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Article . 2021
License: CC BY NC ND
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Article . 2021
License: CC BY NC ND
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Calibrating BMR T2 Distribution logs to well test data

Authors: Keelan O'Neill; Reyes, Mario; Birt, Benjamin; Hopper, Timothy;

Calibrating BMR T2 Distribution logs to well test data

Abstract

Sustainable groundwater management plans are of critical importance to the future of increasingly scarce water resources. Borehole magnetic resonance (BMR) is a wireline logging technique used to provide in-situ formation evaluation. BMR can be utilised to monitor BMR responds to both the volumes of fluids present in a rock, and the geometry of the pores in which this water resides. As such, it is a powerful addition to any borehole geophysical characterisation aimed at evaluating the storage and flow capacity of subsurface formation or aquifer. BMR is highly advantageous due to its ability to provide a lithology independent measurement of formation porosity. A further application of BMR is to estimate the formation permeability. Semi-empirical models have been developed which quantify the relationship between the pore size distribution captured using BMR and formation permeability. The parameters which are used within these models are formation dependent. Thus, the parameters must be calibrated to the geology of interest to ensure that the BMR permeability model is tuned to provide appropriate permeability estimates. Historically this has been through coring programs, however this is often not available in a hydrogeological context due ability to retrieve core in unconsolidated formations. This paper reviews a process that uses a combination of packer tests, pump tests and lugeon tests to calibrate the coefficients to calculate hydraulic conductivity from a T2 distribution. The process will be discussed and its applications to set of data will be presented.

Open-Access Online Publication: March 03, 2023

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Keywords

magnetic resonance, groundwater, aquifer test, hydrogeology., hydraulic conductivity

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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