Measuring Effective Wellbore Permeability

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Measuring Effective Wellbore Permeability Sarah Gasda, Princeton University Michael Celia, Princeton University Jan Nordbotten, Univ. of Bergen

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Measuring Effective Wellbore Permeability. Sarah Gasda, Princeton University Michael Celia, Princeton University Jan Nordbotten, Univ. of Bergen. Objective. Propose a simple field test to determine effective ( bulk ) wellbore permeability - PowerPoint PPT Presentation

Transcript of Measuring Effective Wellbore Permeability

Page 1: Measuring Effective Wellbore Permeability

Measuring Effective Wellbore Permeability

Sarah Gasda, Princeton University

Michael Celia, Princeton University

Jan Nordbotten, Univ. of Bergen

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Objective

• Propose a simple field test to determine effective (bulk) wellbore permeability

• Use numerical analysis to determine the feasibility of this test– Define the range of detection given

constraints on instrument accuracy

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Approach

• We design a test to determine well permeability.– If we can estimate permeability values for the

formation and caprock, we can find well permeability from pressure response.

• We do this by using simulations to generate response curves that relate pressure response to well permeability.

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Existing Oil and Gas Wells

From IPCC SRCCS, 2005End of 2004End of 2004

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Leakage Pathways in Wells

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Modeling CO2 leakage

• Large spatial and temporal scales

• Multiple leaky wells

– probabilistic framework

• No data exist on wells

– Need to pin down statistical distributions

• Need a simple test to identify kwell in well segments

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Experimental Design

Disturbed zone, kw

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Numerical Experiments

• Standard finite-difference simulator– axi-symmetric coordinates– transient, single-phase flow

• 7 permeable layers (10mD), 7 shale caprocks (0.1mD)– Fixed pressure at top and

outer boundaries– Impermeable bottom

boundary

• Explore parameter space– Vary permeability in well

(kw), caprock (k’), and lower formation (k)

Disturbed zone, kw

r

z

rB

Shale layers

Permeable formations

Fixed pressure B.C.

Lower formation, k

Intermediary caprock, k’

0.5 m

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Example Numerical Results

range ofdetection

Transient data

Steady-state data

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Dimensionless Results

k=10-2 Dk= 1 D

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Limits on Field Measurements

• Instrument measurement accuracy – Pressure transducers rated for high P,T

• ±0.1 bar (Schlumberger, UNIGAGE Quartz)

• Fracture pressure – Minimum horizontal fracture stress ~17 kPa/m

• Bachu et al. 2005. Underground Injection Sci. & Tech.

– Maximum pressure change must be less than fracture pressure minus initial pressure

• Average hydrostatic gradient ~11kPa/m

• Order-of magnitude sensitivity limits• Error in ∆ptop = ±10-2 MPa, ∆pbot ≤ 10 MPa

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Estimation of Sensitivity Limits

• Error in field data – ∆ptop/∆pbot = ±10-3

• Viable range of values – minimum pressure that can

be measured reliably

• Insensitive response regions– Slope of curve is flat

– Small error in ∆ptop translates to large uncertainty in kw

Viable range of values

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Range of Detection

range ofdetection

10 3 d ptop pbot

d kw k

1

1

kw k

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Alternative Test Design

• Purpose– Reduce influence of

lower formation permeability on pressure response

– Expand range of detection

• Move perforations to location within intermediary caprock

• Repeat numerical experiments

intermediary caprock

lower formation

upper formation

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Modified Test Results

k=10-2 Dk= 1 D

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Improved Range of Detection

range ofdetection

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Conclusion

• There is a lack of meaningful data available for well properties.

• A simple downhole pressure test can identify effective well permeability values that are in the critical range of values.

• Field experiments are needed to reduce the uncertainty associated with current estimates of CO2 leakage.

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Thank you!