1887

Abstract

Summary

Estimating groundwater storage volumes is important for assessing the potential capacity and recovery efficiencies of Managed Aquifer Recharge (MAR) strategies. However, such storage estimates are challenging, particularly in areas of poor data density. This challenge faced the Broken Hill Managed Aquifer Recharge (BHMAR) project tasked with assessing groundwater options in the Darling River floodplain, NSW, Australia. Within the ~7500 km2 area, 14 fresh groundwater zones were identified with AEM and a workflow was developed to estimate the groundwater volumes in these targets.

Pore fluid sampling from sonic core provided the opportunity to develop simple AEM conductivity thresholds to produce surrogate groundwater salinity maps for each AEM depth slice. Combining the AEM data with other project datasets such as downhole geophysics, detailed sonic-core logging and laboratory analyses facilitated the mapping of hydrostratigraphy, textural classes and saturation within AEM depth slices, which were then used to calculate bulk aquifer volumes. Nuclear magnetic resonance (NMR) free-water statistics were used in effective porosity estimates, to calculate groundwater volumes.

Although preliminary, the volume estimates were essential in the identifying, prioritising, interpreting and reporting of groundwater resource targets during the project and to make recommendations for future phases of investigation.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201413729
2015-09-06
2024-04-25
Loading full text...

Full text loading...

References

  1. Archie, G.E.
    [1942] The electrical resistivity log as an aid in determining some reservoir characteristics. Transactions American Institute of Mechanical Engineers, 146, 54–67.
    [Google Scholar]
  2. BussianA.E.
    [1983] Electrical conductance in a porous medium. Geophysics, 48, 1258–1268.
    [Google Scholar]
  3. Jin, G., Torres-Verdín, C., Devarajan, S., Toumelin, E. and Thomas, E.C.
    [2007] Pore-scale analysis of the Waxman-Smits shaly-sand conductivity model. Petrophysics, 48, 104–120.
    [Google Scholar]
  4. Kennedy, D.
    [2007] The porosity-water saturation-conductivity relationship: An alternative to Archie’s Model. Petrophysics, 48(5), 335–261.
    [Google Scholar]
  5. Lawrie, K.C., BrodieR.S., Tan, K.P., Gibson, D., Magee, J.W., Clarke, J.D.A., Halas, L., Gow, L., Somerville, P., Apps, H.E., Christensen, N.B., Brodie, R.C., Abraham, J., Smith, M., Page, D., Dillon, P., Vanderzalm, J., Miotlinski, K., Hostetier, S., Davis, A., Ley-Cooper, A.Y., Schoning, G., Barry, K. and Levett, K.
    [2012] BHMAR Project: Data acquisition, processing, analysis and interpretation methods. Geoscience Australia Record 2012/11. Geocat 73819.
    [Google Scholar]
  6. NHMRC-NRMMC
    NHMRC-NRMMC. [2011] Australian Drinking Water Guidelines, Paper 6 National Water Quality Management Strategy. National Health and Medical Research Council, National Resource Management Ministerial Council, Commonwealth of Australia, Canberra.
    [Google Scholar]
  7. Sen, P.N., Goode, P.A. and Sibbit, A.M.
    [1988] Electrical conduction in clay bearing sandstones at low and high salinities. Journal of Applied Physics, 63, 4832–4840.
    [Google Scholar]
  8. Waxman, M.H. and Smits, L.J.M.
    [1968] Electrical conductivities in oil-bearing shaly sands. Transactions American Institute Mining Petroleum Engineers, 243(2), 107–122.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201413729
Loading
/content/papers/10.3997/2214-4609.201413729
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error