production allocation[1]
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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
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Out l ine
Introduction
Examples
Mechanics of Method
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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.
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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 51.5% / 48.5% 50.2% / 49.8% 1.3% 40 Yes
Undisclosed 0140 2 Oil 50.5 %/ 49.5% 49.9% / 50.1% 0.6% 40 Yes
Undisclosed 1053 2 Oil 90.4% / 9.6% 91.4% / 8.6% 1.0% 171 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
Undisclosed 1053 2 Oil 45.4% / 54.6% 44.3% / 55.7% 1.1% 171 Yes
Undisclosed 1053 2 Oil 60.2% / 39.8% 59.9% / 40.1% 0.3% 171 Yes
Undisclosed 1053 2 Oil 70.9% / 30.4% 70.2% / 29.8% 0.7% 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 49.2% / 28.9% / 21.9% 48.1% / 29.7% / 22.2% 1.1% / 0.8% / 0.3% 93 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 28.3% / 30.5% / 41.2% 31.0% / 29.9% / 39.1% 2.7% / 0.6% / 1.1% 138 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
Average error of allocation of 3-zone artifical mixtures of oils in this table: 2.0%
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 18.0% / 25.0% / 36.0% / 19.0% 19.8% / 29.9% / 39.1% / 10.6% 1.8% / 4.9% / 3.1% / 8.4% 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 30.7% / 25.9% / 11.0% / 32.4% 30.0% / 30.0% / 10.0% / 30.0% 0.7% / 4.1% / 1.0% / 2.4% 137 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
Undisclosed 48345 4 Oil 21.0% / 26.9% / 22.7% / 29.4% 20.3% / 29.5% / 20.0% / 30.2% 0.7% / 2.6% / 2.7% / 0.8% 137 Yes
Average error of allocation of 4-zone artifical mixtures of oils in this table: 2.3%
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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)
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Analy t ic a l Method: Gas Chrom at ography
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Agi len t 6890 GC-FID
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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
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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
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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
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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
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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
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Mathem at i cs o f A l l oc a t ion
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:
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Mathem at i cs o f A l l oc a t ion
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
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Mathem at i cs o f A l l oc a t ion
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
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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
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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!!
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I l lus t r a t ion:2 end-m em bers, 3 peak s (rea l )
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
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I l lus t r a t ion:2 end-m em bers, 3 peak s (rea l )
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
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Oi lT M th d f Fi d i th B t S l t i
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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.
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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 2 158.00 164.30 170.60 176.90 183.20 189.50 284.00 Height Peak 2 158.00 164.30 170.60 176.90 183.20 189.50 192.02
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
Height Peak 5 277.00 275.40 273.80 272.20 270.60 269.00 245.00 Height Peak 5 277.00 275.40 273.80 272.20 270.60 269.00 268.36
Height Peak 6 130.00 132.25 134.50 136.75 139.00 141.25 175.00 Height Peak 6 130.00 132.25 134.50 136.75 139.00 141.25 142.15
Height Peak 7 283.00 282.35 281.70 281.05 280.40 279.75 270.00 Height Peak 7 283.00 282.35 281.70 281.05 280.40 279.75 279.55
Height Peak 8 172.00 169.05 166.10 163.15 160.20 157.25 113.00 Height Peak 8 172.00 169.05 166.10 163.15 160.20 157.25 156.07
Height Peak 9 143.00 147.55 152.10 156.65 161.20 165.75 234.00 Height Peak 9 143.00 147.55 152.10 156.65 161.20 165.75 167.57
Height Peak 10 149.00 150.60 152.20 153.80 155.40 157.00 181.00 Height Peak 10 149.00 150.60 152.20 153.80 155.40 157.00 157.64
Solution 1 Solution 2
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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
Ex am ple of Why End Mem bers Are Essent ia l
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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
Ex am ple of Why End Mem bers Are Essent ia l
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2009 Weatherford Laboratories. All rights reserved.
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
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2009 Weatherford Laboratories. All rights reserved.
Mat hem at i c s o f A l l oc a t ion
What if both concentrations AND isotopes are measured in the samples?
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
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2009 Weatherford Laboratories. All rights reserved.
Mat hem at i c s o f A l l oc a t ion
What if both concentrations AND isotopes are measured in the samples?
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
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2009 Weatherford Laboratories. All rights reserved.
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
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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)
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