%

Pressure: 1100 ~ 1650 psi

Bg: 65 ~ 100 scf/rescf

Drainage: ~ sect. (160 ~ 480 acres)

Reserves P50:

Production Forecast

IP rate: 500 mcf/d

Abandon rate: 50 mcf/d

Decline: hyperbolic (n=0.5)

Annual decline: 7% (final); 19% (initial)

Permeability: 0.19 ~ 0. 35 md

Shrinkage:


30/44

PROBABILISTIC EXAMPLE

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

Jun-1994 Oct-1995 Mar-1997 Jul-1998 Dec-1999 Apr-2001 Sep-2002 Jan-2004 May-2005 Oct-2006 Feb-2008 Jul-2009

Date

GasRate(mcfd)

13-11 Commingled

8-2 NTKN

6-35 Comingled

2-11 NTKN

9-10 NTKN12-10 NTKN

14-36 Commingled

4-14 NTKN

8-2

13-11

4-14 6-35

14-36

2-11

9-10

12-10

0

200

400

600

800

1,000

1,200

1,400

Jun-1994 Oct-1995 Mar-1997 Jul-1998 Dec-1999 Apr-2001 Sep-2002 Jan-2004 May-2005 Oct-2006 Feb-2008 Jul-2009

Date

GasRate(mcfd

)

8-2 NTKN

2-11 NTKN

9-10 NTKN

12-10 NTKN

4-14 NTKN

8-2

12-10

9-10

4-14

2-11

0

200

400

600

800

1000

1200

1400

1600

1800

3 1-Ja n-19 93 2 8-Oc t-19 95 2 4-Ju l- 19 98 1 9-Ap r-20 01 1 4-Ja n-20 04 1 0-Oc t-20 06 6 -Jul -2 00 9

DATE

DATUMPRESSURES(psia)

13-11 Commingled

8-2 NTKN

6-35 Commingled

2-11 NTKN

9-10 NTKN4-14 NTKN

8-2

13-11

6-35

2-11

9-10

4-14

NTKN Gas C1 C2 C3

9-10 8 4. 94 7 .8 4 3. 35

8 7. 59 7 .4 7 2. 52

8 4. 97 7 .8 2 3. 57

4-14 83.05 7.6 2.84

8 6. 1 7 .7 8 3. 12

13-11 8 5. 55 7 .9 4 3. 21

8 5. 59 7 .7 3 3. 18

8 6. 31 7 .9 1 3. 03

8 8. 39 5 .6 5 3. 26

8-2 8 5. 87 7 .9 3 3. 01

2-11 8 4. 73 7 .9 7 3. 22

6-35 8 6. 08 7 .7 0 3. 22

Average= 8 5. 76 7 .6 1 3. 13

Co n d itio n s Res u lt s

Temp. Pressure Z Factor P/Z Density Cg Bg Bg Viscosity

F psia psia g /c c 1 /p si * 1 E6 bbl/MSCF SCF/cu ft cp

161 1800 0.851 2116.1 0.096 603.0 1.478 120.5 0.0158

161 1700 0.855 1988.4 0.090 642.6 1.573 113.3 0.0154

161 1600 0.860 1860.7 0.084 686.0 1.681 106.0 0.0151

161 1500 0.865 1733.2 0.079 733.9 1.804 98.7 0.0148

161 1400 0.872 1606.3 0.073 787.4 1.947 91.5 0.0145

161 1300 0.878 1480.3 0.067 847.7 2.112 84.3 0.0142

161 1200 0.885 1355.4 0.062 916.8 2.307 77.2 0.0139161 1100 0.893 1231.9 0.056 997.0 2.538 70.2 0.0137

161 1000 0.901 1109.9 0.050 1091.9 2.817 63.2 0.0135

161 900 0.909 989.6 0.045 1206.6 3.160 56.4 0.0133

161 800 0.918 871.1 0.040 1348.6 3.590 49.6 0.0131

161 600 0.937 640.2 0.029 1770.3 4.884 36.5 0.0128

161 500 0.947 528.0 0.024 2105.6 5.922 30.1 0.0127

161 400 0.957 417.9 0.019 2607.2 7.482 23.8 0.0126

161 1630 0.858 1899.0 0.086 672.6 1.647 108.2 0.0152

161 300 0.968 310.1 0.014 3441.9 10.084 17.7 0.0125

161 200 0.978 204.5 0.009 5109.6 15.293 11.6 0.0124

161 100 0.989 101.1 0.005 10110.5 30.924 5.8 0.0123

161 14.7 0.998 14.7 0.001 68137.8 212.367 0.8 0.0123

Upside Most likely Risk



31/44

Brazeau River Nisku A PoolRecovery Options & STOIIP


32/44

West Pembina Brazeau River Nisku A Pool

wabamungroup

winterburngroup

beaverhill

lake group

woodbendgroup



33/44




34/44


Nisku A Pool

Original OOIP Estimate:33.34 mmbblYE 2009 Cum Oil Volume:27.16 mmbblRecovery Factor: 82%

Original GOR1000 scf/bblOSGIP based on GOR33.34 bcf

2009 YE Cum Gas Volume:122.55 bcfCycled Gas Volume:82.08 bcfNet Gas Production:40.46 bcf

The Cum Gas deficit40.46 33.34 = 7.12 bcf(if assume little remaininggas is remaining today)

PHH modeling studysuggested in 2007:OOIP = 40.8 mmbbl(reached a good historymatch with the corrected oilcompressibility for theunder-saturated oil case;PHH did not complete thefinal history match work)

Recovery Factor: 67%

Nisku A Pool History

Discovered in 1977

Original Pressure46,581 kPaReservoir Temperature102 oCGas Cycling Soak-Pressure37,500 kPaCurrent Pool Pressure900 kPa

Wells:100/5-6-49-12W5 (injector)100/15-31-48-12W5100/11-31-48-12W5102/11-31-48-12W5 HZ SUSP.

Primary DrainageJan 1978 ~ March 1980P res. at 1980 = 20 mPa

Dry Gas Cycling FloodingInjection Began: Sept 1980

Injector: 5-6-49-12W5 (topstructure)Injection Stopped: Aug 1995Total Injection Gas: 80.08 bcf

Oil Pbubble = 21 mPaMiscible Flood OperatingPressures: 37 mPa

Oil API Gravity: 45 oAPISweet gas

7-31

11-31

(300 m)



35/44

West Pembina Brazeau River Nisku A PoolBrazeau River Nisku "A" Pool Production

0

1

10

100

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95 Jul-98 Apr-01 Jan-04 Oct-06 Jul-09 Apr-12

Year

GasRate(mmscf/d)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

CondyOilRate(bbl/d)

11-31

5-6

5-6 dry gas injection; 82 bcf

11-31 HZ online

jan 1991

15-31

drilled

Brazeau River Nisku "A" Pool Pressure History

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95 Jul-98 Apr-01 Jan-04 Oct-06 Jul-09 Apr-12

Year

Poo

Presures

(psia)

15-31

5-6

11-31

Series4

5-6 dry gas injection; 82 bcfPi = 45 MPa

Pcycling = 38 MPa

primary

production

final

depletionPbubble = 21 MPa

Brazeau River Nisku "A" Pool GOR Trend

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

8/28/76 5/25/79 2/18/82 11/14/84 8/11/87 5/7/90 1/31/93 10/28/95 7/24/98 4/19/01 1/14/04 10/10/06 7/6/09 4/1/12

Date

GOR(scfd/bbl)

11-31 HZ

5-615-31

11-31 02

5-6 injector 82.08 bcf

Initial Gas SolubilityProduction GOR

Reservoir Engineering Highlights

It is very probable that A pool has 40.8 mmbbl oil, 7.5 mmbblmore than the historical estimates on the book The higher OOIP is supported by the original GOR 1000 scf/bbl,the early pressure history data, and the PHH study based on thecorrection of the oil compressibility (undersaturated reservoirduring its primary production, and the cum gas volume (40 bcf) Areal/volumetric swept efficiency is the most challenginguncertainty to implement future enhanced oil recovery operation;the current well pattern/spacing, the 15-y high pressure injectionplus the subsequent years depletion drive, have swept mostsweepable oil; any new EOR scheme of less degrees is likely notto produce any significant amount of oil A substantial amount of cycling gas is required to raise the poolpressure level to 38 MPa in order to reach the miscible pressurecondition toward better miscible flooding



36/44

Probabilistic Reserve Evaluations



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95

Year

PooPresures(psia)

15-31

5-6

11-31

11-31 02


Pcycling = 38 MPa

primary

production

final

depletion

Pbubble = 21 MPa

7-31

5-6injector

11-31producer

15-31producer

7-31 HZproducer

GOC

gas coning

Probabilistic36


37/44


To evaluate gas storage project prospect, BPhired PHH to build a numerical model &

history match the performance (2008)

In order to make up the cum gas deficit, PHH

had to add an invisible cache vaguely

attached to the A pool, which contained

40 bcf of gas slowly leaking into the pool

over 15 years

In the end, they found that they paid too

much attention to the gas cycling part of the

history, and ignored the early production,

which gives the correct oil compressibility

during the primary depletion drive

Like in PTA analysis, compressibility terms

are often ignored and many times it makes a

big difference

7-31

Nisku A Pool

Original OOIP Estimate:33.34 mmbblYE 2009 Cum Oil Volume:27.16 mmbblRecovery Factor: 82%

Original GOR1000 scf/bblOSGIP based on GOR33.34 bcf

2009 YE Cum Gas Volume:122.55 bcfCycled Gas Volume:82.08 bcfNet Gas Production:40.46 bcf

The Cum Gas deficit40.46 33.34 = 7.12 bcf(if assume little remaininggas is remaining today)

PHH modeling studysuggested in 2007:OOIP = 40.8 mmbbl(reached a good historymatch with the corrected oilcompressibility for theunder-saturated oil case;PHH did not complete thefinal history match work)

Recovery Factor: 67%



38/44

Probabilistic Reserve Evaluations


(1 )

w wi f p o o oi oi

wi

c S cN B N B B NB p

S

(1 )

o oi w wi f p o oi

oi wi

B B c S cN B NB p

B S

o oio

oi

B Bc

B p

(1 )w wi f p o oi o

wi

c S cN B NB c pS

(1 )

o o w wi f p o oi

wi

c S c S cN B NB p

S

p o oi eN B NB c p

o oi eV V c p

p oie

o

N BRF c p

N B

Undersaturated Oil Reservoirs

Probabilistic38


39/44


0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95

Year

PooPresures

(psia)

15-31

5-6

11-31

11-31 02


Pcycling = 38 MPa

primary

production

inal

depletion

Pbubble = 21 MPa


Muhammad Ali Al-Marhoungas specific gravity = 0.652

a1 = -14.1042 Pi= 112,000 kPa 16244.1 psia surface oil relative density = 0.850

a2 = 2.7314 P bubble = 20,995 kPa 3045.0 psia relative oil density at Pb = 0.668

a3 = -5.60605E-05 T = 110oC 230

oF original GOR = 240 m3/m3a4 = -580.8778 oil FVF at Pb = 1.560 resm3/m3

Vasquez and Beggs

O ri gi nal M id dl e E ast

a1 = -1.43300E-02 0.0023386

a2 = 5.00000E-05 3.69769E-05

a3 = 1.72000E-04 5.53945E-05 Al-Marhoun Result Vasquez & Beggs Resulta4 = -1.18000E-02 -0.0081716

a5 = 1.26100E-04 5.82514E-05 ln (Co) = -13.34122171

Oil Compressibility Co = 1.6069E-06 1/psi Oil Compressibility Co = 8.9806E-06 1/psi

Poros i ty Nisku "A"

Nisku Water Salinity 11% Pressures Vasquez&Beggs Al-Marhoun T ot al S w i= 10 %, S o =9 0%

200,000 ppm 1000 ppm Cr (1/psi) (psia) (1/psia) (1/psia) Compress ibi l i ty

Co ln(Co) Co V&B Al-M C o/C t C r/C t

2.08204E-06 2.91220E-06 4.66745E-06 6780.9 1.3174E-05 -11.559 9.5521E-06 1.68151E-05 1.35556E-05 70.47% 34.43%

2.08321E-06 2.91385E-06 4.66745E-06 6757.9 1.3219E-05 -11.554 9.5936E-06 1.68556E-05 1.35931E-05 70.58% 34.34%

2.08582E-06 2.91749E-06 4.66745E-06 6706.9 1.3319E-05 -11.545 9.6862E-06 1.69465E-05 1.36768E-05 70.82% 34.13%

2.09664E-06 2.93263E-06 4.66745E-06 6494.9 1.3754E-05 -11.505 1.0081E-05 1.73393E-05 1.40335E-05 71.83% 33.26%

2.09679E-06 2.93284E-06 4.66745E-06 6491.9 1.3760E-05 -11.504 1.0087E-05 1.73450E-05 1.40386E-05 71.85% 33.25%

2.10154E-06 2.93948E-06 4.66745E-06 6399.0 1.3960E-05 -11.487 1.0265E-05 1.75255E-05 1.41995E-05 72.29% 32.87%

2.10172E-06 2.93973E-06 4.66745E-06 6395.4 1.3968E-05 -11.486 1.0272E-05 1.75326E-05 1.42058E-05 72.31% 32.86%

2.10249E-06 2.94081E-06 4.66745E-06 6380.3 1.4001E-05 -11.483 1.0301E-05 1.75624E-05 1.42322E-05 72.38% 32.79%

2.11071E-06 2.95230E-06 4.66745E-06 6219.4 1.4363E-05 -11.453 1.0618E-05 1.78896E-05 1.45187E-05 73.13% 32.15%

2.12057E-06 2.96609E-06 4.66745E-06 6026.3 1.4823E-05 -11.417 1.1011E-05 1.83052E-05 1.48740E-05 74.03% 31.38%

2.12151E-06 2.96742E-06 4.66745E-06 6007.8 1.4869E-05 -11.413 1.1049E-05 1.83464E-05 1.49087E-05 74.11% 31.31%

2.12243E-06 2.96870E-06 4.66745E-06 5989.8 1.4914E-05 -11.410 1.1087E-05 1.83867E-05 1.49426E-05 74.20% 31.24%

2.12592E-06 2.97358E-06 4.66745E-06 5921.5 1.5086E-05 -11.397 1.1231E-05 1.85420E-05 1.50723E-05 74.51% 30.97%

2.12608E-06 2.97380E-06 4.66745E-06 5918.4 1.5094E-05 -11.396 1.1237E-05 1.85491E-05 1.50782E-05 74.53% 30.95%

2.12721E-06 2.97538E-06 4.66745E-06 5896.3 1.5150E-05 -11.392 1.1284E-05 1.86002E-05 1.51206E-05 74.63% 30.87%

2.12868E-06 2.97744E-06 4.66745E-06 5867.5 1.5225E-05 -11.387 1.1345E-05 1.86674E-05 1.51760E-05 74.76% 30.76%

2.13106E-06 2.98077E-06 4.66745E-06 5820.8 1.5347E-05 -11.378 1.1446E-05 1.87776E-05 1.52666E-05 74.97% 30.57%

2.13464E-06 2.98578E-06 4.66745E-06 5750.6 1.5534E-05 -11.365 1.1598E-05 1.89467E-05 1.54042E-05 75.29% 30.30%

2.13522E-06 2.98659E-06 4.66745E-06 5739.3 1.5565E-05 -11.363 1.1623E-05 1.89743E-05 1.54265E-05 75.34% 30.26%

2.18121E-06 3.05091E-06 4.66745E-06 4838.7 1.8462E-05 -11.193 1.3771E-05 2.15880E-05 1.73668E-05 79.30% 26.88%

2.20877E-06 3.08946E-06 4.66745E-06 4298.9 2.0780E-05 -11.091 1.5245E-05 2.36783E-05 1.86971E-05 81.54% 24.96%

2.21645E-06 3.10021E-06 4.66745E-06 4148.4 2.1534E-05 -11.063 1.5684E-05 2.43578E-05 1.90927E-05 82.14% 24.45%

2.21648E-06 3.10025E-06 4.66745E-06 4147.8 2.1537E-05 -11.063 1.5685E-05 2.43606E-05 1.90943E-05 82.15% 24.44%

2.21741E-06 3.10155E-06 4.66745E-06 4129.7 2.1631E-05 -11.059 1.5739E-05 2.44457E-05 1.91427E-05 82.22% 24.38%

2.21782E-06 3.10212E-06 4.66745E-06 4121.7 2.1673E-05 -11.058 1.5763E-05 2.44836E-05 1.91641E-05 82.25% 24.36%

2.21909E-06 3.10390E-06 4.66745E-06 4096.7 2.1805E-05 -11.053 1.5837E-05 2.46028E-05 1.92312E-05 82.35% 24.27%

2.21939E-06 3.10432E-06 4.66745E-06 4090.9 2.1836E-05 -11.052 1.5854E-05 2.46306E-05 1.92469E-05 82.37% 24.25%2.23764E-06 3.12984E-06 4.66745E-06 3733.5 2.3927E-05 -10.985 1.6958E-05 2.65145E-05 2.02431E-05 83.77% 23.06%

2.24609E-06 3.14166E-06 4.66745E-06 3568.0 2.5037E-05 -10.954 1.7495E-05 2.75145E-05 2.07275E-05 84.41% 22.52%



40/44

Nisku "A" Pool Total Compressibility Estimates

0.0E+00

5.0E-06

1.0E-05

1.5E-05

2.0E-05

2.5E-05

3.0E-05

3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 7,000

Pool Pressures (psia)

Oil&TotalCompressibilities(1/ps

ia)

Vasquez&Beggs

Total Compressibility (V&B)


gas specific gravity = 0.652

Pi = 46,439 kPa 6735.4 psia surface oil relative density = 0.807 43.78 oAPI

P bubble = 20,995 kPa 3045.0 psia relative oil density at Pb = 0.609

T = 103oC 217

oF original GOR = 178 m3/m3 1000 scf/bbl

oil FVF at Pb = 1.560 resm3/m3 1.560 resb/stb

Brazeau River Nisku "A" Pool Cum Oil Match

0.0

0.5

1.0

1.5

2.0

2.5

Oct-77 Jan-78 Apr-78 Jul-78 Nov-78 Feb-79 May-79 Sep-79 Dec-79 Mar-80 Jun-80 Oct-80

year

cumoil(mmbbl)&cumgas(bcf)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

averagepoolpressure(psia)

Cum Oi (actual)l

Cum Gas (actual)

Cum Oil Estimates (40.8 mmbbl)

Cum Oil Estimates (33.3 mmbbl)

Pool Pressures History

40.8 mmbbl

33.3 mmbbl

pool pressure history

The most popular Vasquez&Beggs correlation is used to estimate

Nisku A oil compressibility & the total compressibility, which is

then used to estimate the cum oil production for each step of the

pools pressure decline. 40 mmbbl OOIP seems to be a better

match with the actual production. Al-Marhoun correlation seems

to over-estimate the oil production.

Nisku rock compressibility remains the least known input, which

makes 20~30% of the total compressibility. It is estimated by the

correlation developed in SPE 88464.



41/44

Brazeau River Nisku "A" Pool Production

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95 Jul-98 Apr-01 Jan-04 Oct-06 Jul-09 Apr-12 Dec-14

Year

OilRate(bblf/d)

0

2

4

6

8

10

12

14

16

18

CumO

il(mmbbl)

5-6 Oil Rate

11-31 Oil Rate

15-31 Oil Rate

11-31 HZ Oil Rate

5-6 Cum Oil

11-31 Cum Oil

15-31 Cum Oil

11-31 HZ Cum Oil

11-31

11-31 HZ

15-31

16.75 mmbbl

7.66 mmbbl

1.75 mmbbl

1.00 mmbbl

4 wells combined

27.16 mmbbl

5-6

gas injection ended

blowdown began


Cum Oil at Aug 1995 = 25.56 mmbbl

oil incremental between Aug 95 & Dec 09 = 1.6 mmbbl



42/44

Brazeau River Nisku "A" Pool Production

1

10

100

1,000

10,000

Aug-76 May-79 Feb-82 Nov-84 Aug-87 May-90 Jan-93 Oct-95 Jul-98 Apr-01 Jan-04 Oct-06 Jul-09 Apr-12 Dec-14

Year

OilRate(bblf/d)

0

2

4

6

8

10

12

14

16

18

CumO

il(mmbbl)

11-31 HZ

11-31: 16.75 mmbbl

11-31 HZ: 1.75 mmbbl

11-31gas injection ended

blowdown began


Nisku "A" Pool Performa nce betwee n 11-31 and 11-31 HZ

1

10

100

1000

10000

May-90 Sep-91 Jan-93 Jun-94 Oct-95 Mar-97 Jul-98 Dec-99 Apr-01 Sep-02 Jan-04 May-05 Oct-06

Year

OilRateDifferential(bbl/day)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

IncrementalCumOil(mmbb

Rate Differencel

Cum Incremental

injection ended;blowdown began

0.75 mmbbl0.94 mmbbl

If we assume 15-31 was not affected

The net incremental oil production fromdrilling 11-31 horizontal well seems to bemuch less than the projected/recorded 1.75mmbbl oil due to the competitive drainage

with the original 11-31 vertical well. The netcum oil incremental was most likely less than0.84 mmbbl, or 2% additional recovery ofthe total OOIP (40.8 mmbbl)



43/44

West Pembina Brazeau River Nisku A PoolBrazeau River Nisku "A" Pool

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Cum Oil Production (mmbbl)

OilRate(bbl/d)

11-31

11-31 HZ

15-31

5-6

Nisku "A" Pool

he entire pool

25.558 mmbbl

before blowdown

11-31 well

16.419 mmbbl

before blowdown

15-31 well

7.209 mmbbl

before blowdown

11-31 HZ well caused 15-31/11-31 production loss



44/44


2010

Depleted pressures

Wells are dying

1~2 bcf remaining gas

Remaining bbl oils

Options Decommision the pool

Convert to gas storage

Re-initiate gas cycling

Partners wanted to do both

storage/EOR

Questions?

STOIIP, RF, & remaining for EOR Gas storage alone?

Day 2 Pm - Probabilistic Evaluations

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