A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

Gordon Osterman, Kristina Keating, Andrew Binley, Lee Slater

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

We estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multisalinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty-five sandstone cores collected from fifteen different formations, we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time R2 of 0.69 and 0.33 and normalized root mean square errors (NRMSE) of 0.16 and 0.21, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE=0.23). We demonstrate that that permeability estimates from the joint-NMR-CC model (NRMSE=0.13) compare favorably to estimates from the Katz and Thompson model (NRMSE=0.074). This model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.

Original languageEnglish (US)
Pages (from-to)4321-4337
Number of pages17
JournalWater Resources Research
Volume52
Issue number6
DOIs
StatePublished - Jun 1 2016

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

Keywords

  • complex conductivity
  • induced polarization
  • nuclear magnetic resonance
  • permeability

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