Mature fields often times surprise with respect to the production from the various wells across reservoir sections. This is for example the case in a tight chalk field that we have used as a case study for newly developed technique that employs oil finger printing in the analysis of production data. A small subset of wells has been found to produce significantly better than the remainder and we set out to explore whether the root cause is that there is a connection to higher lying reservoir sections through natural or artificial fractures. This was done with advanced analytical chemistry (GC-MS) and a principal component analysis to map differences between key constituents of the oil from wells across the reservoir section. The comparative parameters are mainly derived from biomarker properties but we also developed a way to directly include production numbers. The approach provides means to correlate the molecular properties of the oil with the production and the general composition that determines density and adhesive (to the rock) properties. Thus, the results provide a new angle on the flow properties of the oil and on the charging history of the reservoir. It is clear from the analysis that the subset of wells does not produce better because of a connection to an upper reservoir section that contributes to the production with oil of a different composition because the molecular mix is indeed quite similar in each of the investigated wells. It is not possible to rule out that there is a connection to an upper-lying section with oil from the same source. One aspect that does differs across the field is the ratio of heavy versus light molecules within each group of molecules and the results show that the region that produce better has the lighter components. We take that to indicate that the lighter components come from oil that flows better and thus is produced more easily. The reservoir section with the lighter oil also lies higher on the structure and is therefore must likely to have been charged first so part of the favorable production seems to be a matter of "first in" "first out". A GC-MS approach such as the one proposed here is cost-effective, fast and highly promising for future predictions on where to perform infill campaigns because the results are indicative of charging history and flow properties of the oil.