Chemostratigraphic Applications of Handheld X-Ray Fluorescence to Mudrock Plays: Methods, Pitfalls, Limitations, Aspirations, and Good Examples
With varied success chemostratigraphic studies continue to be integrated with more traditional evaluations of drill core, and often, with less-than-adequate comprehension of fundamental data generation and calibration. Initially, a workflow model consisting of (1) defining geologic questions, (2) optimizing the generation of high quality chemostratigraphic data, and (3) optimizing the linkages between geochemical data sets and other data sets ought to be considered. A primary reason for taking core during the drilling process is so that the stratigraphic succession and the sedimentary materials from which it is comprised can be observed. Sedimentary facies definition is one of the most fundamental methods of describing a drill core. Thus, in order to optimize the understanding of chemostratigraphic variability, geochemical data must be collected on the scale of facies variability.
This is now easily accomplished, and the outcome yields a much more quantitative perspective of facies variability. Moreover, petrophysical properties can be compared with highly-resolved chemostratigraphic results in order to better understand the linkages between mineralogical and rock physics variability.
Furthermore, a deeper understanding of the problems and limitations associated with the handheld energy-dispersive x-ray fluorescence method of core analysis is required in order to place quantitative, semi-quantitative, and qualitative constraints on a geochemical data set. One should be cognizant of inter-elemental interferences and x-ray physics phenomena that hinder the quantitative evaluation of an element in specific geological matrices. Additionally, the data collector and data user should be sufficiently skilled in the analysis of raw x-ray spectra in order to recognize the existence of and analytical outcomes resulting from, the presence of brines, the occurrence of elevated barium concentrations, the alteration of sulfide minerals, and other common complicating conditions. Ultimately, data quality and the quality of interpretations are intimately tied to the level of understanding of the technique and the depth of geochemical-mineralogical knowledge of the end user. Examples of pitfalls, limitations, and high quality datasets will be provided from drill core successions of the Eagle Ford and Haynesville formations.
AAPG Datapages/Search and Discovery Article #90219 © 2015 GCAGS, Houston, Texas, September 20-22, 2015