Defined artificial mixtures of crude oils from the North Sea were analyzed using atmospheric pressure photoionization coupled to Fourier transform ion cyclotron resonance mass spectrometry (APPI FT-ICR MS). The main objective was the evaluation of the accurate determination of calculated mixing ratios of similar crude oils. The mixing ratios of two oils were determined on the basis of the relative abundances of the main compound classes detected as protonated species and radical cations. The calculation of the ratios of ternary mixtures was based on two different approaches. The first approach used the relative abundances of the main compound classes in combination with the non-negative least squares (NNLS) method. The second approach used principal component analysis (PCA) using the first and second principal components (PC1 and PC2) of the pure oils and defined ternary mixtures to generate a ternary PCA scoring plot. The exact compositions of three ternary mixtures were calculated on the basis of the measured PC1 and PC2 values. Relative compound class abundance plots of the binary mixtures showed remarkably good linear regression factors, indicating linear mixing behavior and high reproducibility of mass spectrometric measurements of petroleum samples using atmospheric pressure photoionization (APPI). As expected, ternary mixtures displayed a higher relative error for the determined ratios than binary mixtures. Nevertheless, the composition of ternary mixtures could be determined with reasonably high accuracy. The errors in the method based on multivariate statistical analysis were smaller than the NNLS method based on the relative abundance of compound classes. This study indicates that APPI FT-ICR MS can be used to identify ratios of crude oils in mixtures, making this approach useful for reservoir connectivity studies.