Evaluation of oil fingerprints similarity by a novel technique based on FTIR spectroscopy of asphaltenes: Modified moving window correlation coefficient technique

摘要

Investigation of oil fingerprints heterogeneities in different wells across the reservoir is a critical effort in various disciplines of geochemical studies. Exploring new, trustworthy, and straightforward techniques is an ongoing and interesting subject in the oil industry. In this paper, a novel procedure for oil fingerprints comparison by employing the structural characteristics of asphaltenes is suggested. For the first time, the modified version of the moving window correlation coefficient is proposed to resolve the drawbacks of the standard procedure and then implementing for comparison of oil fingerprints. This procedure is based on peak ratios calculated from the second derivative FTIR spectra of asphaltene samples. The results of this technique are summarized in a matrix with green, red and yellow cells based on the calculated values of the minimum correlation coefficient in all moving windows (MMWR) and the average of correlation coefficients in all moving windows (AMWR) regarding defined thresholds to better visualization of fingerprint similarity or dissimilarity between studied samples. The oil fingerprint similarities in the two case studies from the Dezful Embayment of southwest Iran were investigated to demonstrate the usefulness of this technique. Ten samples from different wells in the Qale Nar oil field and eight samples from the Shadegan oil field were studied. Results showed that crude oils in the Asmari reservoir from the Qale Nar field have a similar fingerprint and are homogenous. But crude oils in the Asmari reservoir from the Shadegan field involves several zones based on oil fingerprints similarity. Whole oil gas chromatography (WOGC) was performed for checking purposes. The proposed method based on FTIR spectra of asphaltene samples and their comparison with the modified moving window correlation coefficient can be regarded as a novel, reliable, and straightforward technique for oil fingerprint similarity assessment.