Permeability Estimation Directly From Logging‐While‐Drilling Induced Polarization Data

Abstract

In this study, we present the prediction of permeability from time domain spectral induced polarization (IP) data, measured in boreholes on undisturbed formations using the El‐log logging‐while‐drilling technique. We collected El‐log data and hydraulic properties on unconsolidated Quaternary and Miocene deposits in boreholes at three locations at a field site in Denmark, characterized by different electrical water conductivity and chemistry. The high vertical resolution of the El‐log technique matches the lithological variability at the site, minimizing ambiguity in the interpretation originating from resolution issues. The permeability values were computed from IP data using a laboratory‐derived empirical relationship presented in a recent study for saturated unconsolidated sediments, without any further calibration. A very good correlation, within 1 order of magnitude, was found between the IP‐derived permeability estimates and those derived using grain size analyses and slug tests, with similar depth trends and permeability contrasts. Furthermore, the effect of water conductivity on the IP‐derived permeability estimations was found negligible in comparison to the permeability uncertainties estimated from the inversion and the laboratory‐derived empirical relationship.

Cross-borehole tomography with full-decay spectral time-domain induced polarization for mapping of potential contaminant flow-paths

“…This potential of the IP method for mapping sand/clay structures below the water table has been evaluated in this study through synthetic modelling, but field verifications are needed for fully establishing the IP method for mapping potential flow-paths of contamination below water table. However, it is important to note that the approach presented in Maurya et al (2018a) and Fiandaca et al (2018b) for mapping intrinsic permeability, or its counterpart the hydraulic permeability, could be used in cross-borehole imaging in saturated media, opening the way for quantitative prediction of water flow and contaminant transport. Above the water table, mapping permeability is more difficult because a good estimate of saturation with depth is needed.…”

“…Gazoty et al 2012b, Rossi et al 2017), permeability estimation (e.g. Fiandaca et al 2018b, time-lapse monitoring of CO2 injection (e.g. Doetsch et al 2015a and active layer dynamics (e.g.…”

Geophysics‐Based Contaminant Mass Discharge Quantification Downgradient of a Landfill and a Former Pharmaceutical Factory

“…Fiandaca et al () have shown that the and parameters are strongly correlated in the inversion of IP data, and suggest reparameterization of the Cole‐Cole model to improve parameter resolution, for instance by using the maximum imaginary conductivity as the inversion parameter instead of . Furthermore, by enforcing the proportionality between and of equation at the frequency , it is possible to define the Bulk and (maximum) Imaginary Conductivity (BIC) Cole‐Cole reparameterization (Fiandaca et al, ; Maurya et al, ) as follows: …”

“…Thus, the changes in the groundwater flow field at the site will have a lower impact on the contaminant mass discharge than the distribution of contaminant concentrations. The recent works of Weller et al (2015), Fiandaca et al (2018b), and Maurya et al (2018), suggest that induced polarization data can reproduce the spatial distribution of hydraulic conductivities. Therefore, it may be possible to generalize the results of this study to more heterogeneous settings.…”

“…This study aims to develop a novel method for describing the distribution of contaminant concentration by integrating geophysical and chemical data using regression kriging. Specifically, DCIP data were used for imaging the spatial distribution of the bulk conductivity, after removing the effect of the surface conductivity (Fiandaca et al, ; Maurya et al, ). When combined with additional knowledge on groundwater flow, the geophysics‐based method should be beneficial compared to the traditional approach of using only concentration data from multilevel samplers (termed the concentration‐based approach) for contaminant mass discharge estimation from large and heterogeneous sources.…”