Abstract

The identification and quantification of volatile fluids and gases sorbed to organic and mineral surfaces or present in interstitial pore spaces of rock samples have previously been used for the stratigraphic evaluation of petroleum systems. Volatile analysis service (VAS) is one example of this technique. Typically, results from such studies are used to inform drilling/completion decisions through identification of pay intervals and determination of hydrocarbon composition as well as evaluation of other geologic features like rock type and mechanical properties. Immature source rock has not been previously examined using VAS, so the applicability of the method to evaluating immature rocks is unknown. In this study, VAS was applied to thermally immature samples of Upper Cretaceous Eagle Ford Shale taken from a shallow drill core collected near Del Rio, Texas (50 to 250 ft from the surface). Multiple analytes were quantified and their stratigraphic patterns in the well were examined (Fig. 1). Methane and propane represent most of the hydrocarbon gas fraction (CH₄: 535 to 1279 parts per million by volume [ppm-v]; C₃H₈: 29 to 79 ppm-v). Concentrations of hydrocarbons gases increased above 150 ft. In contrast, aromatics decreased above this depth and are disproportionately represented throughout the core relative to what is typically observed in thermally mature strata. Helium and argon showed stratigraphic patterns independent of the hydrocarbon gases, with concentrations continuously increasing from the base of the Eagle Ford at ∼240 ft to 122 ft where they decreased substantially before increasing again above 114 ft. These differences indicate that hydrocarbon and non-hydrocarbon components are providing different information on these immature strata, particularly how organic matter properties affect hydrocarbons and stratigraphic features affect the non-hydrocarbon gases. The results of the volatiles analysis supplements other datasets but also provide additional insights into what are likely post-depositional processes not discernable from other datasets.