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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
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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 • Use numerical analysis to determine the feasibility of this test • Define the range of detection given constraints on instrument accuracy
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.
Existing Oil and Gas Wells End of 2004 From IPCC SRCCS, 2005
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
Disturbed zone, kw Experimental Design
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) Fixed pressure B.C. Permeable formations Shale layers Disturbed zone, kw Intermediary caprock, k’ z Lower formation, k 0.5 m rB r
range of detection Example Numerical Results Transient data Steady-state data
k=10-2 D k= 1 D Dimensionless Results
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 = ±10-2MPa, ∆pbot ≤ 10 MPa
Viable range of values 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
Range of Detection range of detection
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
k=10-2 D k= 1 D Modified Test Results
range of detection Improved Range of Detection
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.