Optimization of Analytical Techniques Used in Applications for Mining and Oil & Gas

Optimized analysis of drilling core sections plays a major role in mining and oil shale industries. Oil extraction from shale depends on finding optimal drilling sites and studying core samples to ascertain the most productive extraction locations.

In standard analysis, a bulk tool is first used to determine the total elemental composition of a core sample, and then secondary tools are used to differentiate particular mineral grains and their distribution. Mining analysts look for fast and cost-effective approaches to analyze core sample features, such as mineral composition and grain size to find optimal locations.

Using an optimized analytical technique to increase the effectiveness of shale location testing would not only help in analyzing large areas of samples quickly, but would help in differentiating between individual grains too.

Comparison with Existing Solutions

X-ray Fluorescence (XRF) is widely used to determine key elements, such as sulfur or iron, present in huge areas of shale drilling core sections. On the other hand, the collection area using this method comprises the bulk shale matrix, though only the grains in the matrix are needed to determine the characteristics of the shale drilling area.

Most of the collection time is therefore spent collecting from areas that are not important. Since the data is obtained from grains and matrices, element weight ratios of the XRF data can only be used to interpret information regarding grain chemistry.

Backscatter electron imaging (BSE) coupled with a scanning electron microscope (SEM) is employed to view the grains, which are found in the matrix of the core shale sample. Since this image signal is based on mean atomic number, when the atomic weight increases, the signal intensity also increases.

For instance, a grain containing iron will possess a stronger BSE signal when compared to one containing calcium. Hence, individual grain images are possible and information regarding size and distribution is determined through image analysis routines. This imaging method, however, does not give an accurate quantitative assessment of the grains (Figure 1).

2048 X 1600 pixel resolution image of the first field of view from a 10 X 10 field run, for a total of 20 K X 16 K pixels in the analysis.

Figure 1. 2048 X 1600 pixel resolution image of the first field of view from a 10 X 10 field run, for a total of 20 K X 16 K pixels in the analysis.

X-ray diffraction analysis gives the required compound associations of elements and hence compound minerals, such as Pyrite, can be proven to be present in the material. However, this is also a complex method; though it produces the overall area fraction of the compound, it does not give information regarding size and distribution which are both useful for identifying the location of the core sample section.

EDS Particle Analysis with the Octane SDD Series

Energy dispersive spectroscopy (EDS) analysis uses a BSE signal from the SEM to produce an image underlining the grains of interest from a sample and then directly obtains data from the specified grains. This analytical method not only detects the elements present, but also calculates the spectral data. It then utilizes a feature specific library to easily sort and classify the grains in a matrix.

EDAX's Octane silicon drift detector (SDD) technology can produce data of high resolution even at high input count rates for collection times within a single second per grain or particle. Data obtained from the shale matrix or clay is not collected and hence large areas can be covered rapidly. Spectra are obtained, then element peaks are identified, and finally quantitative weight percentages are used to correlate the compounds.

Automated software organizes data against libraries that were specifically produced for compounds of interest at the rapid collection rates. In addition, the software produces data regarding particle shape, size, and area fraction, which reveals the distribution of the grains or particles of interest in the shale matrix. Since elements differ by location and drill core depth, miners use this data to determine the optimal drilling sites.

Analytical Methods and Results

Optical images of polished and epoxy-mounted shale revealed the presence of grains in different color, sizes, and luster, all of which denote metallic differences. However, this could not be validated by optical analysis alone. To study the section in a Tungsten Variable Pressure (WVP) SEM, an Octane Super SDD was used which displayed fast collection rates with high quality (Figure 2). Figure 3 shows copper and sulfur peaks in spectrum at 1.2 M cps and 0.1 sec collection time.

Individual examples of a single field of view, 1.35 X 1.055 m with particles as small as 1.2 x 1.2µm shows the metallic particles colored according to their key (right). Darker particles, which are lower atomic number non-metallics are not of interest for this analysis and remain unclassified (blue).

Figure 2. Individual examples of a single field of view, 1.35 X 1.055 m with particles as small as 1.2 x 1.2µm shows the metallic particles colored according to their key (right). Darker particles, which are lower atomic number non-metallics are not of interest for this analysis and remain unclassified (blue).

Collection Conditions

  • Collection speeds of 0.1 second per particle.
  • 1.2 million X-rays per second on the particles.
  • 500 kcps analytical throughput in stored data.
  • Spectral resolution stability at high count rates enables classification matching.

Example of copper and sulfur peaks in spectrum at 1.2 M cps and 0.1 sec collection time. Quant results confirm the particle is Cu2S, or more specifically, chalcocite.

Figure 3. Example of copper and sulfur peaks in spectrum at 1.2 M cps and 0.1 sec collection time. Quant results confirm the particle is Cu2S, or more specifically, chalcocite.

Fracking or drilling uses the oxidization of pyrite in the shale to degenerate it and also in areas having higher concentrations of pyrite in the shale rock, making drilling significantly easier. As a result, appropriate search and classification of pyrite is a major aspect of system performance.

Figure 4 shows the quantitative precision validating compounds such as pyrite. Other compounds were matched in accordance with the class library based on the quant results: chalcocite (Cu2O) and chalcopyrite (CuFeS2).

Quantitative analysis of the particles showing extreme performance quality at 0.1 second collection time at approx. 1.5 million cps.

Figure 4. Quantitative analysis of the particles showing extreme performance quality at 0.1 second collection time at approx. 1.5 million cps.

More than 30,000 metallic particles out of 60,000 + particles were examined in a 142mm2 area of the sample in one overnight run.

  • Particles counted: 62133
  • Particles analyzed: 60376
  • Stub % covered: 37.13
  • Area covered (sq. mm): 142.38

Data review enables particles to be sorted in accordance with association and contribution in a ternary diagram, as shown in Figure 5.

In this ternary view, S (red), Cu (green) and Fe (blue) were selected and each particle was displayed on the diagram according to its contribution from each of the elements, the colors are blended accordingly and the size of the particle is also displayed. This diagram is interactive, so when clicking on the area between S and Fe, an FeS particle will be selected and quant can be performed, leading to the FeS2 spectrum and quant above.

Figure 5. In this ternary view, S (red), Cu (green) and Fe (blue) were selected and each particle was displayed on the diagram according to its contribution from each of the elements, the colors are blended accordingly and the size of the particle is also displayed. This diagram is interactive, so when clicking on the area between S and Fe, an FeS particle will be selected and quant can be performed, leading to the FeS2 spectrum and quant above.

Conclusion

The EDAX Octane silicon drift detector series enables ultra-fast collection of particulate data, leaving out collection from the substrate and collecting only from areas of interest. With collection rates more than 1 M cps, 10+ particles per second are obtained with adequate quality and signal to classify and calculate the particles of interest. The Octane SDD system instantly provides large amounts of data for characterization and thus allows analysts to locate optimal drilling sites.

About EDAX Inc.

EDAX is the global leader in Energy Dispersive X-ray Microanalysis, Electron Backscatter Diffraction and Micro X-ray Fluorescence systems. EDAX manufactures, markets and services high-quality products and systems for leading companies in semiconductors, metals, and geological, biological, material and ceramics markets.

Since its founding in 1962, EDAX has utilized its knowledge and expertise to develop ultra-sensitive silicon radiation sensors, digital electronics and specialized application software that facilitate solutions to research, development and industrial requirements.

EDAX is a unit of AMETEK Materials Analysis Division. AMETEK, Inc. is a leading global manufacturer of electronic instruments and electric motors with annualized sales of more than $1.8 billion.

This information has been sourced, reviewed and adapted from materials provided by EDAX Inc.

For more information on this source, please visit EDAX Inc.

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