production allocation[1]

8/6/2019 Production Allocation[1]

1/39

Canada

United States

Norway

United Kingdom

Kazakhstan

Brazil

Mexico

Trinidad

Venezuela

Kuwait

Libya

Oman

Saudi Arabia

United Arab Emirates

Australia

India

Malaysia

Thailand

New Zealand

For contact information, please visit our website: www.weather fordlabs.com

Geoc hem ic a l Al loc a t ion o f

Com m ing led Produc t ion

Mark A. McCaffrey, Ph.D.

Houston, TX, October 19, 2010


2/39

2009 Weatherford Laboratories. All rights reserved.

Out l ine

Introduction

Examples

Mechanics of Method


3/39


Geoc hemic a l A l loc a t ion o f Comm ing led Product ion

Premise: Naturally occurring geochemicaldifferences can be used to distinguish oils (orgases) from discrete reservoirs.

These geochemical differences can serve asnatural tracers for the contribution of each

reservoir to commingled production from a groupof reservoirs.


4/39


Why do Oi ls f r om Separat e Reser voi rs have

Di f ferent Fingerpr in t s?

Even if oils in separate reservoirs have the same source, those oils

will not have been generated at precisely the same maturity or fromprecisely the same facies.

As a given piece of source rock matures, the oil it generatescontinually changes, imparting differences to oils in separatecompartments.

Which interval (source facies) is generating also changes throughtime.

Because discrete compartments differ in size and location, theynecessarily have slightly different filling histories.

Inter-compartment differences in post-migration processes (waterwashing, biodegradation, fractional evaporation, etc.) createunique compositions.

Two oils can be 99% similar, and still have 50 compositionaldifferences, and each one of those differences can serve as anatural tracer. for that oil.


5/39


Tw o Pr imary Advant ages of Geochem ica l

Produc t ion A l loc at ion vs. Produc t ion Logging

I - Less expensive than production logging $600-$1,800/ geochemical allocation vs. >$60,000 for PLT

Does not interrupt production

More practical for long term monitoring

II - Can be used in cases where production loggingcannot

Can be used even on pumping wells

Deviation of well is not an issue

Rapid technique

Requirements:

Samples of the end member oils


6/39


Mot ivat ion for A lloc at ion of Com m ingled Produc t ion

Quantify Zone Contributions for RoyaltyCalculations or Regulatory Requirements

Monitor Effects of MBEs

Test if IsoSleeves are Set

Control Water Production

Monitor Effects of Water Injectors

Optimize Production From Multilaterals

Identify Sanded Out Intervals for FCO

Identify Competition Between Laterals

Monitor Effect of Initiation of Gas Lift


7/39 2009 Weatherford Laboratories. All rights reserved.

Ex am ple: NK -43 Compar ison of Geochem ic a l

A l locat ion Resul ts w i t h PLT resu l t s

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

10/25/2005 2/2/2006 5/13/2006 8/21/2006 11/29/2006 3/9/2007 6/17/2007

NK-43 Sag vs NOP Oil Splits

Sag Geochem NOP Geochem Sag PLT NOP PLT



Ex ample : Geochem ic a l A lloca t ion More Acc ura te

t han PLTs

1J-166 Production Allocation Results

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

4/3/2006

6/3/2006

8/3/2006

10/3/2006

12/3/2006

2/3/2007

4/3/2007

6/3/2007

8/3/2007

10/3/2007

12/3/2007

2/3/2008

4/3/2008

6/3/2008

8/3/2008

10/3/2008

12/3/2008

2/3/2009

4/3/2009

6/3/2009

8/3/2009

10/3/2009

Date

Wt%

Sand 1

Sand 2

Sand 3

B-IsoSleeve Installed

7/25/-8/18/08

PLT

10/10/08

B IsoSleeve Removed

9/20/09

Viscous Oil Well Example #2


9/39



Ex am ple: Moni t or ing Wat er Floods

1E-121 Production Allocation Results

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Date

Wt%

Sand 2 Water Injection

Shut in 6/6/06

19.8

Viscous Oil Well Example #1

Sand 2

Sand 317.9



0

10

20

30

40

50

60

70

80

90

100

01/01/03 07/02/03 12/31/03 06/30/04 12/29/04 06/29/05 12/28/05

Date

Percentage

Increased production due to

support from new injector

Ex am ple: Moni t or ing Wat er Floods



0

10

20

30

40

50

60

70

80

90

100

01/01/05 01/21/05 02/10/05 03/02/05 03/22/05 04/11/05 05/01/05 05/21/05 06/10/05 06/30/05

Date

Percentage

Increased contribution due to inappropriate

production conditions for 1 of the 3 laterals

Ex am ple: Diagnosing Prob lem s w i th Mul t i la ter a ls



D kL/

B kL/

A2 kL/

1E-168 Production Allocation Results

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Dec-0

4

Mar-0

5

Jun-0

5

Sep-05

Dec-0

5

Mar-0

6

Jun-0

6

Sep-06

Dec-0

6

Mar-07

Jun-0

7

Sep-07

Dec-07

Mar-0

8

Jun-0

8

Sep-08

Dec-0

8

Mar-0

9

Jun-0

9

Sep-09

Dec-0

9

Mar-1

0Date

Wt%

15.0

16.0

17.0

18.0

19.0

20.0

21.0

22.0

23.0

API

Sand A

Sand B

Sand D

API

Discussion Geochem solution dismissed

when it continued to show B

contribution after isoSleeve

Now determined IsoSleevedid not set

B IsoSleeve9/07/07

MBE3/22/06

Ex ample : Iden t i f y ing w hen IsoSleeve not set

IsoSleeve not effective, B Primary Decline



Calcu la t ed A l loc a t ion Resu lt s Com pared t o Ac t ua l

Com posi t ions for Ar t i f i c ia l Mix t ures o f Oi ls or GasesCa lc ul ated Ac tua l c ompos iti on of Di ffer ence between Geochemi ca l

Number Type Allocation Artifical Mixutre Calculated and Parameters Blind

Location of Zones Result Prepared by Laboratory Actual Composition Used Test?

Well NK-43 2 Oil 13.4% / 86.6% 15.0% / 85.0% 1.6% 48 Yes

Well NK-43 2 Oil 47.5% / 52.5% 50.1% / 49.9% 2.6% 48 YesWell NK-43 2 Oil 78.9% / 21.1% 79.9% / 20.1% 1.0% 48 Yes

Well S-26 2 Oil 68.8% / 31.2% 75.0% / 25.0% 6.20% 132 Yes

Well S-26 2 Oil 46.1% / 53.9% 50.0% / 50.0% 3.90% 132 Yes

Well S-26 2 Oil 20.9% / 79.1% 25.0 % / 75.0% 4.10% 132 Yes

Undisclosed Alaska A 2 Oil 65.1% / 34.9% 66.5% / 33.5% 1.4% 209 Yes

Undisclosed Alaska A 2 Oil 87.1% / 12.9% 87.85% / 12.15% 0.75% 209 Yes

Undisclosed 0140 2 Oil 48.0% / 52.0% 50.1% / 49.9% 2.1% 40 Yes


Undisclosed 0140 2 Oil 50.5 %/ 49.5% 49.9% / 50.1% 0.6% 40 Yes


Undisclosed 1053 2 Oil 59.9% / 40.1% 59.6% / 40.4% 0.3% 171 YesUndisclosed 1053 2 Oil 87.2% / 12.8% 86.4% / 13.2% 0.8% 171 Yes




Average error of allocation of 2-zone artifical mixtures of oils in this table: 1.8%

Undisclosed 1100 2 Gas 50.6% / 49.4% 50.0% / 50.0% 0.6% 8 No

Undisclosed 08834 3 Oil 60.2% / 39.8% / 0% 64.5% / 35.5% / 0% 4.3% / 4.3% / 0% 158 Yes

Undisclosed 08834 3 Oil 33.5% / 46.7% / 19.8% 39.1% / 40.9% / 20.0% 5.6% / 5.8% / 0.2% 158 Yes


Undisclosed 08692 3 Oil 12.9% / 17.2% / 69.9% 10.8% / 19.7 % / 69.5% 2.1% / 2.5% / 0.4% 93 Yes

Undisclosed 0140 3 Oil 10.0% / 31.0% / 59.0% 15.0% / 29.9% / 55.1% 5.0% / 1.1% / 3.9% 40 YesUndisclosed 0140 3 Oil 54.0 %/ 15.0 %/ 31.0% 55.0% / 15.1% / 29.9% 1.0% / 0.1% / 1.1% 40 Yes


Undisclosed 48345 3 Oil 20.1% / 22.2% / 57.7% 19.6% / 20.4% / 60.0 % 0.5% / 1.8% / 2.3% 138 Yes


Undisclosed 0140 4 Oil 10.0% / 18.0% / 29.0% / 43.0% 10.0% / 19.9% / 29.8% / 40.3% 0.0% / 1.9% / 0.8% / 2.7% 40 Yes


Undisclosed 0140 4 Oil 42.0% / 7.0% / 17.0% / 34.0% 40.1% / 10.2% / 19.8% / 29.9% 1.9% / 3.2 % / 2.8 %/ 4.1% 40 Yes


Undisclosed 48345 4 Oil 30.0% / 43.1% / 7.7%/ 19.2% 26.3% / 43.7% / 12.7% / 17.2% 3.7% / 0.6%/ 5.0% / 2.0% 137 Yes

Undisclosed 48345 4 Oil 9.6% / 10.3% / 39.1% / 41.0% 10.0 % / 10.0% / 40.0% / 40.0% 0.4% / 0.3% / 0.9% / 1.0% 137 Yes





Conc ept ua l ly the Sam e Approac h Used for Oi l ,

Wat er , and Gas Al loc at ion: Only Inp ut Dat a Di f fers

Oil:

Whole Oil GC Data

Stable Isotope Data (13C)Water:

Major Ion Composition (Cl-, Br-, Na+, Mg2+ , etc.)

Stable Isotope Data (D, 18O, 86Sr/87Sr)Gas:

Gas Component Abundances (e.g., %C1, C2, CO2, N2, etc)

Stable Isotope Data (D, 13C)


16/39


Analy t ic a l Method: Gas Chrom at ography


17/39


Agi len t 6890 GC-FID


18/39


GC-c api l lary c olum n

Column resolution related to:

Column length

Column ID

Type of phase

Thickness of phase Condition of phase

60m DB-1, 0.25mm ID, 0.25umfilm thickness


19/39


GC Fingerpr int of a w hole o i l :

Show s the re la t i ve abundance o f c ompounds

w i th d i ffe ren t m o lecu la r w e igh ts

min10 20 30 40 50 60 70 80 90

pA

0

200

400

600

800

1000

1200

1400

1600

FID1 A, (REF_OIL\6017-1.D)

n-C7

MCH

Tolu

ene

n-C8

M&PXylene

O-xylene

n-C9

n-C10

n-C11

n-C

12 n

-C13

n-C14

n-C15

n-C16

n-C17

Pristane

n-C18

Phytane

n-C19

n-C20

n-C21

n-C22

n-C23

n-C24

n-C25

n-C26

n-C27

n-C28

n-C29

n-C30

n-C31

n-C32

n-C33

n-C34

n-C35

n-C40

Gasoline

Kerosene

Diesel Fuel

Heavy Gas Oil

Lubricating Oil


20/39


Ex panded View s of a Whole Oi l GC Chrom atog ram

Revea l Hundreds s o f In te r para f f in Peak s

10.0 840.0 870.0 900.0 930.0 960.0 990.0

821.9

8

23.3

827.3

829.8

832.6

836.1

83

8.0

839.2

84

0.8

844.8

846.2

847.6

853.5

856.3

8

58.5

864.4

865.4

86

7.3

8

69.9

871.9

875.3

883.0

885.2

88

9.6

89

7.0

NC9

908.8

911.7

914.1

916.9

91

9.4

92

2.9

925.2

929.7

93

1.5

935.49

38.3

9

40.6

942.3

94

4.3

946.2

948.1

951.5

9

54.0

9

55.6

956.7

95

8.3

961.2

962.9

965.6

9

69.1

971.9 977.9

9

79.9

982.4

98

3.9

98

5.3

98

7.6


21/39


Ex panded v iew s of GC chrom atogram s revea l

d i f ferenc es betw een o i ls f rom each in te r va l

10.0 840.0 870.0 900.0 930.0 960.0 990.0

821.9

823.3

827.3

829.8

832.6

836.1

838.0

839.2

840.8

844.8

846.2

847.6

853.5

856.3

858.5

864.4

865.4

867.3

869.9

871.9875.3

883.0

885.2

889.6

897.0

NC9

908.8

911.7

914.1

916.9

919.4

922.9

925.2

929.7

931.5

935.49

38.3

940.6

942.3

944.3

946.2

948.1

951.5

954.0

955.6

956.7

958.3

961.2

962.9

965.6

969.1

971.9 977.9

979.9

982.4

983.9

985.3

987.6

10.0 840.0 870.0 900.0 930.0 960.0 990.0

821

.9

823

.3

827

.3

829

.8832

.6

836

.1

838

.0

839

.2

840

.8844

.8

846

.2

847

.6853

.5

856.3

858

.5

864

.4

865

.4

869

.9

871

.9

8

75

.3

883

.0

885

.2

889

.6

897

.0

908

.8911.7

914

.1

916

.9

919

.4

922

.9

925

.2

929

.7

931

.5

935

.4

938

.3

940

.6

942

.3

944

.3946

.2

948

.1

951

.5

954

.0

955

.6

956

.7

958

.3

961

.2

962

.9

965

.6

969

.1

971

.9

977

.9

97

9.9

982

.4

983

.9

985

.3

987

.6


22/39


Gas 1 is 10% Ethane

Gas 2 is 20% Ethane

A mixture of Gas 1 and Gas 2 was found to be15% Ethane

How much of Gas 1 is in the mixed gas?

Mathem at i cs o f A l l oc a t ion


23/39



This is a system of 2 equations in 2 unknowns.

1 = fraction of Gas 1 in the mix

2 = fraction of Gas 2 in the mix

1*0.1 + 2*0.2 = 0.15

2

1

1.0

1.0

1.5

0.75

1 + 2 = 1.0

x1 = 0.5x2 = 0.5

Solution:


24/39



m end-members

Analyze by GC the same amount of each end member andcomminlged oil

n peaks: P1, P2 , , Pn xij = height of peak i in end-member j

yi = height of peak i in commingled oil Commingled oil consists of:

1 of end-member 1 (fraction) 2 of end-member 2 (fraction)

m of end-member m (fraction) Problem: Determine values of given the height of the n peaks

in each end-member and the commingled oil


25/39



Peak heights mixes linearly. Therefore, we have n

equations. The ith equation is:

xi1 1 + xi2 2 + xim m = yi Implicit constraint: 1 + 2 + m = 1


26/39


I l lus t r a t ion:2 end-m em bers, 3 peak s (idea l )

6000 1 + 4000 2 = 5000

3000 1 + 4000 2 = 3500

1 + 2 = 1

1 = 2 = 0.5

1

2

1000 1 + 2000 2 = 1500


27/39


I l lus t r a t ion:2 end-m em bers, 3 peak s (rea l )

1

2Effect of errors:

NO UNIQUE SOLUTION!!


28/39



1

2

If you believe in this peak

and you believe in this peak

then this is your unscaled solution

and this is your scaled solution


29/39



1

2But if you have no reason to believe

any one peak more than you believe inany other

then any solution in this region is possible


30/39

Oi lT M th d f Fi d i th B t S l t i


31/39


Oi lTrac ers Method fo r Find ing the Best So lu t ion

fo r t he Unmix ing Problem

Y = X is an overconstrained system of equations * = (XTX)-1XTY is the least squares solution to Y = X

If Y = X has a unique solution, * is that solution If Y = X has no solution, * is the value that minimizes ||Y -

X||2 We project * onto the Implicit constraint to find the solution Significantly better estimates of can be derived by (1) applying

certain scaling techniques to X and Y, (2) utilizing informationrevealed by the structure of the variance within the dataset, and(3) eliminating from consideration GC peaks with certain

specific characteristics. Those optimization techniques areproprietary.


32/39


Ex am ple of Why End Mem bers Are Essent ia l

Oil 1 Mix B Mix C Mix H Mix D Mix E Oil 2 Oil 1 Mix B Mix C Mix H Mix D Mix E Oil 2

%Oil 2 0 5 10 15 20 25 100 %Oil 2 0 18.52 37.04 55.56 74.07 92.59 100

Height Peak 1 114.00 121.75 129.50 137.25 145.00 152.75 269.00 Height Peak 1 114.00 121.75 129.50 137.25 145.00 152.75 155.85


Height Peak 3 126.00 130.50 135.00 139.50 144.00 148.50 216.00 Height Peak 3 126.00 130.50 135.00 139.50 144.00 148.50 150.30Height Peak 4 236.00 232.40 228.80 225.20 221.60 218.00 164.00 Height Peak 4 236.00 232.40 228.80 225.20 221.60 218.00 216.56







Solution 1 Solution 2


33/39


0.00

50.00

100.00

150.00

200.00

250.00

300.00

0 10 20 30 40 50 60 70 80 90 100

Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Peak 7

Peak 8

Peak 9

Peak 10

GC

Pea

kHeight

% Oil 2 in Mixture

MixB

MixC

MixH

MixD

MixE

Solution 1



34/39


0.00

50.00

100.00

150.00

200.00

250.00

300.00

0 10 20 30 40 50 60 70 80 90 100

Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Peak 7

Peak 8

Peak 9

Peak 10

GC

Pea

kHeight

% Oil 2 in Mixture

MixB

MixC

MixH

MixD

MixE

Solution 2



35/39


Mathem at ic s o f A l loca t ion

What if both concentrations AND isotopes are measured in the samples?

End Member

Abundance

C1 C2 13C1 13C21 0.9 0.1 -70.00 -50.00

2 0.8 0.2 -60.00 -40.00

Commingled

Gas 0.85 0.15 -65.29 -43.33


36/39


Mat hem at i c s o f A l l oc a t ion


1 = fraction of Gas 1 in the mix2 = fraction of Gas 2 in the mix

0.1 * 1 +0.2 * 2 = 0.15

2

1

1.0

1.0

1.5

0.75

1 + 2 = 1.0 0.9 * 1 +0.8 * 2 = 0.85

0.1 * ((-43.33) - ( -50)) * 1 + 0.2 * ((-43.33) - ( -40)) 2 = 0

0.9 * ((-65.29) - ( -70)) * 1 + 0.8 * ((-65.29) - ( -60)) 2 = 0

M h i f A ll i


37/39


Mat hem at i c s o f A l l oc a t ion


x1 = fraction of Gas 1 in the mixx2 = fraction of Gas 2 in the mix

0.1 * 1 +0.2 * 2 = 0.15

2

1

1.0

1.0

1.5

0.75

1 + 2 = 1.0 0.9 * 1 +0.8 * 2 = 0.85

0.1 * ((-43) - ( -50)) * 1 + 0.2 * ((-43) - ( -40)) 2 = 0

0.9 * ((-66) - ( -70)) * 1 + 0.8 * ((-66) - ( -60)) 2 = 0

Summ ary o f Advanta ges vs Produc t ion Logging


38/39


Summ ary o f Advanta ges vs Produc t ion Logging

Cost advantages relative to conventional e-line PLT

Advantages relative to coiled tubing or tractor-conveyed e-line PLT

Detection of zone performance problems at any pointduring the life of a well.

Applicability to vertical, deviated and horizontalwells.

Applicability to pumping wells

Ability to quantify uncertainty Zonal Production vs. wellbore entry

No risk of sticking a logging tool


39/39

Geochemistry solves problems throughout the lifespan of a field

Rela ted App l ic a t ions o f Geoc hem is t ry

Characterizing charge

Risk (source, maturity,

timing, gas vs oil

potential)

Flow Assurance: Prevent

Sludge/Asphaltene/ Wax

Deposition

EXPLORATION DEVELOPMENT PRODUCTION FIELD ABANDONMENT

Identifyingfluid contacts

Assessing reservoir

compartmentalization

Oil/gas propertyprediction (API, viscosity)

Identifying missed pay

Identifying inducedfracture geometry

Flood monitoring

Assessing sweep

Environmental site

assessment and

di ti

Production

allocation

Identifying completion

problems (tubing string

leaks, poor cement jobs,

ineffective stimulations)

production allocation[1]

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