Unconventional source rock reservoirs, commonly referred to as unconventional gas or oil shale reservoirs, are geologically and petrophysically complex, organic rich, fine-grained mudrocks that must be hydraulically fracture-stimulated to produce gas or oil at economic rates. Increasingly these hydrocarbon reservoirs are being developed and produced using horizontal laterals. The dominant clay matrix particle size of these source rock reservoirs include heterogeneous compositional components that may include varying amounts of extrabasinal (terringenous fluid or airborne origin) clastics (quartz, feldspars, clays, and reworked rock fragments that include carbonate, igneous and metamorphic and volcanic rock fragments), and intrabasinal sedimentary particles (biologic origin silica, and calcite and preserved and altered kerogens), and diagenetically or chemically altered origin chert, dolomite, siderite, clays, and pyrite. These complex reservoirs possess complex pore systems that are dominantly nanoscale (extremely small-sized) inorganic, and organic interparticle, inter-crystalline and intraparticle pores (Loucks et al. 2012). In order for these reservoirs to produce hydrocarbons, the reservoir must exhibit very high hydrocarbon saturations (oil saturation, abbreviated, as So, or gas saturation, abbreviated as Sg) and very low (irreducible to sub-irreducible) water saturations abbreviated, as Sw. Natural fracture systems can also occur, either sub-vertical (of tectonic origin) or horizontal

(of petroleum system origin). Permeability is extremely low, often in the nanodarcy range. Movable hydrocarbons may be present within the pores (identified as free gas) but are also present as adsorbed or absorbed hydrocarbons to the kerogen and clay surfaces (identified as adsorbed gas). These very complex and nanoscale varying reservoir characteristics pose significant formation evaluation challenges. Successful formation evaluation of reservoir characterization requires the acquisition and analysis of high-definition, first-order technical data from many sources.