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Variations in amplitude with offset are routinely being incorporated into our inversion products in order to differentiate lithology and fluids for increasingly complicated exploration and production projects. Commonly derived inversion products are acoustic impedance (AI) along with shear impedance (SI) or Poisson's ratio (σ). Density is also often derived separately with decreased reliability however, due to the dependence on accurate far-offset amplitudes beyond 30°for a stable result. The AI and SI attributes which may be determined with offset ranges up to 30°are in turn regularly crossplotted to investigate discrimination between differing lithology and fluid types.In AI-SI crossplot space, we may highlight our discrimination between any two litho-fluid types by choosing a rotated axis that optimizes the desired separation. One particular rotation in AI-SI crossplot space is worth noting because of its link to Poisson's ratio (σ) and density (ρ). Poisson's ratio and density are important in our reservoir delineation activities because low values for these parameters tend to be associated with many of our high quality reservoirs because gas-and oil-saturated rocks have low Poisson's ratios and densities compared to brine saturations, and higher porosity reservoirs have lower densities than those that are less porous. Poisson impedance or PI, as will be introduced, incorporates both σ information and ρ into a single display attribute which has been useful in reservoir delineation. In addition, because ρ is not being determined separately, but in combination with the σ information, such a combined attribute does not have a far-offset data requirement for stability, just as the combined V P and ρ attribute of AI does not require far-offset data beyond 30°.Seismic link to rock physics. Seismically we can determine AI and SI through inversion. An interesting relation between these two seismic attributes is:(1) which describes a rotation of the AI-SI data to obtain lithofluid discrimination, while the "c" term optimizes this rotation. The rotation of the data equates to a rotation of the axes which is illustrated in the schematic AI-SI crossplot in Figure 1. While neither AI nor SI alone completely discriminates oil sands, brine sands, and shale, a new coordinate system represented by the dotted box would completely discriminate the data groups in this example as represented by the rotated distribution plots.Since AI = V P ρ and SI = V S ρ, the simple relationship in equation 1 can be written:where V P is compressional velocity, V S is shear velocity, and we define V σ = (V P -cV S ). We can readily discern a linked relationship between V σ and σ. As V S increases relative to V P , both V σ and σ are decreased. This close relationship helps deter-mine what to call V σ , namely Poisson velocity because it responds to the same intrinsic rock V P /V S variations as Poisson's ratio but with velocity units. In an effort to gain a more detailed understanding of the relationship between Poisson velocity and Poisson's ra...