Quantitative calibration of hyperspectral core imaging data: A new method for producing continuous, high-resolution mineralogical characterization of cores from both conventional and unconventional reservoirs

Abstract

Hyperspectral core imaging (HCI) involves a method of non-destructive, infrared spectroscopy to capture mineralogical and textural information of the slabbed face of a core. A combination of two co-registered spectrometers, one for the short-wave infrared (SWIR) spectrum and one for the long-wave infrared (LWIR) spectrum, are utilized together to identify the minerals present in a core. The LWIR identifies tectosilicates such as quartz and feldspar, which cannot be detected in the SWIR or very-near infrared (VNIR) ranges. Spectral data is acquired using specialized high-resolution lenses for a spatial resolution of 300 to 500 microns per pixel, allowing identification of thin laminations and subtle sedimentological features in cores from unconventional reservoirs. This level of resolution also facilitates integration of HI with discrete measurements (XRD, thin section, SEM, etc.) for upscaling to core and wireline log scales. Most standard HCI analyses involve interpretive or spectral-matching classifications of waveforms to deliver qualitative mineralogical information. A variety of spectral un-mixing algorithms can be used to infer mineralogy in a more quantitative manner; however, these methods are limited by the non-linearity and spectral variability of mineral mixing. In this study, analytic models were developed to calibrate the spectral classifications using discrete X-Ray Diffraction (XRD) measurements as control points. Forward modeling was used to validate the fit between the measured and predicted property values. This methodology was successfully applied using HCI data from several unconventional formations, including the Eagle Ford Shale, Austin Chalk, Smackover, Bone Spring Shale and Wolfcamp Formations, and used to produce curves of continuous mineralogy and facilitate upscaling of quantitative mineralogical properties to wire-line log scale.

AAPG Datapages/Search and Discovery Article #90350 © 2019 AAPG Annual Convention and Exhibition, San Antonio, Texas, May 19-22, 2019