2019 AAPG Annual Convention and Exhibition:

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Utilization of High-Resolution Short- and Long-Wave Hyperspectral Imaging for Integrative Rock Typing


Hyperspectral imaging (HI) is a method of observing and enhancing geological rock properties that are not readily apparent visually. Originally developed for the mining industry for use in airborne systems, HI uses a combination of short-wave infrared light (SWIR) and long-wave infrared light (LWIR) to create a visual ‘map’ of the minerals on the surface of a core that respond to reflectance principles. Although bespoke hyperspectral imaging systems have now been developed and utilized to great success in the mining industry to map mineralogical changes along a core, the technology has been limited to the SWIR region (<2500 nm), and important minerals in oil and gas reservoirs, such as quartz and feldspar, cannot be detected in those wavelengths. Until very recently, commercial imaging technology for the LWIR has not been available due to cost and technical challenges. The relatively new LWIR spectrometer, which contains a specialized lens to obtain data at a high resolution of 300-500 µm per pixel, measures responses from tectosilicates, carbonates and some clays, as well as hydroxides, sulfates, and phosphates. Processing of the HI data involves the generation of two sets of self-organizing map (SOM) classifications, one for each of the SWIR and LWIR sensors. SOM is a type of unsupervised artificial neural network, which is an effective classification method to classify non-linear data with a large number of variables by calculating minimum distances between the data points. Each acquired pixel on the core surface is associated with a SOM class from the SWIR and LWIR sensors. We have developed a method that utilizes these raw (uninterpreted) SOM data to produce rock types for cores from both silicate and carbonate formations. These rock types have been generated for a variety of conventional and unconventional reservoirs to guide sampling for plug locations for conventional and special core analysis. We present examples of how HI-derived rock types have been combined with a variety of core data, including core description, thin-section, X-Ray Fluorescence (XRF) data and X-Ray Diffraction (XRD) data to produce impactful mineralogical integration within a stratigraphic context.