One of the characteristics of the Shale Revolution in the United States has been the multitude of small and medium-sized independents that took part in it.  These companies, while punching far above their weight and potentially offering substantial returns, usually do not have the technical resources of the Majors, and they often operate on tighter timelines with looming drilling commitments.  Consequently, a substantial amount of capital has been invested with relatively sparse and sometimes low-quality data, where the most important variables have to be inferred, often with appreciable error bars. Technical teams must do their best with what they have to build a picture of the reservoir they are thinking of acquiring or investing in. This presentation explores this process and sheds some light on the traps and difficulties encountered along the way. We present a synthetic – but realistic – case where the “butterfly effect” of assumptions can be appreciated; small differences at the beginning of the process can lead to vastly different development plans down the line. We conclude with three real cases drawn from public data.