--> Integration of Geochemistry Data with Fluid Property Information Acquired During Well Testing for a Comprehensive Understanding of Petroleum Accumulations

AAPG Middle East Region GTW, Regional Variations in Charge Systems and the Impact on Hydrocarbon Fluid Properties in Exploration

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Integration of Geochemistry Data with Fluid Property Information Acquired During Well Testing for a Comprehensive Understanding of Petroleum Accumulations

Abstract

An integrated molecular and isotope geochemistry and petroleum engineering approach yielded new parameters for reservoir charge history, water washing, biodegradation and gas to oil ratio.  A total of 14 light oil samples were investigated utilizing two gas chromatography (GC) techniques for their detailed light hydrocarbon (n-C4 to n-C10) composition and whole-oil gas chromatography fingerprinting. The samples were also assessed by liquid chromatography for their saturates, aromatic and polar fraction concentrations. Furthermore, the first two fractions were assessed for their biomarker and carbon isotope compositions.  The results classify the oils based on source rock and charge into three groups. Two groups are attributed to two different source rocks, and the third represents a mixture of two groups. The biomarker concentrations were low due to the high thermal maturity; however, they elucidate similar conclusion. The isotope data did not illustrate great variations among the samples possibly because of similarity in the source rock age.  The study elucidates a new geochemical ratio for water washing and GOR predictions. The whole oil fingerprinting method indicates at least 5 reservoir compartments.  The light hydrocarbon assessment implies water washing effects increase toward the north. These data positively correlate with C11 hydrocarbon compound ratios, API gravities and gas to oil ratios (GOR). These new relationships allow for utilizing molecular geochemistry in predicting reservoir engineering parameters. Such application opens the door for better geochemical data optimization to understand reservoir alteration process.