Transmissivity identification through multi-directional aquifer stimulation

This paper presents a geostatistical approach to multi-directional aquifer stimulation in order to better identify the transmissivity field. Hydraulic head measurements, taken at a few locations but under a number of different steady-state flow conditions, are used to estimate the transmissivity. Well installation is generally the most costly aspect of obtaining hydraulic head measurements. Therefore, it is advantageous to obtain as many informative measurements from each sampling location as possible. This can be achieved by hydraulically stimulating the aquifer through pumping, in order to set-up a variety of flow conditions. We illustrate the method by applying it to a synthetic aquifer. The simulations provide evidence that a few sampling locations may provide enough information to estimate the transmissivity field. Furthermore, the innovation of, or new information provided by, each measurement can be examined by looking at the corresponding spline and sensitivity matrix. Estimates from multi-directional stimulation are found to be clearly superior to estimates using data taken under one flow condition. We describe the geostatistical methodology for using data from multi-directional simulations and address computational issues.     

Transmissivity identification through multi-directional aquifer stimulation

This paper presents a geostatistical approach to multi-directional aquifer stimulation in order to better identify the transmissivity field. Hydraulic head measurements, taken at a few locations but under a number of different steady-state flow conditions, are used to estimate the transmissivity. Well installation is generally the most costly aspect of obtaining hydraulic head measurements. Therefore, it is advantageous to obtain as many informative measurements from each sampling location as possible. This can be achieved by hydraulically stimulating the aquifer through pumping, in order to set-up a variety of flow conditions. We illustrate the method by applying it to a synthetic aquifer. The simulations provide evidence that a few sampling locations may provide enough information to estimate the transmissivity field. Furthermore, the innovation of, or new information provided by, each measurement can be examined by looking at the corresponding spline and sensitivity matrix. Estimates from multi-directional stimulation are found to be clearly superior to estimates using data taken under one flow condition. We describe the geostatistical methodology for using data from multi-directional simulations and address computational issues.     

New Method for Continuous Transmissivity Profiling in Fractured Rock

A new method is presented to search for hydraulically transmissive features in open boreholes in bedrock. A flexible borehole liner made of a watertight, nylon fabric is filled with water to create a constant driving head to evert (reverse of invert) the liner down the hole so that the liner pushes the borehole water out into transmissive fractures or other permeable features. The descent rate is governed by the bulk transmissivity of the remaining permeable features below the liner. Initially, the liner descent rate or velocity is a measure of transmissivity (T) of the entire hole. As the everting liner passes and seals each permeable feature, changes in the liner velocity indicate the position of each feature and an estimate of T using the Thiem equation for steady radial flow. This method has been performed in boreholes with diameters ranging from 96 to 330 mm. Profiling commonly takes a few hours in holes 200‐ to 300‐m long. After arrival of the liner at the bottom of the hole, the liner acts as a seal preventing borehole cross connection between transmissive features at different depths. Liner removal allows the hole to be used for other purposes. The T values determined using this method in a dolostone aquifer were found to be similar to the values from injection tests using conventional straddle packers. This method is not a replacement for straddle‐packer hydraulic testing of specific zones where greater accuracy is desired; however, it is effective and efficient for scanning entire holes for transmissive features.     

The attenuation anisotropy of mudstones and shales in subsurface formations

The energy of elastic waves attenuates graduallywhen propagating in anelastic media. The absorptionof P- and S-waves in rocks strongly depends on rocks’physical properties and saturation conditions. With thechange of physical conditions of rocks, the attenuationof wave energy is more sensitive than the change of itsvelocity, so it carries more information about therock’s physical property compared with the latter.Hauge et al.[1―3] determined the lithology of subsur-face formations by their…     

Measuring a Low Horizontal Hydraulic Gradient in a High Transmissivity Aquifer

High transmissivity aquifers typically have low hydraulic gradients (i.e., a flat water table). Measuring low gradients using water levels can be problematic because measurement error may be greater than the true difference in water levels (i.e., a low signal-to-noise ratio). In this study, the feasibility of measuring a hydraulic gradient in the range of 10⁻⁶ to 10⁻⁵ m/m was demonstrated. The study was performed at a site where the depth to water from land surface ranged from 40.1 to 94.2 m and the aquifer transmissivity was estimated at 41,300 m²/d (hydraulic conductivity of 18,800 m/d). The goals of the study were to reduce measurement error as much as practicable and assess the importance of factors affecting water level measurement accuracy. Well verticality was the largest source of error (0.000 to 0.168 m; median of 0.014 m), and geodetic survey of casing elevations was the next most important source of error (0.002 to 0.013 m; median of 0.005 m). Variability due to barometric pressure fluctuations was not an important factor at the site. Hydraulic heads were measured to an accuracy of ±0.0065 m, and the average hydraulic gradient was estimated to be 8.0 × 10⁻⁶ (±0.9 × 10⁻⁶) m/m. The improvement in accuracy allowed for two reversals in the groundwater flow direction to be identified, after which the gradient averaged 2.5 × 10⁻⁵ (±0.4 × 10⁻⁵) m/m. This study showed it is possible to sufficiently control sources of error to measure hydraulic gradients in the 10⁻⁶ to 10⁻⁵ m/m range.