You have just joined a new asset team or new company. You're handed an area to evaluate. The data include seismic, logs, and a cube of acoustic impedance. What do you do with the impedance data? How was it created? What unique information does it provide? What pitfalls and artifacts may be present? How do you interpret this data set on a workstation that is designed for seismic data? How do you report your results to management? Valid questions? Read on. Inversion of seismic data into acoustic impedance (AI) is a rapidly growing field, due primarily to the ease and accuracy of interpretation of the impedance data. The term “inversion” has the potential for a great amount of confusion, as it is used to mean many different things within various branches of geoscience. The discussion in this paper will concentrate on the inversion of poststack seismic traces into acoustic impedance data. Even with this narrower scope, the plethora of programs on the market today makes the comparison of various inversion methodologies and the determination of the quality of your AI cube difficult at best. This paper will provide a description of terminology and a basis for comparison of poststack acoustic impedance inversion products, as well as give the interpreter a methodology for quality control and interpretation of inverted data. Acoustic impedance (AI) is the product of rock density and P -wave velocity. This means that AI is a rock property and not an interface property (e.g., seismic reflection data). As we will illustrate, this distinction is the power of AI. Acoustic impedance inversion is simply the transformation of seismic data into pseudoacoustic impedance logs at every trace. All information in the seismic data is retained. Figure 1 shows an acoustic impedance model and its representation with two imaging techniques. The …