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Statistical Comparison of Hydrocarbon Gas Composition and Isotopic Ratios From Multiple Sampling Methods

Abstract

A standard aspect of formation evaluation is an inferential analysis of hydrocarbon gases encountered in the subsurface. The nature of these gases can indicate fluid saturation, phase, quality, provenance, and many other unknowns that are fundamental to understanding the petroleum system as well as commerciality of the respective well. Currently, there are four principal sampling and analysis techniques employed. These include well site mud gas analysis, offsite analysis of collected mud gas (IsoTubes®), headspace analysis from cuttings samples (IsoJars®), and analysis of flashed gas from down-hole fluid-sampling tools (e.g. MDT). The interpretation of these data is imperative to any petroleum systems analysis, but, as is often the case in applied exploration science, only one or two sampling methods may be prudent to collect during operations. Additionally, historic data may be incomplete or limited, and an understanding of relationships and inherent biases in the sampling and analytic methods can help to increase confidence when dealing with such limited datasets. This study offers a statistical comparison of these four methods, in the context of applied analysis of a deepwater dataset, to quantify sampling and analytical uncertainty. It has been observed in limited case studies that normalized gas composition measurements are variable between IsoTube® and MDT samples, but a statistical analysis on a large dataset across multiple hydrocarbon plays with both compositional and isotopic variables has not been published. This comparison, combined with well-site GC and headspace gas analysis, creates a robust analytic tool that can help to overcome the problems of data sufficiency and cost associated with running redundant analyses.