Friday 25 March 2011

ICAM 2011 presentation on rock typing of PDC drill cuttings



FEI Australia Center of Excellence for Natural Resources in collaboration with CO2CRC is going to present a third talk at the 10th International Congress for Applied Mineralogy (ICAM 2011) in Trondheim, 1-5 August 2011. Here is a preview of our presentation on a novel lithotyping approach performed on Polycrystalline Diamond Compact (PDC) drill cuttings. Micron-scale compositional mapping, using FEI's QEMSCAN® automated mineralogy solution, and cutting-by-cutting classification by the iDiscover™ software package are demonstrated to provide detailed reservoir rock properties beyond chemical assays and modal mineralogy reports.

Petrological reconstruction of the subsurface based on PDC drill cuttings: an advanced rock typing approach"
by David Haberlah, Pieter W.S.K. Botha, Nicole Dobrzinski, Alan R. Butcher and John G. Kaldi

Polycrystalline Diamond Compact (PDC) drill bits are increasingly used in conjunction with motors and turbines as a fast and cost-effective way to drill wells. However, produced rock cuttings, in particular from clastic reservoir rocks, are often considered too fine and problematic for conventional petrological analysis. Recent advances in automated scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM-EDS) have transformed the petrological analysis of drill cuttings by replacing conventional qualitative descriptions of handpicked samples, with ultra-fast, quantitative and repeatable petrological analysis. Further developments include moving from chemical and mineralogical whole-rock analysis towards textural characterisation performed on a cutting-by-cutting and mineral grain-by-grain basis. Automated SEM-EDS compositional mapping allows for the definition of rule sets that classify individual cuttings into categories based on parameters such as mineral associations, grain sizes and shapes. As a result, drill cuttings can be classified into lithotypes representing subsurface rock types.

This study demonstrates that accurate and detailed reservoir characterisation can be based on SEM-EDS compositional maps of PDC drill cuttings. Lithofacies associations are reported from rock cuttings at continuous 5 m depth intervals from the CO2CRC’s CRC-1 well for a continuous stratigraphic interval in the Late Cretaceous Skull Creek Fm and Lower Paaratte Fm of the Otway Basin, Victoria, Australia. The CO2CRC Otway Project is the world’s largest research and geological storage demonstration project of the deep geological storage of carbon dioxide (CO2). For each cutting interval, a chemical assay, modal mineralogy report, and corresponding compositional maps were reported. A key advantage of automated SEM-EDS solutions such as QEMSCAN® is that particles can be categorised on the basis of mineralogy, grain size and texture. Here, the drill cuttings were first classified into three general lithotypes, corresponding with sandstone, shale and cemented clasts, and subsequently divided into more specific lithotypes. These provide detailed information on the depositional environment and diagenetic history of the rock formations, and highlight intervals of cementation and intra-formational seals within the reservoir. The lithotyping results were plotted against wireline log data and show a strong correlation with the gamma-ray log.

This study demonstrates that combining automated SEM-EDS measurements of PDC cuttings with advanced digital image analysis and processing, can significantly contribute to the petrological reconstruction of the subsurface. This reinforces drill cuttings are a valuable source of geological and engineering information, potentially reducing the requirements for routine coring and wireline logging.

Wednesday 16 March 2011

CASANZ 2011 presentation on silica in ambient air


The scientific community and general public are becoming increasingly aware that mineralogy of airborne particulates matters as much as size and shape. The latest paper on this topic will be presented by Anthony Morrison at the 20th Clean Air Society of Australia and New Zealand Conference CASANZ 2011 in Christchurch 5-8th July 2011. It characterises silica and silicon concentrations in ambient air in the vicinity of open cut coal mining operations in the Hunter Valley, New South Wales, Australia. FEI’s automated scanning electron microscopy and energy- dispersive x-ray spectroscopy (SEM-EDS) solution QEMSCAN is used to quantify the proportion of quartz in the particulate matter (PM) samples, identify other silicon containing species for provenance interpretation, and to determine the degree of liberation of quartz in the dust samples.

This study is among the first to apply Automated Mineralogy to the investigation of the public health impacts of airborne particulates to inform the discussion of air quality management plans. It is also pioneering a direct sampling to measurement process, using a Micro Orifice Uniform Deposit Impactor (MOUDI) allowing the dust samples to be collected on polycarbonate discs specially prepared for transferral into the QEMSCAN sample holder. Finally, the study is involving the world’s first attempt at measuring loosely bound particles, thus avoiding sectioning or polishing. The QEMSCAN Particle View screenshot above demonstrates that the surface covered by silt-sized particles is flat enough to be measured.

Have a look at the abstract below and make sure to attend the conference to get a copy of the full paper.

"Quantifying respirable crystalline silica in the ambient air of the Hunter Valley, NSW - sorting the silica from the silicon"
by Anthony Morrison, Peter F. Nelson, Eduard Stelcer, David Cohen, David Haberlah

Crystalline forms of silica are known to cause lung damage for which there is no effective treatment. Silicon is abundant in crustal material and silicates are the single largest mineral grouping, with silica (SiO2) being the most abundant crustal compound. Media reports of high levels of silicon in particles in the air in the vicinity of Hunter Valley open-cut coal mines have caused community anxiety and concerns about potential health impacts on local populations. An extensive sampling campaign using continuous air quality monitoring and targeted collection of particles has been carried out in an area close to mining operations. It was determined that silicon as silica was present in the ambient air, although the concentrations of crystalline silica measured suggest that it should not should cause health problems even for sensitive individuals within the general population. The results of the research should inform more rigorous discussions of air quality management plans for fine particles in the Hunter Valley and aid discussions of community concerns over the potential health impacts of coal mining

Friday 4 March 2011

ICAM 2011 presentation on hematite and magnetite discrimination

1) optical microscopy, 2) enhanced BSE image, 3) segmentation, 4) MLA classification

FEI Australia Center of Excellence for Natural Resources is going to present a second talk at the 10th International Congress for Applied Mineralogy (ICAM 2011) in Trondheim, 1-5 August 2011. Here is a preview of our talk on a new MLA approach discriminating hematite from magnetite for iron ore characterisation.

"Advanced discrimination of hematite and magnetite by Automated Mineralogy"
by German Figueroa, Kurt Moeller, Michael Buhot, Gerda Gloy and David Haberlah

As the global growth of steel production and consumption continues to accelerate, innovation in the whole industry from iron ore extraction to processing is needed. By providing quantitative and statistically reliable compositional information, automated mineralogy solutions such as the Mineral Liberation Analyser (MLA) have become important tools for characterising iron ore minerals (i.e. hematite, magnetite, goethite and limonite) and their processing products. Although magnetite (Fe3O4) and hematite (Fe2O3) can be easily distinguished qualitatively using optical microscopy, quantitative characterisation by automated scanning electron microscopy/energy-dispersive x-ray spectroscopy (SEM-EDS) is challenging. Hematite and magnetite are chemically close and display similar backscatter electron (BSE) intensities, making discrimination by energy-dispersive X-ray (EDX) spectra alone difficult.

This study presents an automated mineralogy approach discriminating iron oxides by taking full advantage of the subtle difference in backscatter intensities between hematite and magnetite. The advanced workflow involves three steps: 1) Optimisation of measurement parameters increasing the BSE brightness and contrast. In standard MLA operation mode, the BSE brightness is calibrated so that the mounting media (resin) is kept at backscatter brightness values below 15, and gold at a value of 250, covering all common minerals. The modified settings stretch the BSE range for iron oxides from 115-120 to 195-215, effectively doubling the grey level contrast. Two separate modes emerge representing hematite (~200) and magnetite (~208), which can be separated in the image segmentation stage. 2) EDX spectra acquisition combining two measurement settings. Single EDX spectra are collected from geometric centre points of unsaturated segmented phases corresponding to discrete minerals, including hematite and magnetite. Saturated segments, comprising multiple bright mineral phases, are mapped using a regular grid with further phase discrimination based on EDX spectra. 3) Mineral identification is performed by an advanced classification algorithm combining BSE thresholds and EDX spectra.

The new approach is applied to a synthetic sample including particles displaying complex intergrowth between hematite and magnetite, bright sulphide phases, and common gangue minerals. The automated phase-by-phase approach characterises hematite and magnetite reporting quantitative modal composition, mineral association and locking. The results demonstrate that the advanced approach can successfully discriminate iron oxides into hematite and magnetite while at the same time correctly reporting the modal contributions of other phases. Hematite and magnetite are locked as binary phases reflecting intergrowth, and further occur as ternary phases with quartz and feldspar. Locking of the iron oxides can be slightly overestimated without significantly impacting overall results, due to mineral impurities, defects and boundaries with epoxy showing in the BSE image.

In conclusion, an automated SEM-EDS approach is demonstrated to successfully discriminate and quantify hematite and magnetite by advanced mineral identification based on modified backscatter intensities and EDX spectra matching.

Tuesday 1 March 2011

ICAM 2011 presentation on SEM-EDS mineral identification


Our team at FEI Australia Center of Excellence for Natural Resources is going to present a number of talks at a range of interesting conferences this year. In particular, we will have a strong presence at the 10th International Congress for Applied Mineralogy (ICAM 2011) in Trondheim, 1-5 August 2011. Here is a preview of our talk on a new QEMSCAN protocol for mineral identification using the new Spectral Analysis Engine.

"SEM-EDS based protocol for subsurface drilling mineral identification and petrological classification"
by David Haberlah,Michael Owen, Pieter W.S.K. Botha and Paul Gottlieb

Integrated scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM-EDS) solutions are widely employed in the mining sector. In subsurface drilling for hydrocarbons, SEM-EDS systems are less common and often only applied to the analysis of thin sections of core samples. Coring wells is more expensive and takes significantly longer than drilling wells. The downside of drilling versus coring is the produced slurry of fine rock cuttings and drilling fluid additives that prove difficult to interpret in terms of rock properties. Thus, drill cuttings are rarely analysed beyond qualitative microscopic descriptions by the mudlogger. Automated SEM-EDS solutions have great potential by providing quantitative cutting-by-cutting data. One difficulty is to develop robust mineral and petrological identification for the cuttings and the drilling mud. Here, we present a fully automated quantitative SEM-EDS based approach, measuring pixels along a predefined grid and comparing measured energy-dispersive x-ray (EDX) spectra with a library of mineral compositions. The analytical protocol is based on the new QEMSCAN® Spectral Analysis Engine (SAE) employing the elemental concentrations method. Mineral phase identification is accomplished by a multi-layered approach using iDiscover™ software v.5.0.

First of all, elemental peak positions and relative intensities from the measured EDX spectra are compared with spectra of elemental standards measured on the same system. The new SAE can perform identification and quantification of up to 72 elements. However, in subsurface drilling applications, the majority of reservoir and seal rock-forming minerals can be adequately discriminated by less than 20 elements. Subsequently, a position-dependent, multi-layered approach to mineral classification is applied. The elemental composition from the measurement point is compared to elemental ranges calculated from synthetic mineral spectra and high-count spectra measured on mineral standards. The elemental ranges are typically based on 100 iterations or more, simulating statistical variability in measured low-count spectra. Variation in the composition of mineral phases and across mineral groups is accounted for by a second layer, merging end-member definitions into single combined mineral (group) expressions (e.g. orthoclase, sanidine, and anorthoclase into alkali feldspars), and by adding common accessory and substitute elements into a “may have” category. Next, the elemental ranges are adjusted interactively on measured samples of known mineral composition. Finally, a few broad definitions trapping poorly defined components such as the mounting medium, inorganic drilling fluid additives, and organic matter can be defined. Once the mineralogical composition of the individual cuttings is fully mapped, they can be further categorised into discrete classes such as rock types. Micro-lithotype classes are based on expressions that take into account textural attributes, such as mineral associations and grain sizes. Rock characteristics of particular interest to reservoir modelling, e.g. the presence of pore-filling cements, can be identified and numerically reported.

Our results suggest that SEM-EDS based mineral identification and petrological classification of drill cuttings can significantly reduce the need for expensive coring, reduce the size of cuttings that can be analysed, and overall improve petroleum reservoir characterisation and modelling efforts. The direct quantitative cutting-by-cutting measurements can also provide an independent means for calibrating gamma ray wireline log data, by reporting the presence of low-potassium clay minerals (i.e. kaolinite and chlorite) in seal formations, and high-potassium feldspars in reservoir rocks.