SURFACE NMR AQUIFER PROPERTY MAPPING IN THE HIGH PLAINS AQUIFER

Abstract

Within the High Plains Aquifer, understanding groundwater resources and their management are growing in importance to society as groundwater resources are stressed by drought and continued development. To minimize conflicts, tools and techniques need to be applied to support knowledge-based decisions and management. Traditionally, point data, such as borehole logs, borehole geophysics, surface geophysics, and aquifer tests were interpolated over long distances to create hydrogeologic frameworks. These methods have enjoyed a long history of being the best available technology to inform our understanding of groundwater and how it moves. However, the critical and challenging measurements in characterizing aquifers include effective porosity and hydraulic conductivity. Typically, aquifer properties are derived by lithological comparisons with published data; direct measurements of hydraulic conductivity acquired by a few constant head aquifer tests or slug tests; and expensive and time consuming laboratory measurements of cores which can be biased by sampling and the difficulty of making measurements on unconsolidated materials. Aquifer tests are considered to be the best method to gather information on hydraulic conductivity but are rare because of cost and difficult logistics. Also they are unique in design and interpretation from site to site. Nuclear Magnetic Resonance (NMR) can provide a direct measurement of the presence of water in the pore space of aquifer materials. Within areas of the High Plains Aquifer effective porosity values were derived directly from surface NMR data, and hydraulic conductivity values were calculated using empirical relationships calibrated and verified with aquifer tests. Unlike aquifer tests, NMR logs are not unique in design and are applied in similar fashion from borehole to borehole providing a standard way of measuring hydraulic properties. When the hydraulic properties from the NMR are integrated with hydrogeological framework large areas can be characterized. This allows a much more robust method for conceptualizing groundwater models then simply using previously published data for assigning effective porosity and hydraulic conductivity.