Using XRF Data to Estimate XRD Mineralogy and TOC as an Exploration Tool

Abstract

X-Ray Diffraction (XRD) and X-Ray Fluorescence (XRF) are complementary analytical techniques that are fundamental in understanding the geological context of petroleum source rocks, migration conduits, and reservoirs. XRD uses the crystal lattice structure of constituent mineral species to identify and quantify those mineral species of a rock sample. XRF, on the other hand, uses atomic fluorescence to identify and quantify the total elemental composition of a rock sample, but does not identify individual mineral species. XRD analyses generally require greater time and are an order of magnitude more expensive than XRF analyses. The latter can be performed quickly using hand held XRF instruments.

We examined XRD and XRF datasets for multiple source and reservoir rocks to determine if XRF generated elemental data could be used as a proxy to estimate bulk mineralogy. We constructed multiple linear regression models using the XRF data to predict the XRD mineralogy. The linear regression models are the numeric response column (major minerals) as a weighted sum of the predictor columns (XRF elemental data). Here, we have targeted basic XRD bulk mineralogy such as quartz, feldspar, calcite, pyrite, and total clay content using individual mineral stoichiometry (and elemental proxies) in the multiple linear regression modelling. Using this methodology on core from multiple formations and basins, we have built predictive mineralogy regression models for individual formations based on the XRF data. A universally predictive model was also constructed for different formations and basins. In addition to XRD mineralogy, a regression model was constructed that predicts Total Organic Carbon (TOC) based on the XRF data.

In this study, we worked with XRD and XRF data from multiple laboratories, and found that the basic relationships between mineralogy and elemental concentrations were robust. XRF data therefore provides a cost-effective and quick screening tool to estimate bulk mineralogy and TOC for exploration purposes. Additionally, others have shown that XRF data can be used to glean insights into basin-wide depositional system variations, adding to the value of XRF data collection.

AAPG Datapages/Search and Discovery Article #90323 ©2018 AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20-23, 2018