--> Utica-Pt. Pleasant Sub Basin: Integrating Stable Isotope Geochemistry and Basin Modeling to Help Predict Condensate Yield

Eastern Section Meeting

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Utica-Pt. Pleasant Sub Basin: Integrating Stable Isotope Geochemistry and Basin Modeling to Help Predict Condensate Yield

Abstract

The Utica-Pt. Pleasant unconventional play produces gas and condensate in eastern Ohio and western Pennsylvania. Condensate yield is important to the commercial success of the play, so improving the pre-drill prediction of this parameter is of interest to the producers.

In general, measured and modeled maturity can be used as a predictive tool to distinguish areas prospective for oil, wet gas and dry gas for unconventional plays. For marine Type II kerogen, as a general rule, oil is generated in the 0.6–1.1 Ro range, wet gas from 1.1–1.7 and dry gas over 1.7. In this case we attempt to predict condensate yield rather than just wet-gas based on a range of modeled maturity.

A 3D maturity model of the Utica-Point Pleasant Basin was constructed in order to predict maturity scaled as vitrinite reflectance equivalence (VRE) for multiple stratigraphic horizons. The horizons modeled were the Berea, Marcellus, Top Ordovician, Utica, Top Knox, Base Knox and Basement. In addition to structural horizons a map estimating late Paleozoic erosion was constructed. An uncorrected temperature gradient map from bottom hole temperatures from nearly 1500 wells was also made. This map was adjusted to correlate the Utica-Point Pleasant modeled maturity to the rock maturity for this interval.

Condensate yield was calculated from Utica-Point Pleasant production data for 256 wells provided by the Ohio Department of Natural Resources. These condensate yields were correlated to Utica-Pt. Pleasant modeled maturity and a good correlation (R2 = 0.76) was found between these data sets. The Utica-Point Pleasant modeled maturity map was then transformed to a condensate yield map by means of the equation.

Stable carbon isotopes from mud gas and production gases are used to further calibrate the model regionally and locally.