An alternative approach using electrical well logging for estimating porosity and hydraulic conductivity in volcanic aquifers of the upper Awash River sub-basin, Ethiopia
A. Muauz, B. Berehanu, H. Bedru
Journal of Hydrology: Regional Studies · 2025
doi:10.1016/j.ejrh.2025.102547 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Study region: Upper Awash River sub-basin, Ethiopia Study focus: This study introduces an alternative method for characterizing volcanic aquifers using electrical well logging to estimate porosity and hydraulic conductivity. Integrating resistivity data with Archie’s law and the Kozeny–Carman equation, it provides a practical approach for evaluating aquifer properties in complex terrains. Analysis involved data from 335 wells, including resistivity logs, gamma logs, 1230 water quality samples, and 290 wells with lithological and pumping test records, addressing challenges faced by conventional techniques in volcanic regions. New insights for the region: The study revealed apparent and intrinsic formation factors for basalt, tuff, and ignimbrite, which were applied to the Humble equation to estimate porosity, yielding values between 10.02 % and 23.14 %. Hydraulic conductivity, calculated using the Kozeny–Carman equation, ranged from 2.4 to 33.1 m/day. Validation through conventional pumping tests across seven sub-regions demonstrated strong alignment, with hydraulic conductivity values of 5.3 m/day (A), 2.8 m/day (B), 33.1 m/day (C), 4.6 m/day (D), 2.4 m/day (E), 8.1 m/day (F), and 6.2 m/day (G). Pumping test ranges of 0.2–63.6 m/day further corroborated the findings. This study underscores the potential of resistivity well logging as a cost-effective, efficient alternative for characterizing hydraulic properties in volcanic aquifers. It offers critical new insights for sustainable groundwater management in geologically complex regions, providing a replicable framework for similar settings worldwide.
Abstract licence: CC BY-NC
References16
16 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.