The highly heterogeneous nature of the micro fabric, and complex gas storage mechanisms, in shale formations can present significant evaluation challenges for unconventional formation evaluation. In this paper we present a new and robust methodology for shale formation characterization, termed "Simultaneous Core Log Multi-mineral Inversion (SCLMI)". This methodology executes a series of iterative processes, and computational logic, to provide an optimum solution for mineral volume, organic content, porosity and fluid saturation from the simultaneous inversion of log and core data utilizing an underlying physically consistent petrophysical model. The SCLMI methodology is flexible enough to accommodate advanced geo-mechanical log outputs, but also has the flexibility to deal with situations where datasets are more limited, and it can significantly reduce the data interpretation processing times required when analyzing complex formations. Critical factors for the successful implementation of the methodology, however, relate to the consistency in analysis and control over input parameters to ensure these outputs are consistent with the underlying petrophysical model. The methodology can also be extended to improve formation evaluation in conventional formations.

The flexibility and robustness of the SCLMI methodology has been demonstrated for a number of different shale gas and liquid rich plays, where it facilitates the development of optimized log interpretation parameters for calibration wells, which can then be readily applied to other geologically similar wells. In this paper, we illustrate the utility of the methodology using examples from the Marcellus Shale. The value of this methodology is further demonstrated by performing a rigorous comparative assessment against standard shale gas formation evaluation techniques – empirical correlations and geochemical logs based multi-mineral interpretations provided by a major service provider. The methodology works particularly well in the challenging lower Marcellus formation, which shows high gamma ray, total organic and heavy mineral content. In comparison, whilst empirical correlations provide reasonable predictive results for organic content and gas-filled porosity they are unable to accurately characterize mineral volumes, and un-calibrated geochemical log based multi-mineral interpretations are show to exhibit a significant and consistent bias in total porosity, water saturation and heavy mineral volume calculations.

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