Abstract
AbstractPumped flowing fluid electrical conductivity (FFEC) logs, also known as pumped borehole dilution testing, is an experimentally easy‐to‐perform approach to evaluating vertical variations in the hydraulic conductivity of an aquifer. In contrast to the simplicity of the logging equipment, analysis of the data is complex and laborious. Current methods typically require repeated solution of the advection‐dispersion equation (ADE) for describing the flow in the borehole and comparison with the experimental results. In this paper, we describe a direct solution for determining borehole fluid velocity that bypasses the need for complex numerical computation and repetitive optimization. The method rests on the observation that, while solving the ADE for concentration profile in the borehole (as required for modeling and combined methods) is computationally challenging, the solution for flow distribution along the length of the borehole given concentration data is straightforward. The method can accommodate varying borehole diameters, and uses the fact that multiple profiles are taken in the standard logging approach to reduce the impact of noise. Data from both a simulated borehole and from a field test are successfully analyzed. The method is implemented in a spreadsheet, which is available as supporting information material to this paper.
Highlights
Characterizing the variations in hydraulic conductivity is a critical step in the development of groundwater flow models
Horizontal variations in transmissivity can be characterized through hydraulic tests in multiple boreholes over the area, but vertical variations in hydraulic conductivity usually remain poorly characterized, and are the focus of this study
This paper presents a method for interpreting single-borehole dilution-testing data that is objective and does not rely on a priori knowledge of the likely hydraulic conductivity profile
Summary
Characterizing the variations in hydraulic conductivity is a critical step in the development of groundwater flow models. Evans [1995] built on the success of BORE by using less computationally expensive algorithms and making allowances for the time lag between measurements taken at the top of the borehole and the bottom His code performs a least squares fit to an observed data set, cutting out the time consuming trial and error required to calibrate models. Easier to use than the modeling method, signature methods use simplified approaches derived from physical insights or truncated versions of the ADE They can only be applied to sections of the log that can be assumed to behave in some idealized manner, such as a long borehole with isolated inflows.
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