Tracer Tests in flooded underground mines
Tracer tests are a common means to investigate the hydrogeological conditions in the hydrosphere. Nevertheless, only few successful tracer tests in flooded underground mines have been described. In two flooded German underground mines tracer tests with club moss spores (Lycopodium clavatum) and microspheres had been conducted by the use of the LydiA technique. Both times, effective velocities between 1 and 8 m min could be calculated and a good hydraulic connection between the mines’ parts investigated could be proved. Lycopodium Apparatus (LydiA)
Tracing Ground‐Water Movement in Abandoned Coal Mined Aquifers Using Fluorescent Dyes
In shallow, essentially free-draining abandoned coal mine workings, quantitative ground-water tracing using the orange fluorescent dye Sulpho Rhodamine B (CI 45100) provides a powerful hydrogeological tool for determining ground-water flow regimes. However, this is not the case in deep, confined, abandoned coal mine workings where various dyes exhibit a nonconservative behavior due to adsorption onto ferric hydroxide deposits. This is a more significant problem than that of the effects of pH or acidity on fluorescence. Laboratory tests indicate that dyes with sulphonic functional groups should be selected in such situations and that dye concentrations need to be maintained at the highest level commensurate with aesthetic and toxicological conditions.
Predicting the gas resource potential in reservoir C-sand interval of Lower Goru Formation, Middle Indus Basin, Pakistan
Abstract The integrated study of seismic attributes and inversion analysis can provide a better understanding for predicting the hydrocarbon-bearing zones even in extreme heterogeneous reservoirs. This study aims to delineate and characterize the gas saturated zone within the reservoir (Cretaceous C-sand) interval of Sawan gas field, Middle Indus Basin, Pakistan. The hydrocarbon bearing zone is well identified through the seismic attribute analysis along a sand channel. The sparse-spike inversion analysis has efficiently captured the variations in reservoir parameter (P-impedance) for gas prospect. Inversion results indicated that the relatively lower P-impedance values are encountered along the predicted sand channel. To further characterize the reservoir, geostatistical techniques comprising multiattribute regression and probabilistic neural network (PNN) analysis are applied to predict the effective porosity of reservoir. Comparatively, the PNN analysis predicted the targeted property more efficiently and applied its estimations on entire seismic volume. Furthermore, the geostatistical estimations of PNN analysis significantly predicted the gas-bearing zones and confirmed the sand channel as a major contributor of gas accumulation in the area. These estimates are in appropriate agreement with each other, and the workflow adopted here can be applied to various South Asian regions and in other parts of the world for improved characterization of gas reservoirs.