The enhanced analytical performance of comprehensive two-dimensional gas chromatography-mass spectrometry (GCXGC-MS) has demonstrated significant advantages for geochemical investigations of crude oils. However, the conventional geochemical analysis of crude oils based on diagnostic ratios from specific petroleum biomarkers can be more laborious and time-consuming for GCxGC. Additionally, the extraction of biomarker patterns from the crude oils is more analyst-dependent; therefore, the discovery of less evident and/or new patterns can be more challenging. This work introduces the use of GCxGC-MS/SIM and chemometrics for selected monitoring of the petroleum biomarkers and efficient discovery of the most relevant geochemical features that differentiate inter-reservoir crude oils. Pixels-based analysis using principal component analysis (PCA) extracted the multivariate patterns in the biomarkers fingerprints that successfully distinguished inter-reservoir geochemical properties that could also be obtained by the conventional diagnostics ratio approach, such as (i) the predominant marine or lacustrine organic matter depositional environment of the source rocks, (ii) oil's thermal maturity, and (iii) biodegradation level. Furthermore, a biomarker fingerprint that distinguishes similar crude oils among specific reservoirs was obtained using variable selection into partial least squares-discriminant analysis (PLS-DA). The discriminant power of the selected biomarkers was statistically ranked using one-way ANOVA F-test and null distribution analysis. GCxGC-MS/SIM alongside multistep chemometrics can potentially enhance the geochemistry features that distinguish crude oils according to their origins and/or degrees of chemical similarity.