On Permeability Prediction From Complex Conductivity Measurements Using Polarization Magnitude and Relaxation Time
Abstract
Geophysical length scales determined from complex conductivity (CC) measurements can be used to estimate permeability when the electrical formation factor F is known. Two geophysical length scales have been proposed: (1) the specific polarizability normalized by the imaginary conductivity and (2) the time constant multiplied by a diffusion coefficient . The parameters and account for the control of fluid chemistry and/or varying minerology on the geophysical length scale. We evaluated the predictive capability of two CC permeability models: (1) an empirical formulation based on or normalized chargeability and (2) a mechanistic formulation based on . The performance of the CC models was evaluated against measured ; and further compared against that of well‐established estimation equations that use geometric length scales. Both CC models predict permeability within one order of magnitude for a database of 58 sandstone samples, with the exception of samples characterized by high pore volume normalized surface area . Variations in and likely contribute to the poor model performance for the high samples, which contain significant dolomite. Two observations favor the implementation of the ‐based model over the ‐based model for field‐scale estimation: (1) a limited range of variation in relative to and (2) field measurements are less time consuming to acquire relative to . The need for a reliable field‐estimate of limits application of either model, in particular the model due to a high power law exponent associated with .
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 01, 2018
- Source ID
- 10.1002/2017wr022034
Entities
People
- Andreas Weller
- Beth L. Parker
- Carla Rose
- J. Robinson
- Kristina Keating
- Lee D. Slater
- Tonian Robinson
Organizations
- Clausthal University of Technology
- Pacific Northwest National Laboratory
- Rutgers University
- United States Army Corps of Engineers
- University of Guelph