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Centenario Field Case Study

a strategy for EOR design in a HT/HS field

Alejandra Hryc, Federico Hochenfellner

Pluspetrol SA, Argentina

EOR Workshop, Paris 2015

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

NEUQUÉN

Centenario Field is located in the Neuquén Basin

Patagonia region, Argentina

Field Location

NEUQUÉN

The field produces dry gas, wet gas and light oil.

Most of the oil reserves are located below the city of Neuquén.

Field Location

Fluids:Light oil (40° API) (Tordillo, Lotena & Lajas)Wet gas (Lajas & Lotena) Dry gas (Los Molles)

Trap:Structural & Stratigraphic

Reservoirs:Los Molles , Lajas, Lotena, TordilloLow perm sandstones and conglomerates

Seals and source rock:Shale Formations Vaca Muerta and Los Molles

Average thickness:20-50 mts

Average depth:2550 mgl

Geological Data

Conditions:

Temperature: 82°C

Original Pressure: 265 kg/cm2

Reservoir Fluids:

Oil Density: 40 API

Oil Viscosity: 0,7 cp (@RC)

Oil activity: non active

Original Water salinity: >150.000 ppm TDS

Reservoir water hardness: 40.000 ppm CaCO3

River water salinity: ~ 250 ppm TDS

Reservoir Rock :

Mix to oil-wet High clay content (illite, chlorite 10-30%)

Swir: ~0.35

Sorw: > 0.3

Permeability range: 1mD – 200+mD (kabs)

Porosity range: 9-13%

Very high heterogeneity ~ 0.9 Dykstra Parsons

Drive mechanism: waterflood - Hydraulically fractured

Reservoir Conditions

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

Production History

WcutP[%] qoP[m³/DC] qlP[m³/DC]

0

15

30

45

60

75

90

105

0

2000

4000

6000

8000

10000

12000Ce.x-1/Ce.x-2/Ce.a-3/Ce.a-4/Ce.a-5/...

1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

m3/

d

Wcu

t[%

]

Current Production

Qliq: 9800 m3/dQoil: 390 m3/dWcut: 96%

100

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

• Lotena Formation was selected as EOR target

(400 MMB OOIP, better reservoir conditions)

• Reservoir characteristics made it suitable for CEOR,in particular, surfactant - polymer flood

• Fresh water source availability is an upside for CEORapplications (simplifies selection process, lowerchemical consumption, lower costs)

EOR Screening and Process Selection

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

• Early lab studies started in 2007 in the search for a formulationthat would withstand harsh reservoir conditions

• Complex process requirements led Pluspetrol to take the projectto providers with capabilities to tailor design the chemistryrequired by the water-oil-rock system

• From 2009 on, extensive lab work began with surfactantdeveloper to tailor a formulation for Centenario case

• The EOR pilot zone was developed with infill drilling and freshwater injection

Early Lab Studies

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

Process challenges

1) Define injection salinity (optimal salinity window for surfactantformulation considering fresh water source/salinity gradient)

2) Quantify slug mixing in the front to request formulationchemical stability

3) Select polymer to withstand mixing front conditions and havethe desired rheology

Faced challenges

Process challenges

1) Define injection salinity (optimal salinity window for surfactantformulation considering fresh water source/salinity gradient)

2) Quantify slug mixing in the front to request formulationchemical stability

3) Select a polymer to withstand mixing front conditions andhave the desired rheology

Methodology challenges

1) Limitations mimicking live oil in such light dead oils(surrogate oils)

2) Limited amount of usable cores (extremely highheterogeneous material. Representative & Repeatable? )

3) Definition of analogous fluids and core material (what kindof analogy is required)

Faced challenges

How we addresses them

1) Define injection salinity (optimal salinity window forsurfactant formulation considering: fresh water source/salinitygradient)

Targeted a salinity that would allow finding a surfactant with

good interaction and generating salinity gradient in polymerflush

2) Quantify slug mixing in the front to request formulationchemical stability

Conducted a series of simulation studies for a betterunderstanding of the problematic

3) Select a polymer to withstand mixing front conditions andhave the desired rheology

Stability tests to screen different kinds of formulations underanaerobic conditions

Process Challenges

Derived Simulation Work

Base Case - Assumptions– WF displacement is representative of Centenario field

• 150 g/L initial homogeneous reservoir salinity (initial state for WF)

• 1 g/L injection water salinity (always)

• 65 g/L average reservoir salinity prior to all chemical injections (heterogeneous salinity map)

– Sequence of injections: WF [0.4 PV] / S+P [0.3 PV] / P [0.5 PV]

200mD

180mD

160mD

140mD

120mD

100mD

80mD

60mD

40mD

20mD

2mD

0.2mD

P1 P2

P3 P4

I1

Process Challenges

200mD

180mD

160mD

140mD

120mD

100mD

80mD

60mD

40mD

20mD

2mD

0.2mD

P1 P2

P3 P4

I1

P3 I1 P2

P1 I1 P4

Sequence of injections:

WF [0.4 PV] / S+P [0.3 PV] / P [0.5 PV]

Step 1: 0.4 VP injected

Process Challenges

200mD

180mD

160mD

140mD

120mD

100mD

80mD

60mD

40mD

20mD

2mD

0.2mD

P1 P2

P3 P4

I1

P3 I1 P2

P1 I1 P4

Sequence of injections: WF [0.4 PV] / S+P [0.3 PV] / P [0.5 PV]

Step 2: 0.6 VP injected

Process Challenges

200mD

180mD

160mD

140mD

120mD

100mD

80mD

60mD

40mD

20mD

2mD

0.2mD

P1 P2

P3 P4

I1

P3 I1 P2

P1 I1 P4

Sequence of injections: WF [0.4 PV] / S+P [0.3 PV] / P [0.5 PV]

Step 3: 0.8 VP injected

Process Challenges

P3 I1 P2

P1 I1 P4

P3 I1 P2

P1 I1 P4

Step 3: 0.8 VP injected Step 4: 1.0 VP injected

Process Challenges

Green areas: [Csurf] > 50% [Csurf injected]

(Surfactant effectiveness)

P3 I1 P2

P1 I1 P4

P3 I1 P2

P1 I1 P4

Step 3: 0.8 VP injected Step 4: 1.0 VP injected

Red areas: [Csurf] > 0 & Salinity > 1.0 g/l

(Mixing front conditions)

Process Challenges

Salinity (left) and surfactant concentration (right) maps at t = 0.7 PV(Polymer Drive Start)

Process Challenges

Summary and conclusions

A total of 30 cases were run, combining:

• Six chemical injections scenarios (different sequences, concentrations andmobility ratios)

• Five production strategies scenarios (considering well shut off, wellconversion and infill drilling)

For all cases it was derived that:

• To define slug salinity:

– Original salinity does not play a major role. Bulk surfactant mass interacts withreservoir oil under injection water salinity

– For Centenario study formulation was tailored for 3-5 g/l (3.6 g/l optimal salinity)

• To prevent formation damage:

– Salinity upper limit can be defined by quantifying the mixing that occurs in theslug front. The formulation needs to be chemically stable up to this limit

– For Centenario study, 40 g/l was defined an upper limit for formulation stability

Process Challenges

Oil

• Significant amount of dissolved gas required formulationvalidation under live oil conditions

• Live oil low viscosity (0.7 cp) is hard to mimic under Patm. Needto select a surrogate oil for lab experiments

Temperature

• Degradation issues show at high temperature (f.e. ironinteraction) Specific anaerobic protocols are mandatory forrelevant evaluation

Reservoir Rock Selection

• Strong heterogeneities (at core, layer and sector model scale)makes selection of representative samples challenging

Methodology Challenges

Methodology Challenges

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Strong heterogeneities

• Preferred paths in small cores• Major limiting factor for core-scale experiments with limited slug sizes

28

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CE1288 BOX 7

Full size coreCT-Scan image Tracer test

Methodology Challenges

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Pore Volume injected (PV)

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

Selected formulation (AGES &AAS blend) has very good

interaction with Centenario fluids,achieving ultra low IFT region atoptimal salinity

Formulation Work Results

Coreflood test

High performance (80+ %ROIP Oilrecovery) in model rock(Clashach sandstone) wasachieved

Selected polymer (AMPS) showsdesired rheologic behavoir andcan withstand mixing frontconditions (aging tests andporous media evaluation done)

Salinity

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

Optimization Work and Project Status

Optimization tasks description

• Formulation long term stability tests

• Formulation robustness study

• CDC determination- relative perm end points

• SP injection strategy definition and core simulation

• Formulation performance under extreme conditions (low perm)

Results

• Most of the optimization tasks are completed

• High performance in model core (80+% recovery), incomplete oilrecovery in reservoir rock samples

• Further information is to be acquired to fully understand if core scaleheterogeneity is responsible for incomplete recovery on reservoir rock

• Formulation injectivity is a concern for such low permeabilities,therefore an injectivity test is planned once the lab tests uncertaintiesare narrowed down

• Field Location - Reservoir Description

• Production History

• EOR Screening and Process Selection

• Early Lab studies

• Faced Challenges

• Process Challenges

• Methodology Challenges

• Formulation Work Results

• Optimization Work and Project Status

• Main Lessons Learnt

Outline

Main lessons learnt

• HT/HS reservoirs are complex CEOR candidates that requirespecific approach

Main lessons learnt

• HT/HS reservoirs are complex CEOR candidates that requirespecific approach

• When available, a low salinity water source can be veryhelpful to CEOR in HS reservoirs, allowing to freely tailor theoptimal salinity

Main lessons learnt

• HT/HS reservoirs are complex CEOR candidates that requirespecific approach

• When available, a low salinity water source can be veryhelpful to CEOR in HS reservoirs, allowing to freely tailor theoptimal salinity

• Formulation stability is key to prevent damage in low permformations. Reservoir simulation can be a useful tool to definesalinity upper limit for the formulation to be chemically stable

Main lessons learnt

• HT/HS reservoirs are complex CEOR candidates that requirespecific approach

• When available, a low salinity water source can be veryhelpful to CEOR in HS reservoirs, allowing to freely tailor theoptimal salinity

• Formulation stability is key to prevent damage in low permformations. Reservoir simulation can be a useful tool to definesalinity upper limit for the formulation to be chemically stable

• In highly heterogeneous reservoirs lab results can bechallenging to design, analyze and up-scale

Main lessons learnt

• HT/HS reservoirs are complex CEOR candidates that requirespecific approach

• When available, a low salinity water source can be veryhelpful to CEOR in HS reservoirs, allowing to freely tailor theoptimal salinity

• Formulation stability is key to prevent damage in low permformations. Reservoir simulation can be a useful tool to definesalinity upper limit for the formulation to be chemically stable

• In highly heterogeneous reservoirs lab results can bechallenging to design, analyze and up-scale

• HS/HT CEOR projects could demand several years of researchand evaluation before moving to a field pilot scale

Acknowledgments

Pluspetrol SA

for disclosing the results of this research

EOR Alliance (Solvay & IFP group)

for the years of dedication to this challenging project

Thank you

Back up Slides

SIMULATION CASESA total of 30 cases were run, base case included:

Chemical injections strategiesA) WF [0.4 PV] / S [0.3 PV] / WF [0.5 PV]

B) WF [0.4 PV] / S [0.3 PV] / P1 [0.5 PV]

C) WF [0.4 PV] / S [0.3 PV] / P2 [0.5 PV]

D) WF [0.4 PV] / S+P1 [0.3 PV] / P1 [0.5 PV]

E) WF [0.4 PV] / S+P2 [0.3 PV] / P2 [0.5 PV]

P1 & P2 are the same polymer but with 500 ppm & 2000 ppm, Mr=1.2 & Mr=10

Production strategies0) Regular direct 5-spot displacement.1 central injector and 4 corner producers

I & II) Well conversion. single well and well pair conversion

III) Well shut-off

IV & V) Infill drilling. 1 additional injection well, central injector remaining or

turned into a producer

Simulation Studies

SIMULATION CASESFirst attempts do not account for

• Cross-flow (single layer approach)

• Ion exchange with reservoir clays (rock ion exchange capacity)

• Dispersion effect (assumed as if distance is short between I &P)

Additional simulation work did not modify the mentionedconclusions

Simulation Studies