Core Analysis Uncertainty andRock Typing

SPWLA Carbonate Workshop

Abu Dhabi

February, 2010

Gary Potter

Houston

Is Rock Typing the Same asFacies?

• Facies are a body of rock with specifiedcharacteristics (from Wikipedia)

Is Rock Typing the Same asFacies?

• Facies are a body of rock with specifiedcharacteristics (from Wikipedia)

• Types of facies

– Lithofacies - based on lithology (sandstones,siltstones etc)

– Microfacies - based on micro fabric

– Ichnofacies - based on burrow forms

– Electrofacies - based on electric log responses

– Seismicfacies - based on velocity response

Rock Type

• Rock types that have been classified according totheir petrophysical properties, especially propertiesthat pertain to fluid behavior within the rock, such asporosity, capillary pressure, permeabilities, irreduciblesaturations or saturations. (from Schlumberger Oilfield Glossary)

Rock Type

• Rock types that have been classified according totheir petrophysical properties, especially propertiesthat pertain to fluid behavior within the rock, such asporosity, capillary pressure, permeabilities, irreduciblesaturations or saturations. (from Schlumberger Oilfield Glossary)

• Rock Types are categorized by propertiesimportant to HC storage and flow.

Scale

(after Worthington)

WellLog

BeddingScale

Core PlugScale

StratumScale

PoreScale

HomogeneousStratum

HeterogeneousStratum

HomogeneousRock Fabric

HeterogeneousRock Fabric

Pore Scale Controls

How are Rock Types Determined

• Porosity and Permeability

– Considers pore throat size

How are Rock Types Determined

• Porosity and Permeability

– Considers pore throat size

• Capillary Pressure

– Considers interconnection and distribution ofpore throats with storage

How are Rock Types Determined

• Porosity and Permeability

– Considers pore throat size

• Capillary Pressure

– Considers interconnection and distribution ofpore throats with storage

• Relative Permeability

– Includes wettability

Rock Types by Porosity and

Permeability

• K-Phi Cross Plot

0.01

0.10

1.00

10.00

100.00

1000.00

0 10 20

Air

Perm

eab

ilit

y,

md

Core Porosity, %

Rock Types by Porosity and

Permeability

• K-Phi Cross Plot

• Winland

– Log (R35) = .732+ .588Log(K) - .864Log(Φ)

0.01

0.10

1.00

10.00

100.00

1000.00

0 10 20

Air

Perm

eab

ilit

y,

md

Core Porosity, %

Rock Types by Porosity and

Permeability

• K-Phi Cross Plot

• Winland

– Log (R35) = .732+ .588Log(K) - .864Log(Φ)

• Pittman– Pittman Log (R10) = .459 + .500Log(K) - .385Log(f)

– Pittman Log (R20) = .218 + .519Log(K) - .303Log(f)

– Pittman Log (R30) = .215 + .547Log(K) - .420Log(f)

– Pittman Log (R35 )= .255 + .565Log(K) - .523Log(f)

– Pittman Log (R40) = .360 + .582Log(K) - .680Log(f)

– Pittman Log (R50) = .778 + .626Log(K) – 1.205Log(f)

0.01

0.10

1.00

10.00

100.00

1000.00

0 10 20

Air

Perm

eab

ilit

y,

md

Core Porosity, %

Rock Types by Porosity and

Permeability

• K-Phi Cross Plot

• Winland

– Log (R35) = .732+ .588Log(K) - .864Log(Φ)

• Pittman– Pittman Log (R10) = .459 + .500Log(K) - .385Log(f)

– Pittman Log (R20) = .218 + .519Log(K) - .303Log(f)

– Pittman Log (R30) = .215 + .547Log(K) - .420Log(f)

– Pittman Log (R35 )= .255 + .565Log(K) - .523Log(f)

– Pittman Log (R40) = .360 + .582Log(K) - .680Log(f)

– Pittman Log (R50) = .778 + .626Log(K) – 1.205Log(f)

• Rock Quality Index

0.01

0.10

1.00

10.00

100.00

1000.00

0 10 20

Air

Perm

eab

ilit

y,

md

Core Porosity, %

e

kRQI

0314.0

Rock Types by Porosity and

Permeability

• K-Phi Cross Plot

• Winland

– Log (R35) = .732+ .588Log(K) - .864Log(Φ)

• Pittman– Pittman Log (R10) = .459 + .500Log(K) - .385Log(f)

– Pittman Log (R20) = .218 + .519Log(K) - .303Log(f)

– Pittman Log (R30) = .215 + .547Log(K) - .420Log(f)

– Pittman Log (R35 )= .255 + .565Log(K) - .523Log(f)

– Pittman Log (R40) = .360 + .582Log(K) - .680Log(f)

– Pittman Log (R50) = .778 + .626Log(K) – 1.205Log(f)

• Rock Quality Index

All from equating Poiseuille’s and Darcy’s equation

0.01

0.10

1.00

10.00

100.00

1000.00

0 10 20

Air

Perm

eab

ilit

y,

md

Core Porosity, %

e

kRQI

0314.0

Poiseuille`s/Darcy`s equation

relates Pore Throat to K & Phi

• Poiseuille’s Equation for a tube

L

PA

rq

8

2

Poiseuille`s/Darcy`s equation

relates Pore Throat to K & Phi

• Poiseuille’s Equation for a fracture

L

PA

dq

12

2

Poiseuille`s/Darcy`s equation

relates Pore Throat to K & Phi

• Poiseuille’s Equation for a tube

• Darcy’s Equation

L

PA

rq

8

2

L

PAkq

Poiseuille`s/Darcy`s equation

relates Pore Throat to K & Phi

• Poiseuille’s Equation for a tube

• Darcy’s Equation

• Combined

L

PA

rq

8

2

L

PAkq

8

2rk

Poiseuille`s/Darcy`s equation

relates Pore Throat to K & Phi

• Poiseuille’s Equation for a tube

• Darcy’s Equation

• Combined with porosity

L

PA

rq

8

2

L

PAkq

8

2rk

8

2rk

Poiseuille`s/Darcy`s EquationRelates Pore Throat to K & Phi

kr

8

Solve for radius

Poiseuille`s/Darcy`s EquationRelates Pore Throat to K & Phi

kr

8

Solve for radius Similar to RQI

e

kRQI

0314.0

Poiseuille`s/Darcy`s EquationRelates Pore Throat to K & Phi

kr

8

log5.0log5.0452.0log kr

Logrithm

Solve for radius Similar to RQI

e

kRQI

0314.0

Poiseuille`s/Darcy`s EquationRelates Pore Throat to K & Phi

kr

8

log5.0log5.0452.0log kr

Logrithm

Solve for radius

Compare to Winland and Pittman equations

Winland Log (R35) = .732+ .588Log(K) - .864Log(Φ)

Pittman Log (R10) = .459 + .500Log(K) - .385Log(f)

Similar to RQI

e

kRQI

0314.0

Lab Performance in Measuring K

and Phi

Internal Core Lab Quality Assurance Program

• Twenty- three (23) locations

• Some 3200 total points of data for evaluation

• Over 2 year(s) involved in each data series

• Updated program as existed for 8 years

RCAL QA/QC Plugs - materials &plan

Twenty-four (24) total samples

Twelve (12) 1.0” diameterTwelve (12) 1.5” diameter

Porosity Ranges: 2.0 – 23.0%

Kinf Ranges: 0.0001 – 1050 mD

Grain Den. Ranges: 2.599 – 2.858 g/cc

QA/QC Results - assessmentcriteria

• “Experienced-based acceptabledeviations” ofThomas & Pughused forperformanceassessments

• Prelim resultscompared tomean of limited“standard”measurements

Table 1: Maximum acceptable deviation in standard core plug analysis

Meancoefficient

Experience- Statistically- of

Measurement based derived1

variance, %

Porosity +/-0.5 Por% +/-0.23% 0.67

Grain density +/-0.01 g/cm3

+/-0.0093 g/cm3

0.13

Air permeability:0.01 - 0.1 md +/-30% +/-21% 8.0

0.1 - 1.0 md +/-25% +/-21% 8.01.0 - 50 md +/-15% +/-13% 5.0

50 md - 1 darcy +/-15% +/-8% 3.0

1A single measurement made on the same sample that falls outside

the specified limit is 99% likely to be in error, assuming that both testsare performed with the same standard deviation

Taken from:Thomas, D.C. and Pugh, V.J.: "A Statistical Analysis of the Accuracyand Reproducibility of Standard Core Analysis", The Log Analyst,March-April, 1989, 71-77. (journal version of SCA 8701)

Core Labs` QA Experience

MeasurementThomas & PughExperience Error

Internal CoreLab QA

Porosity 0.50 Por% 0.20 Por%

Permeability

<0.001 md -- 26%

0.01 - 0.1 md 30% 12%

0.1-1.0 md 25% 8

1.0-50 md 15% 7

50 md- 1 darcy 15% 7

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.1 0.2 0.3

3S

tdD

ev

,P

or%

Porosity, %

Measurement Error vsPorosity

0

20

40

60

80

100

0.0001 0.001 0.01 0.1 1 10 100 1000

3R

el

Std

Dev

,%

Permeability, md

Measurement Error vsPermeability

Impact on K&Phi Crossplot

y = 0.0194e0.4433x

0.001

0.010

0.100

1.000

10.000

100.000

1000.000

10000.000

0.00 10.00 20.00 30.00

Perm

eab

ilit

y,

md

Porosity, %

Porosity-Perm Cross Plot

Series1

Expon.(Series1)

y = 0.0194e0.4433x

y = 0.0232e0.4422x

0.001

0.010

0.100

1.000

10.000

100.000

1000.000

10000.000

100000.000

0.00 10.00 20.00 30.00

Perm

eab

ilit

y,

md

Porosity, %

Error Hi Perm vs Low Porosity

Series1

Series2

Series3

Expon. (Series1)

Expon. (Series3)

y = 0.0194e0.4433x

y = 0.016e0.4447x

0.001

0.010

0.100

1.000

10.000

100.000

1000.000

10000.000

100000.000

0.00 10.00 20.00 30.00

Perm

eab

ilit

y,

md

Porosity, %

Error Low Perm vs Hi Porosity

Series1

Series2

Series3

Expon. (Series1)

Expon. (Series2)

MeasurementThomas & PughExperience Error

Internal CoreLab QA

Porosity 0.50 Por% 0.20 Por%

Permeability

<0.001 md -- 26%

0.01 - 0.1 md 30% 12%

0.1-1.0 md 25% 8

1.0-50 md 15% 7

50 md- 1 darcy 15% 7

Impact in Pitman/Winland curves

0.001

0.01

0.1

1

10

100

1000

10000

0 10 20 30 40

Perm

eabili

ty,

md

Porosity, %

Winland R35 Type Curves

150mm

20mm

3mm

0.3mm

0.02mm

Impact in Pitman/Winland curves

0.001

0.01

0.1

1

10

100

1000

10000

0 10 20 30 40

Perm

eabili

ty,

md

Porosity, %

Winland R35 Type Curves

3mm

Perm*0.92

Perm*1.08

Impact in Pitman/Winland curves

0.1

1

10

100

0 10 20 30 40

Perm

eabili

ty,

md

Porosity, %

Winland R35 Type Curves

3mm

Perm*0.92

Perm*1.08

Using Leverett J-Function

• J-Function used to normalize capillary pressurefor different K and f within a rock type

• J-Function data that does not group indicatesdifferent rock type

• J-Function

k

J

rPc

coscos2

Leverett J-Function

• J-Function used to normalize capillary pressurefor different K and f within a rock type

• J-Function data that does not group indicatesdifferent rock type

• J-Function

k

J

rPc

coscos2

cos

2166.0k

P

Jc

J = 0.08691(Sw*)-1.11195

0.01

0.1

1

10

0.01 0.1 1

Sw*, (Sw-Swir)/(1-Swir)

J

Laboratory Pc vs Swdata for 6 samples.

Sw converted to Sw*

• Sw* at Pc max (140 psi) = 0, therefore not plotted on log scale

• Correlate Sw @ Pc max vs Rock Quality parameter (e.g., RQI)

• Determine J from interval K, f, Pc (or Height above FWL); Predict Sw*

• Predict Swir (140) for Rock Quality of interest; de-normalize Sw*

Sw* = (0.08691/J)(-1/-1.11195)

Swir = Sw at max Pcof test; in this example,max Pc = 140 psi

Leverett J Function vs Sw*

J = 0.08691(Sw*)-1.11195

0.01

0.1

1

10

0.01 0.1 1

Sw*, (Sw-Swir)/(1-Swir)

J

Laboratory Pc vs Swdata for 6 samples.

Sw converted to Sw*

• Sw* at Pc max (140 psi) = 0, therefore not plotted on log scale

• Correlate Sw @ Pc max vs Rock Quality parameter (e.g., RQI)

• Determine J from interval K, f, Pc (or Height above FWL); Predict Sw*

• Predict Swir (140) for Rock Quality of interest; de-normalize Sw*

Sw* = (0.08691/J)(-1/-1.11195)

Swir = Sw at max Pcof test; in this example,max Pc = 140 psi

Leverett J Function vs Sw*

Lab Measurement error in Capillary

pressure

0

50

100

150

200

250

300

350

400

450

0.00 0.20 0.40 0.60 0.80 1.00

Pc,p

si

Sw, fraction

CENTRIFUGE GAS/WATER PcRepeatability Testing

Originaltest1stRecheck

Lab Measurement error in Capillary

pressure

0

50

100

150

200

250

300

350

400

450

0.00 0.20 0.40 0.60 0.80 1.00

Pc,p

si

Sw, fraction

CENTRIFUGE GAS/WATER PcRepeatability Testing

Originaltest1stRecheck

0

50

100

150

200

250

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Cap

illa

ryP

ressu

re,p

si

Water Saturation, fraction

CoreLab IF

Average Sw

Pc COMPARISONUnconfined Centrifuge

gas/water

Note, these data werere-evaluated 1-20-10using Forbes (TblCrv

After Owens & Archer, JPT, July 1971

0.001

0.01

0.1

1

0 0.2 0.4 0.6 0.8 1

Sw

Re

lati

ve

Pe

rme

ab

ilit

y,fr

ac

tio

n

0º

47º

90º

138º

180º

Contact Angle

WW

OW

• Same core plug (Torpedo Sand; Ka = 571 md)

• Swi = 0.20 for all tests

• Steady-State (Penn State) method

• Oil treated to change wettability

Relative Permeability includesWettability

Unsteady-State RelativePermeability Error

• Pore volume major factor

• In JBN analysis

– Smoothness of data critical

– Knowing dead volumes and detectingbreakthrough very important

– Experience indicates• Effective Perm +/- 5% of value

• Saturation +/- 10% saturation unit

• Variability decreases as floodout is approached

Steady-State RelativePermeability Error

• X-ray saturation data

– +/- 1.2% saturation % units

– At least 1 million photons used (Poisson’sstatistics)

• Effective permeability data

– Typically +/- 2% of value

– Low flow rate, +/-10 – 50% of value

Error bounds on RelativePermeability

0.001

0.01

0.1

1

0 0.2 0.4 0.6 0.8 1

Rela

tive

Perm

eab

ilit

y,

fracti

on

Water Saturation, fraction

Krw WaterIncreasingKro Water Increasing

Water Kr LCL

Water Kr UCL

Conclusion

• Rock type is used to group rocks that havecommon storage and flow properties

• Rock typing is mostly based on pore size

• Rock properties measurement variabilitieshave no impact on rock typing

• Rock typing uses porosity, permeability,capillary pressure, and relative permeability