Temporal damping effect of the Yucca mountain fractured unsaturated rock on transient infiltration pulses
Performance assessment of the Yucca Mountain unsaturated zone (UZ) as the site for an underground repository of high-level radioactive waste relies on the crucial assumption that water percolation processes in the unsaturated zone can be approximated as a steady-state condition. Justification of such an assumption is based on temporal damping effects of several geological units within the unsaturated tuff formation. In particular, the nonwelded tuff of the Painbrush Group (PTn unit) at Yucca Mountain, because of its highly porous physical properties, has been conceptualized to have a significant capacity for temporally damping transient percolation fluxes. The objective of this study is to investigate these damping effects, using a three-dimensional (3-D) mountain-scale model as well as several one-dimensional (1-D) models. The 3-D model incorporates a wide variety of the updated field data for the highly heterogeneous unsaturated formation at Yucca Mountain. The model is first run to steady state and calibrated using field-measured data and then transient pulse infiltrations are applied to the model top boundary. Subsequent changes in percolation fluxes at the bottom of and within the PTn unit are examined under episodic infiltration boundary conditions. The 1-D model is used to examine the long-term response of the flow system to higher infiltration pulses, while the damping effect is also investigated through modeling tracer transport in the UZ under episodic infiltration condition. Simulation results show the existence of damping effects within the PTn unit and also indicate that the assumption of steady-state flow conditions below the PTn unit is reasonable. However, the study also finds that some fast flow paths along faults exist, causing vertical-flux quick responses at the PTn bottom to the episodic infiltration at the top boundary.
Capillary Barriers in Unsaturated Fractured Rocks of Yucca Mountain, Nevada
Yu-Shu Wu, Winnie Zhang, Lehua Pan, Jennifer Hinds, and Gudmundur S. Bodvarsson Earth Sciences Division Lawrence Berkeley National Laboratory Berkeley, CA 94720 This work presents modeling studies investigating the effects of capillary barriers on fluid-flow and tracer-transport processes in the unsaturated zone of Yucca Mountain, Nevada, a potential site for storing high-level radioactive waste. These studies are designed to identify factors controlling the formation of capillary barriers and to estimate their effects on the extent of possible largescale lateral flow in unsaturated fracture rocks. The modeling approach is based on a continuum formulation of coupled multiphase fluid and tracer transport through fractured porous rock. Flow processes in fractured porous rock are described using a dual-continuum concept. In addition, approximate analytical solutions are developed and used for assessing capillary-barrier effects in fractured rocks. This study indicates that under the current hydrogeologic conceptualization of Yucca Mountain, strong capillary-barrier effects exist for significantly diverting moisture flow.
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.