Fractures and joints in the field often contain debris within the void spaces. Debris originates from many different mechanisms: organic and/or inorganic chemical reactions/mineralization, sediment transport, formation of a fracture, mechanical weathering or combinations of these processes. In many cases, the presence of debris forms a “sub-porosity” within the fracture void space. This sub-porosity often is composed of material that differs from the fracture walls in mineralogy and morphology. The “sub-porosity” may partially fill voids that are on the order of hundreds of microns and thereby reduce the local porosity to lengths scales on the order of sub-microns to tens of microns. It is quite clear that a sub-porosity affects fracture porosity, permeability and storativity. What is not known is how the existence/formation of a sub-porosity affects seismic wave propagation and consequently our ability to probe changes in the subsurface caused by the formation or alteration of a sub-porosity. If seismic techniques are to be developed to monitor the injection and containment of phases in sequestration reservoirs or the propping of hydraulically induced fracture to enhance oil & gas production, it is important to understand how a sub-porosity within a fracture affects macroscopic seismic and hydraulic measurements. A sub-porosity will …

This report discusses the methodology, formulas, and inputs needed to make characterization and clearance decisions for Bacillus anthracis-contaminated and uncontaminated (or decontaminated) areas using a statistical sampling approach. Specifically, the report includes the methods and formulas for calculating the • number of samples required to achieve a specified confidence in characterization and clearance decisions • confidence in making characterization and clearance decisions for a specified number of samples for two common statistically based environmental sampling approaches. In particular, the report addresses an issue raised by the Government Accountability Office by providing methods and formulas to calculate the confidence that a decision area is uncontaminated (or successfully decontaminated) if all samples collected according to a statistical sampling approach have negative results. Key to addressing this topic is the probability that an individual sample result is a false negative, which is commonly referred to as the false negative rate (FNR). The two statistical sampling approaches currently discussed in this report are 1) hotspot sampling to detect small isolated contaminated locations during the characterization phase, and 2) combined judgment and random (CJR) sampling during the clearance phase. Typically if contamination is widely distributed in a decision area, it will be detectable via judgment …