1887
Volume 16, Issue 6
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

The estimation of hydraulic parameters is critical for the rational use of water resources and the development of reliable hydrogeological models. However, the cost of such estimation can be very high and the data are limited to the area near the pumping well. For this reason, complementary methods for estimating hydraulic conductivity and transmissivity have become increasingly important in recent years, such as the adjustment of empirical relationships between geoelectrical and hydraulic parameters. In this paper, two linear relationships were tested, combining resistivity measurements from well logging profiles and hydraulic conductivity values from pumping test data, in a semi‐confined fluvial aquifer in the province of Buenos Aires, Argentina. Furthermore, these relationships were used to obtain two‐dimensional (2D) hydraulic conductivity and transmissivity sections from electrical resistivity tomography using a high‐definition electrode array. Predicted values were compared with traditional pumping test in a near well showing very good agreement with both methods. Results showed that it would be possible to quantify the 2D variation of hydraulic parameters in aquifers and to identify high‐ or low‐productivity areas. By knowing this information in advance, it is possible to reduce the number of failures or unexpected results when drilling a well. These 2D sections also provide additional information about hydraulic parameters and their lateral variability, and can improve hydrogeological models without drilling new wells.

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/content/journals/10.1002/nsg.12020
2018-11-13
2024-04-23
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References

  1. ArchieG.E.1942. The electrical resistivity log as an aid in determining some reservoir characteristics. Transactions of the American Institute Mining, Metallurgical and Petroleum Engineers146, 54–62.
    [Google Scholar]
  2. AugeM.2005. Hidrogeología de La Plata, Provincia de Buenos Aires. In: Relatorio del XVI Congreso Geológico Argentino (eds R.E.de Barrio , R.O.Etcheverry , M.F.Caballé and E.Llambías ) pp.293–312. Quick Press, La Plata.
    [Google Scholar]
  3. AugeM., HirataR. and López VeraF.2004. Vulnerabilidad a la contaminación por nitratos del acuífero Puelche en La Plata Argentina. Centro de Estudios de América Latina. Buenos Aires. http://www.bfa.fcnym.unlp.edu.ar/catalogo/doc_num.php?explnum_id=239
    [Google Scholar]
  4. BohlingG.C. and ButlerJ.J.Jr. 2010. Inherent limitations of hydraulic tomography. Groundwater48, 809–824.
    [Google Scholar]
  5. CaminosR.1999. Geología Argentina. Buenos Aires. Instituto de Geología y Recursos Minerales. SEGEMAR. ISSN 0328–2325.
  6. CarmanP.C.1937. Fluid flow through granular beds. Transactions of the Institution of Chemical Engineers15, 415–421.
    [Google Scholar]
  7. CaterinaD., BeaujeanJ., RobertT. and NguyenF.2013. A comparison study of image different appraisal tools for electrical resistivity tomography. Near Surface Geophysics11, 639–657.
    [Google Scholar]
  8. ChandraS., AhmedS., RamA. and DewandelB.2008. Estimation of hard rock aquifers hydraulic conductivity from geoelectrical measurements: a theoretical development with field application. Journal of Hydrology357, 218–227.
    [Google Scholar]
  9. ChenJ., HubbardS.S. and RubinY.2001. Estimating the hydraulic conductivity at the South Oyster Site from geophysical tomographic data using Bayesian techniques based on the normal linear regression model. Water Resources Research37, 1603–1613.
    [Google Scholar]
  10. ChooH., KimJ., LeeW. and LeeC.2016. Relationship between hydraulic conductivity and formation factor of coarse‐grained soils as a function of particle size. Journal of Applied Geophysics127, 91–101.
    [Google Scholar]
  11. ClennellM.B.1997. Tortuosity: a guide through the maze. In: Developments in Petrophysics: Geological Society, Vol. 122 (eds M.A.Lovell and P.K.Harvey ) pp. 299–344. Geological Society, London.
    [Google Scholar]
  12. CostaA.2006. Permeability‐porosity relationship: a reexamination of the Kozeny‐Carman equation based on a fractal pore‐space geometry assumption. Geophysical Research Letters33, L02318.
    [Google Scholar]
  13. CrestaniE., CamporeseM and SalandinP.2015. Assessment of hydraulic conductivity distributions through assimilation of travel time data from ERT‐monitored tracer tests. Advances in Water Resources84, 23–36.
    [Google Scholar]
  14. deGroot‐HedlinC. and ConstableS.1990. Occam's inversion to generate smooth, two‐dimensional models for magnetotelluric data. Geophysics55, 1613–1624.
    [Google Scholar]
  15. DhakateR. and SinghV.S.2005. Estimation of hydraulic parameters from surface geophysical methods, Kaliapani Ultramafic complex, Orissa, India. Journal of Enviromental Hydrology13, 1–11.
    [Google Scholar]
  16. Di MaioR., PiegariE., ToderoG., and FabbrocinoS.2015. A combined use of Archie and van Genuchten models for predicting hydraulic conductivity of unsaturated pyroclastic soils. Journal of Applied Geophysics112, 249–255.
    [Google Scholar]
  17. DriscollF.G.1989. Groundwater and Wells , 2nd edn. Johnson Screens.
  18. FarzamianM., Monteiro SantosF.A. and Khalil, M.A.2015. Estimation of unsaturated hydraulic parameters in sandstone using electrical resistivity tomography under a water injection test. Journal of Applied Geophysics121, 71–83.
    [Google Scholar]
  19. FittsC.R.2002. Groundwater Science. Academic Press.
    [Google Scholar]
  20. FreezeR.A. and CherryJ.A.1979. Groundwater. Prentice‐Hall Inc.
    [Google Scholar]
  21. GomezC.T., DvorkinJ. and VanorioT.2010. Laboratory measurements of porosity, permeability, resistivity and velocity on Fontainebleau sandstones. Geophysics75, E191–E204.
    [Google Scholar]
  22. HeigoldP.C., GilkesonR.H., CartwrightK. and ReedP.C.1979. Aquifer transmissivity from surficial electrical methods. Groundwater17, 338–345.
    [Google Scholar]
  23. HeinzJ., KleinedamS., TeutschG., and AignerT.2003. Heterogeineity patterns of Quaternary glaciofluvial gravel bodies (SW Germany): application to hydrogeology, Sedimentary Geology158, 1–23.
    [Google Scholar]
  24. HochstetlerD.L., BarrashW., LevenC., CardiffM., ChidichimoF. and KitanidisP.K.2016. Hydraulic tomography: continuity and discontinuity of high‐K and low‐K zones. Groundwater54, 171–185.
    [Google Scholar]
  25. IrvingJ and SinghaK. 2010. Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities. Water Resources Research46, W11514.
    [Google Scholar]
  26. JacksonP.D., Taylor SmithD. and StanfordP.N.1978. Resistivity‐porosity‐particle shape relationships for marine sands. Geophysics43, 1250–1268.
    [Google Scholar]
  27. JonesP.H. and BufordT.B.1951. Electric logging applied to groundwater exploration. Geophysics16, 115–139.
    [Google Scholar]
  28. KellyW.E.1977. Geoelectric sounding for estimating aquifer hydraulic conductivity. Groundwater15, 420–425.
    [Google Scholar]
  29. KhalilM.A., RamalhoE.C. and Monteiro SantosF.A.2011. Using resistivity logs to estimate hydraulic conductivity of a Nubian sandstone aquifer in southern Egypt. Near Surface Geophysics9, 349–355.
    [Google Scholar]
  30. KozenyJ.1927. Ueber kapillare Leitung des Wassers im Boden. Sitzungsber Akademie der Wissenschaften136, 271–306.
    [Google Scholar]
  31. KozenyJ.1953. Hydraulik. Springer‐Verlag.
    [Google Scholar]
  32. LokeM.H.1999. RES2DMOD ver 2.2: Rapid 2D resistivity forward modelling using the finite‐difference and finite‐element methods, Geotomo Software, Penang, Malaysia. (https://www.geotomosoft.com).
  33. LokeM.H.2006. RES2DINV ver. 3.50, Rapid 2‐D resistivity and IP inversion using the least square method, Geotomo Software, Penang, Malaysia. (https://www.geotomosoft.com).
  34. LokeM.H.2015. Tutorial: 2D and 3D electrical imaging surveys, Geotomo Software, Penang, Malaysia. (https://www.geotomosoft.com).
  35. LokeM.H. and BarkerR.D.1996. Rapid least‐squares inversion of apparent resistivity pseudosections by a quasi‐Newton method. Geophysical Prospecting44, 131–152.
    [Google Scholar]
  36. MailletR.1947. The fundamental equation of electrical prospecting. Geophysics12, 529–556.
    [Google Scholar]
  37. MassoudU., SantosF., KhalilM.A., TahaA. and AbbasA.M.2010. Estimation of aquifer hydraulic parameters from surface geophysical measurements: a case study of the Upper Cretaceous aquifer, central Sinai, Egypt. Hydrogeology Journal18, 699–710.
    [Google Scholar]
  38. MazáčO., KellyW.E. and LandaI.1985. A hydrogeophysical model for relations between electrical and hydraulic properties of aquifers. Journal of Hydrology79, 1–19.
    [Google Scholar]
  39. MesgouezA., BuisS., RuyS. and Lefeuve‐MesgouezG.2014. Uncertainty analysis and validation of the estimation of effective hydraulic properties at the Darcy scale. Journal of Hydrology512, 303–314.
    [Google Scholar]
  40. MilschH., BlöcherG. and EngelmannS.2008. The relationship between hydraulic and electrical transport properties in sandstone: An experimental evaluation of several scaling models. Earth and Planetary Science Letters, 275, 355–363.
    [Google Scholar]
  41. MorinR.H.2006Negative correlation between porosity and hydraulic conductivity in sand‐and‐gravel aquifers at Cape Cod, Massachusetts, USA. Journal of Hydrology316, 43–52. https://doi.org.10.1016/j.jhydrol.2005.04.013
    [Google Scholar]
  42. NiwasS. and CelikM.2012. Equation estimation of porosity and hydraulic conductivity of Ruhrtal aquifer in Germany using near surface geophysics. Journal of Applied Geophysics84, 77–85. https://doi.org.10.1016/j.jappgeo.2012.06.001
    [Google Scholar]
  43. NiwasS. and SinghalD.C.1981. Estimation of aquifer transmissivity from Dar‐Zarrouk parameters in porous media. Journal of Hydrology50, 393–399.
    [Google Scholar]
  44. NiwasS., TezkanB. and IsrailM.2011. Aquifer hydraulic conductivity estimation from surface geoelectrical measurements for Krauthausen test site, Germany. Hydrogeology Journal19, 307–315.
    [Google Scholar]
  45. PurvanceD.T. and AndricevicR.2000. On the electrical‐hydraulic conductivity correlation in aquifers. Water Resources Research36, 2905–2913.
    [Google Scholar]
  46. RevilA. and CathlesL.M.III1999. Permeability of shaly sands. Water Resources Research35, 651–662.
    [Google Scholar]
  47. RevilA., KaraoulisM., JohnsonT. and KemnaA.2012. Review: Some low‐frequency electrical methods for subsurface characterization and monitoring in hydrogeology. Hydrogeology Journal20, 617–658.
    [Google Scholar]
  48. RubinY.2003. Applied Stochastic Hydrogeology. Oxford University Press.
    [Google Scholar]
  49. RuggeriP., GloaguenE., LefebvreR., IrvingJ. and HolligerK.2014. Integration of hydrological and geophysical data beyond the local scale: application of Bayesian sequential simulation to field data from the Saint‐Lambert‐de‐Lauzon site, Québec, Canada. Journal of Hydrology514, 271–280.
    [Google Scholar]
  50. RuggeriP., IrvingJ., GloaguenE. and HolligerK.2013. Regional–scale integration of multiresolution hydrological and geophysical data using a two‐step Bayesian sequential simulation approach. Geophysical Journal International194, 289–303.
    [Google Scholar]
  51. ShevninV., Delgado‐RodriguezO., MousatovA. and RyjovA.2006. Estimation of hydraulic conductivity on clay content in soil determined from resistivity data. Geofísica Internacional45, 195–207.
    [Google Scholar]
  52. SinghK.P.2005. Nonlinear estimation of aquifer parameters from surfficial resistivity measurements. Hydrology and Earth System Sciences Discussions2, 917–938.
    [Google Scholar]
  53. SinhaR., IsrailM. and SinghalD. C.2009. A hydrogeophysical model of the relationship between geoelectric and hydraulic parameters of anisotropic aquifers. Hydrogeology Journal17, 495–503.
    [Google Scholar]
  54. SlaterL.2007. Near surface electrical characterization of hydraulic conductivity: from petrophysical properties to aquifer geometries ‐ A review. Surveys in Geophysics28, 169–197.
    [Google Scholar]
  55. SoupiosP.M., KouliM., ValianatosF., VafidisA. and StavroulakisG.2007. Estimation of aquifer hydraulic parameters from surficial geophysical methods: a case study of Keritis Basin in Chania (Crete‐Greece). Journal of Hydrology338, 122–131.
    [Google Scholar]
  56. Taheri TizroA., VoudourisK. and BasamiY.2012. Estimation of porosity and specific yield by application of geoelectrical method – A case study in western Iran. Journal of Hydrology454–455, 160–172.
    [Google Scholar]
  57. TheisC.V.1935The relation between the lowering of the piezometric surface and the rate and duration of discharge of a well using groundwater storage. Transactions American Geophysical Union16, 519–524.
    [Google Scholar]
  58. UrishD.W.1981. Electrical resistivity‐hydraulic conductivity relationships in glacial outwash aquifers. Water Resources Research17, 1401–1408.
    [Google Scholar]
  59. WildenschildD., RobertsJ.J., and CarlbergE.D.2000. On the relationship between microstructure and electrical and hydraulic properties of sand‐clay mixtures. Geophysical Research Letters27, 3085–3088.
    [Google Scholar]
  60. WorthingtonP.F.1993. The uses and abuses of the Archie equations, 1: the formation factor‐porosity relationship. Journal of Applied Geophysics30, 215–228.
    [Google Scholar]
  61. YehT.‐C. J. and LiuS.2000. Hydraulic tomography: development of a new aquifer test method. Water Resources Research36, 2095–2105.
    [Google Scholar]
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  • Article Type: Research Article
Keyword(s): Aquifer; ERT; Hydraulic conductivity; Hydraulic transmissivity; Hydrogeology

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