Research paperMineral carbon MinC(%) from Rock-Eval analysis as a reliable and cost-effective measurement of carbonate contents in shale source and reservoir rocks

- Total carbonate content (abundance) based on XRD analyses correlate positively with Rock-Eval MinC values.
- Rock-Eval MinC values are effective proxy for the total carbonate contents in rock samples.
- High TOC content may lead to overestimate of mineralogical compositions by XRD analysis.

The abundance of carbonate minerals in rocks is an important element for petroleum geochemists, geologists and engineers to consider during hydrocarbon exploration and production. Carbonate minerals can be related to the depositional environments of the source rocks and hence the type of organic matter that can be subsequently modified through diagenetic processes. The total carbonate content in shales can also be used to deduce their fracability as reservoir rock for shale gas/oil extraction. At present, mineralogical analysis by X-ray diffraction (XRD) is the most widely used technique in the oil and gas-related petrophysical and geochemical laboratories for identifying and quantifying carbonate minerals in rock samples. In contrast, the use of the total mineral carbon content parameter MinC (%) from Rock-Eval analysis has been limited despite (1) the parameter's effectiveness as demonstrated through instrument and methodology development; and (2) the presence of a large volume of Rock-Eval results due to its widespread use in the oil and gas industry.In this study, we acquired XRD and Rock-Eval analytical results on over nine hundred rock samples ranging from Ordovician to Cretaceous age from four petroleum sedimentary basins in Canada. Least-squares regression analyses produce empirical equations with R2 values greater than 0.92 for the correlations between XRD total carbonate contents and the Rock-Eval MinC (%) values of six different suites of samples. This indicates that the MinC (%) values generated by Rock-Eval 6 and other instruments of similar capability can be used with confidence for estimating the amounts of total carbonates in sedimentary rock samples. While the correlation between the two types of carbonate content measurements is geology-specific, a global linear regression model (R2 of 0.97) based on the large combined data set has been proposed for approximating the total carbonate abundances based on Rock-Eval MinC (%) values.