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Hyperspectral core imaging (HCI) technology was used to enhance characterization of a thin-bedded reservoir in the Permian Basin. Originally developed for the mining industry, hyperspectral imaging (HI) uses a combination of short-wave infrared light (SWIR) and long-wave infrared light (LWIR) to create a visual ‘map’ of the minerals in a core that respond to reflectance principles. HCI, which requires no special preparation other than that the core be clean and dry, can be applied rapidly and provides mineralogical results related to various energy emitted in wavelength spectrum by either halogen bulb reflectance (short-wave quantification) or heat reflectance spectra (long-wavelength quantification).
HCI provided detailed, high-resolution mineralogic and textural information of a conventional whole-cored interval and was used to produce interpreted mineral maps to refine stratigraphic models, explain petrophysical responses, and guide selection of plug locations for conventional and special core analysis. Digital HI-derived single mineral curves calibrated to X-Ray Diffraction Data (XRD) were imported as curves to display mineralogical variations with depth alongside open-hole wireline logs.
HCI was successfully applied and utilized as an integrative tool across additional data streams, associating open-hole wireline properties, overlays of textural relationships of mineralogical assemblages, and rock typing models with co-location of petrophysical properties to obtain better understandings of mineralogical-to-petrophysical links. We illustrate how hyperspectral imaging can be a powerful aid in geological and petrophysical quantification and property ‘up-scaling’ from SEM- and thin-section scales to depositional-system-level understandings.
Abstract Hyperspectral imaging (HCI) is a non-destructive analytical technique that uses infrared light to produce a visual ‘map’ of the minerals in a core. A whole core from the Bakken formation (Mississippian-Devonian) in the Williston basin, North Dakota, was scanned using both low-resolution (1.5 mm) short-wave infrared energy (SWIR) and longwave infrared (LWIR) energy. Next, a new technology was employed that uses three cameras to simultaneously acquire high-resolution information over wider wavelengths of the electromagnetic spectrum. This new long-wave infrared (LWIR) spectrometer, the first in the United States, contains a specialized lens to obtain data at a high resolution of 300–500 μm pixels and measure responses from tectosilicates, carbonates and some clays, as well as hydroxides, sulfates and phosphates. The new SWIR, which also uses a specialized lens for a high resolution of 300–500 μm pixels, identifies carbonates, hydroxides, sulfates, hydrocarbons, other silicate minerals, and clays. The LWIR and SWIR data were co-registered with high resolution (160 μm) RGB core photographs taken under high-wattage white LED lights. Mineral maps (both multi-mineral and single-mineral heat maps) of the core were obtained that display the textural relationships of the minerals in each core and distinguish subtle variations in mineral composition with depth, including silicate, carbonate and clay species. Curves of this mineralogical and textural data were then imported into petrophysical software to facilitate comparison of the older, low-resolution data with the data generated by the new high-resolution SWIR and LWIR technology. Furthermore, the SWIR and LWIR curves were overlaid with a variety of petrophysical curves, which allowed the visualization of the link between mineralogy and log measurements. Finally, quantification of continuous mineralogy from core provides calibration for petrophysical interpretation and integration of multiple mineralogy analysis from logs. Introduction The use of hyperspectral image data to map minerals on the surface of the Earth was the result of decades of research conducted in both commercial and government sectors. Hyperspectral imaging of core using short-wave infrared light (SWIR) is a non-destructive analytical technique originally developed from airborne systems by the mining industry (Taranak and Aslett, 2009), and since the late 2000s has been widely applied in other industries, including food, forensics, pharma and art (e.g. Cucci et al., 2016; Sun, 2010; Edelman et al., 2012; Lu and Fei, 2014).
Martini, Brigette (Corescan Inc.) | Bellian, Jerome (Whiting Petroleum Corporation) | Katz, David (Encana Corporation) | Fonteneau, Lionel (Corescan Pty Ltd) | Carey, Ronell (Corescan Pty Ltd) | Guisinger, Mary (Whiting Petroleum Corporation) | Nordeng, Stephan H. (University of North Dakota)
Abstract Hyperspectral core imaging studies of the Bakken-Three Forks formations over the past four years has revealed non-destructive, high resolution, spatially relevant insight into mineralogy, both primary and diagenetically altered that can be applied to reservoir characterization. While ‘big’ data like co-acquired hyperspectral imagery, digital photography and laser profiles can be challenging to analyze, synthesize, scale, visualize and store, their value in providing mineralogical information, structural variables and visual context at scales that lie between (and ultimately link) nano and reservoir-scale measurements of the Bakken-Three Forks system, is unique. Simultaneous, co-acquired hyperspectral core imaging data (at 500 μm spatial resolution), digital color photography (at 50 μm spatial resolution) and laser profiles (at 20 μm spatial and 7 μm vertical resolution), were acquired over 24 wells for a total of 2,870 ft. of core, seven wells of which targeted the Bakken-Three Forks formations. These Bakken-Three Forks data (~5.5 TB) represent roughly 175,000,000 pixels of spatially referenced mineralogical data. Measurements were performed at a mobile Corescan HCI-3 laboratory based in Denver, CO, while spectral and spatial analysis of the data was completed using proprietary in-house spectral software, offsite in Perth, WA, Australia. Synthesis of the spectral-based mineral maps and laser-based structural data, with ancillary data (including Qemscan, XRD and various downhole geophysical surveys) were completed in several software and modelling platforms. The resulting spatial context of this hyperspectral imaging-based mineralogy and assemblages are particularly compelling, both in small scale micro-distribution as well as borehole scale mineralogical distributions related to both primary lithology and secondary alteration. These studies also present some of the first successful measurement and derivation of lithology from hyperspectral data. Relationships between hyperspectral-derived mineralogy and oil concentrations are presented as are separately derived structural variables. The relationship between hyperspectral-based mineralogy to micro-scale reservoir characteristics (including those derived from Qemscan) were studied, as were relationships to larger-scale downhole geophysical data (resulting in compelling correlations between variables of resistivity and hyperspectral-mineralogy). Finally, basic Net-to-Gross calculations were completed using the hyperspectral imaging data, thereby extending the use of such data from geological characterizations through to resource estimations. The high-fidelity mineralogical maps afforded by hyperspectral core imaging have not only provided new geological insight into the Bakken-Three Forks formations, but ultimately provide improved well completion designs in those formations, as well as a framework for applying the technology to other important unconventional reservoir formations in exploration and development. The semi-automated nature of the technology also ushers in the ability to consistently and accurately log mineralogy from multiple wells and fields globally, allowing for advanced comparative analysis.
Whidden, Katherine (U.S. Geological Survey) | Birdwell, Justin (U.S. Geological Survey) | Dumoulin, Julie (U.S. Geological Survey) | Fonteneau, Lionel (Corescan Pty Ltd) | Martini, Brigette (Corescan Pty Ltd)
Abstract The Middle – Upper Triassic Shublik Formation is an organic-rich heterogeneous carbonate-siliciclastic-phosphatic unit that generated much of the oil in the Prudhoe Bay field and other hydrocarbon accumulations in northern Alaska. A large dataset, including total organic carbon (TOC), X-ray diffraction (XRD), X-ray fluorescence (XRF) and inductively coupled plasma – mass spectrometry (ICP-MS) measurements, has been built from core and outcrop samples of the Shublik, with a focus on the organic-rich intervals. In addition, two core intervals from the Shublik were analyzed using a hyperspectral imaging system in the visible, near-infrared and shortwave-infrared range. Integration of the hyperspectral results with core descriptions, microfacies interpretations, and analytical data is being used to decipher mudstone depositional and diagenetic processes. Petrographic analysis of Upper Triassic organic-rich intervals within the Shublik suggests that the main microfacies is a laminated bioclastic wackestone/packstone that was episodically disrupted by energetic events of variable intensity. These energetic events produced transitional and sparry calcite bioclastic packstone to grainstone intervals, depending on the depth of sediment column disturbance. By using hyperspectral imaging data from the Ikpikpuk core, individual distribution maps for minerals of interest have been generated and corroborate the microfacies interpretations. These maps also illustrate small-scale vertical changes in mineralogy. The laminated bioclastic wackestone/packstone intervals contain less calcite than the adjacent sparry bioclastic packstone to grainstone intervals. The calcite in these laminated intervals is more iron rich. This interpretation suggests that lower iron concentrations should be expected in the disrupted intervals than in nearby laminated intervals. Textural features are also enhanced in the hyperspectral images relative to visual description of the cores by combining the extraction of the average reflectance in the visible part of the electromagnetic spectrum and the depth of the main carbonate-related feature belonging to calcite. Examples noted in the enhanced imagery include low-angle features, calcite grain-size, and the size, shape and orientation of phosphatic nodules. This enhancement is being used to differentiate laminated from sparry bioclastic packstone to grainstone-rich intervals and provides a more comprehensive assessment of the microfacies than is practical by thin-section analysis.
Abstract The potential of petroleum source rocks as a dependable energy resource has been recognized and realized by the petroleum industry in the past decade. The production of clean natural gas from these resources and their potential for utilization as carbon storage sites (in adsorbed state) are also aligned with efforts towards mitigating climate change. Optimization of development and production from these resources requires dependable computational models, which in turn require, as inputs, accurate geologic characterizations. We investigate the potential of near-infrared (NIR) spectroscopy through hyperspectral imaging in mapping the spatial distribution of organic content at the core-scale with O(100μm) resolution. We apply the method to the immature oil shale of the Green River Formation, USA. We also draw comparisons with a recently developed optical method for detecting kerogen content in organic-rich shales . Implications for mapping spatial distributions of thermo-hydro-mechanical properties of petroleum source rocks on excavated cores are discussed. Introduction Quantification of organic content (TOC) in unconventional resources is important for both reserve estimation and resource development. There are several methods for measuring TOC, directly or indirectly, which include chemical analysis, Rock-Eval pyrolysis, and well logging . Most of these approaches are often destructive, require careful sample processing, or are limited in spatial resolution. An attractive alternative is spectroscopy, the deduction of TOC from interactions of light of a certain wavelength with the source rock, which is rapid, non-destructive, and potentially requires minimal sample preparation. In geosciences, two regions of the electromagnetic spectrum are used for quantifying the abundance of minerals and organic matter. The first is the mid-infrared (MIR), which spans wavelengths between 2500 and 25000nm. The other is the near-infrared (NIR) spanning wavelengths between 1000 to 2500nm. Reflectance, a (mostly) material property measured in spectroscopy, is defined as the ratio of the intensity of light reflected from a sample surface to the intensity of the incident light of a given wavelength.