SaraThomasمهم.ppt

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SPE DISTINGUISHED LECTURER SERIESis funded principally

through a grant of the

SPE FOUNDATIONThe Society gratefully acknowledges

those companies that support the program

by allowing their professionals

to participate as Lecturers.

And special thanks to The American Institute of Mining, Metallurgical,

and Petroleum Engineers (AIME) for their contribution to the program.


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CHEMICAL EOR THE PAST,DOES IT HAVE A FUTURE?Sara Thomas

PERL Canada Ltd

[email protected]
mailto:[email protected]:[email protected]


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THE PAST :Limited Commercial Success

FUTURE :Very BrightPast experience

High oil pricesScaled models


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OBJECTIVES Why chemical EOR methods have not

been successful?

Process limitations Current status of chemical floods

Recent changes that make such methodsattractive


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CHEMICAL EOR HOLDSA BRIGHT FUTURE

Conventional oil RF


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CHEMICAL EOR TARGET INSELECTED COUNTRIES

100

8477

63 61

51

40

26 24

12 10 10 9 7 6 4 4 3 3

173

0.3 0.20.60.9

020

40

60

80

100

120

140

160

180

S.Arabia

USA

Iran

Iraq

Kuwait

AbuDhabi

Venezuela

Russia

Libya

Nigeria

China

Qatar

Mexico

Canada

Brazil

Norway

Oman

India

UK

Dubai

Denmark

Romania

Germany

France

BillionBbl

Assumed:

Primary Rec. 33.3 %OOIP

Chem. Flood Rec. 33.3 %OIP


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CHEMICAL EOR TARGET INSELECTED COUNTRIES

100 84 77 63 61 51 40 26 24 12 10 10 9 7 6 4 4 3 3173

0.3

0.2

0.6

0.9

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

S.

Arabia

USA

Iran

Iraq

Kuwait

AbuDhabi

Venezuela

Russia

Libya

Nigeria

China

Qatar

Mexico

Canada

Brazil

Norway

Oman

India

UK

Dubai

Denmark

Romania

Germany

France

BillionBbl

Assumed:

Primary Rec. 33.3 %OOIP

Chem. Flood Rec. 33.3 %OIP


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CHEMICAL METHODS Chemical EOR methods utilize:

Polymers

Surfactants

Alkaline agents

Combinations of such chemicals

ASP (Alkali-Surfactant-Polymer) flooding MP (Micellar-Polymer) flooding


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CLASSIFICATIONCHEMICAL METHODS

Polymer

SurfactantAlkali

Emulsion

Micellar

ASP


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CHEMICAL FLOODS HISTORYUSA CHINA

0

5,000

10,000

15,000

20,000

25,000

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

OilProduction,

B/D

Total

Polymer

Micellar

Alkaline

Surfactant

50,000

100,000

150,000

200,000

250,000

300,000

1995 1997 1999 2001 2003

O

ilProduction,

B/D

Total


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Chemical Floods -CURRENT STATUS WORLDWIDE

OGJ April 12, 2004

China

Venezuela

France

India

IndonesiaUSA

Total Number of Projects: 27


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Chemical Floods -PRODUCTION WORLDWIDE

OGJ April 12, 2004

China

France Indonesia

USA

Total oil production: 300,000 B/D


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OBJECTIVES OF CHEMICALFLOODING Increase the Capillary NumberNc to

mobilize residual oil

Decrease the Mobility Ratio Mforbetter sweep

Emulsification of oil to facilitateproduction


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Chemical Flooding -GENERAL LIMITATIONS

Cost of chemicals

Excessive chemical loss: adsorption,

reactions with clay and brines, dilution

Gravity segregation

Lack of control in large well spacing

Geology is unforgiving!

Great variation in the process mechanism,both areal and cross-sectional


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Polymer Flood -FIELD PERFORMANCESanand Field, India

1989 1991 1993 1995

0

25

50

75

100

125

500

530

560

590

620

650

Projected

EOR OIL


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Variations Surfactant-Polymer Flood (SP)

Low Tension Polymer Flood (LTPF)

Adsorption on rock surface

Slug dissipation due to dispersion

Slug dilution by water

Formation of emulsions

Treatment and disposal problems

SURFACTANT FLOODING

mixing zone

Surfactant Flood

residual oiloil

watersurfactant

slug

drive

water


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Surfactant flood -FIELD PERFORMANCEGlenn Pool Field, OK

1984 86 87 88 89 90 91 9285

1,000

100

10

OIL

WOR


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Process depends on mixing of alkali and oil Oil must have acid components

Emulsification of oil, drop entrainment and

entrapment occur Effect on displacement and sweep efficiencies?

Polymer slugs used in some casesPolymer alkali reactions must be accounted for

Complex process to design

ALKALINE FLOODING

Alkaline Flood

mixingzones

oil

waterdrive

water

caustic

slug

residual oil

low

IFT

zone


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Alkaline flooding -

FIELD PERFORMANCEField Slug Size Conc. Oil Satn. Consum. Oil Rec.

% PV wt% %PV mg/g rock %OIP

1 Whittier 8 0.2 51 2.4-11.2 4

2 Singleton 8 2.0 40 - 53 N. Ward Estes 15 4.9 64 17.2 8

4 L. A. Basin 5 0.4 30 - 3

5 Orcutt Hill 2 0.42 50 0.5 2

6 Van 12 0.14 25-35 0.6-1.2 3

7 Kern River 48 0.15 52 1.3 none8 Harrisburg 9 2.0 30-40 - 6

9 Brea-Olinda 1.2 0.12 50-60 - 2


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ALKALINE-POLYMER FLOODDavid Field, Alberta

0.1

1

10

100

10

1

100

1969 1974 1979 1984 1989 1994 1999 2004

Oil Cut

Oil Rate

PrimaryWaterflood Alkaline-Polymer

Flood

1000


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ASP: ALKALI-SURFACTANT-POLYMER FLOODING

Several variations:

ASP

SAP PAS Sloppy Slug

Injected aspremixed slugsor in sequence

ASP Flood

oil

bankSurf

alkalidrive

water polymer

oil

water

Field tests have been encouraging Successful in banking and producing residual oil Mechanisms not fully understood


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ASP PILOT Daqing, China

10

100

20

1993

Oil Cut

Oil Rate

1994 1995 1996

50


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Utilizes microemulsion and polymer buffer slugs Miscible-type displacement Successful in banking and producing residual oil

Process Limitations: Chemical slugs are costly Small well spacing required High salinity, temperature and clay Considerable delay in response Emulsion production

MICELLAR FLOODING

mixing

zone

drive

water

oil

water

micellar

slug

polymer

oil

bank

mixing zone

Micellar Flood


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ASP vs. MICELLAR FLOOD -Lab Results Mitsue Oil Core Floods

Earlier oil breakthrough and quicker recovery in micellar flood

Micellar Flood

0

20

40

60

80

100

0 0.5 1 1.5 2 2.5

Pore Volumes Injected

OilCut,%;Cum.

Recovery,%O

IP

Slug 5% Buffer 50%

Soi 32%

92% OIP

Oil Cut

ASP Flood

0

20

40

60

80

100

0 0.5 1 1.5 2 2.5

Pore Volumes Injected

Alkali 5%,Surfactant 10%,Polymer 60%

Soi 38% 80% OIP

Oil Cut


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Micellar flood TYPICAL PERFORMANCEBradford Special Project No. 8

10

100

1,000

0.1

1

10

Dec. 81 Dec. 82 Dec. 83 Dec. 84 Dec. 85

Oil Cut

Oil Rate

micellarinjection


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Micellar floods FIELD TESTS

Micellar Slug Size, %PV

00

20

40

60

80

100

2 4 6 8 10 12 14

Henry S

119-RHenry E & Henry W

Wilkins

Dedrick


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ASP AND MP FIELD PROJECTS

* %OOIP

ASP Floods Started Appln. Acre Rec., %OIP

David, Alberta 1986 Tertiary 252 *21West Kiehl, Wyoming 1987 " 106 34.4

Gudong, China 1992 " 766 29.4

Cambridge, Wyoming 1993 " 72 *26.8

Daqing, China 1994 " 8.4 23.9

Karamay, China 1996 " 766 *24

Viraj, India 2002 " 68 *24

Micellar FloodsDedrick (IL) 1962 Secondary 2.5 *49.7

Robinson, 119-R (IL) 1968 Tertiary 40 39

Benton (IL) Shell 1972 " 160 29

Robinson, 219-R (IL) 1974 " 113 27

North Burbank (OK) 1976 " 90 11

Robinson, M1 (IL) 1977 " 407 50

Bradford (PA) 1980 " 47 50Salem Unit (IL) 1981 " 200 47

Louden (IL) 1977 " 40 27

Louden (IL) 1980 " 80 33

Chateaurenard, (France) 1983 " 2.5 67


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OTHER METHODS Emulsion flooding

Micellar-Alkaline-Polymer flood (MAP) Surfactant huff npuff

Surfactant with thermal processes


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REASONS FOR FAILURE Low oil prices in the past

Insufficient description of reservoir geology Permeability heterogeneities

Excessive clay content

High water saturation Bottom water or gas cap

Fractures

Inadequate understanding of process mechanisms

Unavailability of chemicals in large quantities Heavy reliance on unscaled lab experiments


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SCALE-UP METHODS Require:

Knowledge of process variables orcomplete mathematical description

Derivation of scaling groups Model experiments

Scale-up of model results to field

Greater confidence to extend lab

results to field


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SCALING GROUPS Micellar Flood:

Additional Groups: Slug Size, Flood Rate, Mixing Coefficient, Oil Recovery

1

p M M

p M

M p P

oi oi oi M p

p M p M PS soi m oi oi

S S S rkPV PV v v a r

S k S S

max max max max

max maxmax

max max

* *

* *

2 * 2

LE LE

EA

c c rw o rE w A E

o o c ro w rw E L L

oi o L o oi L o

ro ro

P P k k q qL p

d gh gh P k k q q

S L q L S K

kk pt kk p

max ,

s sL

ro T oi o L s p

C CK

kk p K S C C


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0

10

20

30

40

50

60

0 0.2 0.4 0.6 0.8 1 1.2

Pore Volumes Produced

OilRecovery,

%OIP

Predicted

Actual

RESULTS: PREDICTION vs.ACTUAL


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HOW TO PLAN A FLOOD Choose a process likely to succeed in

a candidate reservoir Determine the reasons for success or

failure of past projects of the process

Research to fill in the blanks Determine process mechanisms Derive necessary scaling criteria Carry out lab studies

Field based research Establish chemical supply Financial incentives essential


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PROCESS EVALUATION Compare field results with lab

(numerical) predictions

Relative permeability changes?

Oil bank formation? If so, what size?

Mobility control?

Fluid injectivity?

Extent of areal and vertical sweep? Oil saturations from post-flood cores?


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INTERPRETATION OF RESULTS Large number of chemical floods

with little technical success

Field tests implemented for taxadvantage distort theprocesspotential

Questionable interpretation


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COST OF CHEMICALS

As the oil prices rise, so does the cost ofchemicals, but not in the same proportion Typical Costs:

Polymer - $3/lb

Surfactant - $1.20/lb Crude oil - $60/bbl Caustic - $0.60/lb Isopropanol - $20/gallon Micellar slug - $25/bbl

Process Efficiency: volume of oil recovered perunit volume (or mass) of chemical slug injected


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THE CASE FOR CHEMICALFLOODING

Escalating energy demand, declining reserves

Two trillion bbl oil remaining, mostly in depleted

reservoirs or those nearing depletion

Infill drilling often meets the well spacing required

Fewer candidate reservoirs for CO2 and miscible

Opportunities exist under current economic conditions

Improved technical knowledge, better risk

assessment and implementation techniques


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CONCLUSIONS Valuable insight has been gained through

chemical floods in the pastfailures as wellas successes

MP and ASP methods hold the greatestpotentialfor commercial success; polymerflooding a third option

Chemical flooding processes must bere-evaluated under the current technical andeconomic conditions


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Chemical floods offer the only chance ofcommercial success in many depleted andwaterflooded reservoirs

Chemical flooding is here to stay becauseit holds the key to maximizing the reservesin our known reservoirs

CONCLUSIONS

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