The typical sample description log is a qualitative description of the rock samples recovered from the mud system during the drilling operations at a well site or from conventional or sidewall cores taken over specific intervals in the well. Semi-quantitative analysis can be done using a microscope and eyeball estimates of the quantities of each mineral present. This is a little imprecise but may resolve some issues.

X-Ray diffraction spectroscopy (XRD) is another quantitative method for description of the mineralogy of cuttings or core samples.

Infra-red spectroscopy is a somewhat newer technology. Infra-red analysis of washed samples can resolve most minerals, including clays and organics, into a quantitative breakdown. It can be performed at the well site, as part of the other sample description and gas logging process (measurements while drilling) or in a laboratory after drilling the well.


There are two types of infra-red spectroscopy. The most common is transmission, or absorption, infra-red spectroscopy, in which the spectra are inverted to a mineral assemblage by a Fourier Transform algorithm, commonly abbreviated as FTIR. Another independent method is diffuse reflection infra-red Fourier Transform spectroscopy, better known as DRIFTS. DRIFTS is newer, faster, and cheaper than conventional FTIR. Although the transmission and reflection spectra are quite different in appearance, both techniques give very similar results.

Samples from cores can also be used. Small samples (0.5 to 1.0 grams) are crushed and placed in the FTIR apparatus, where IR absorption spectrum is scanned with a broad range of infra-red frequencies. Each mineral, liquid, and gas has a unique spectrum, allowing the software to identify each mineral by comparing to pure mineral spectra.

Multiple scans of the same sample are used to increase signal to noise ratio. With the most recent development of wellsite instruments, a typical measurement takes two to three minutes. Results in weight percent or mass fraction are stored on disc and displayed on request. Sample preparation can take a few minutes as well. 


FTIR absorption spectra for calcite and quartz after being processed by the Fourier transform software. The peaks are due to covalent bonds in the molecules and give a unique pattern for each mineral. The relative amplitudes of peaks compared to pure mineral standards are used to estimate the quantity of each mineral present in a mixture.  (image: Ana-Min)


A log of results versus depth is constructed by the FTIR software package and can augment the conventional sample log or stand alone for comparison to wireline or computed log analysis results.


An FTIR quantitative sample log, measured in weight percent, with interpreted lithology description (images courtesy of Ana-Min)

Tabular listing of FTIR quantitative mineralogy, measured in weight percent, can be loaded into petrophysical analysis software in a manner similar to core analysis or XRD data, to assist in calibrating analysis results. Note the availability of TOC data in this example.


The technique is quite new and not yet widely used at the wellsite. It has applications in conventional and unconventional reservoirs, including shale gas, tight oil, and coal bed methane. It can provide a quantitative estimate of total organic carbon (TOC) and quantitative mineralogy and clay volume without waiting to transport and analyze samples in the laboratory. Since it is a near-real time measurement, it can assist in geo-steering of horizontal or deviated wells.

The example below is from "Kerogen Content and Maturity, Mineralogy, and Clay Typing from DRIFTS Analysis of Cuttings or Cores", M.Heron et al, Petrophysics, Oct 2014.


DRIFTS analysis of core samples from the Montney formation in Alberta. Note that clay content averages about 30% by weight, quartz-carbonate ratio is about 50:50, and carbonate is mostly dolomite (with minor calcite-rich layers). Kerogen is about 3%. Although pyrite weight fraction usually is in the 3 to 8% range in this interval, none is shown in this example.

DRIFTS example from cuttings in Marcellus Shale. Clay-quartz ratio is near 50:50 with little carbonate. Kerogen runs 4 to 12% by weight. Colour codes same as previous example.

Comparison of DRIFTS and FTIR methods on the same core samples from the Montney example shown earlier.





Infra-red radiation Is a form of electromagnetic radiation with frequencies between those visible to humans and those familiar as radio waves. Ultra-violet, X-rays, and gamma rays are at higher frequencies.


The radiation spectrum shows the infra-red to the lower frequency side of the visible light region. Ultra-violet, X-ray, and gamma rays are on the high frequency side of the visible spectrum.

Some definitions are in order:
      1:  Wavelength = 10^4 / Wave Number (microns)
      2: Wave Number = 10^4 / Frequency ((reciprocal centimeters - cm^-1)
      3: Wavelength = 2.9979 * 10^4 / Frequency (meters)

In frequency terms, 1 cm^-1 = 2.9979 * 10^9 = 30 Ghz.

Infra-red energy obeys the same laws of transmission, reflection, and absorption as does visible light. The frequencies absorbed and reflected by each substance have a unique frequency spectrum or signature,  which depends on the molecular structure of the substance.

FTIR spectroscopy relies on detection of covalent bonds or molecular group vibrations. Mineral identification is possible because minerals have characteristic absorption bands in the mid-range of the infrared (4000 to 400 cm-1). The concentration of a mineral in a sample can be extracted from the FTIR spectrum because the absorbance of the mixture is proportional to the concentration of each mineral. This is given by Beers Law:
      4: A = SUM (Cj * Ej * L)

  A = absorbance of a mineral mixture at a given wavenumber
  Ej = absorbtivity of component j
  L = the absorption path length (pellet thickness)
  Cj is the concentration of component j.

All multi-component analyses are based on Beer’s law, and the absorbance at a specific wavenumber is the sum of the absorbance of all sample components that absorb at that wavenumber. Since the spectrum covers a wide range of wavenumbers, a non-negative least squares solution to the Cj concentration values is possible.


Source: Wikipedia

The goal of any absorption spectroscopy is to measure how well a sample absorbs light at each wavelength. The most straightforward way to do this, the "dispersive spectroscopy" technique, is to shine a monochromatic light beam at a sample, measure how much of the light is absorbed, and repeat for each different wavelength. 

Fourier transform spectroscopy is a less intuitive way to obtain the same information. Rather than shining a monochromatic beam of light at the sample, this technique shines a beam containing many frequencies of light at once, and measures how much of that beam is absorbed by the sample. Next, the beam is modified to contain a different combination of frequencies, giving a second data point. This process is repeated many times. Afterwards, a computer takes all these data and works backwards to infer what the absorption is at each wavelength.

The beam described above is generated by starting with a broadband light source, one containing the full spectrum of wavelengths to be measured. The light shines into a Michelson interferometer, a certain configuration of mirrors, one of which is moved by a motor. As this mirror moves, each wavelength of light in the beam is periodically blocked, transmitted, blocked, transmitted, by the interferometer, due to wave interference. Different wavelengths are modulated at different rates, so that at each moment, the beam coming out of the interferometer has a different spectrum. The raw data is sometimes called an "interferogram".

As mentioned, computer processing is required to turn the raw data (light absorption for each mirror position) into the desired result (light absorption for each wavelength). The processing required turns out to be a common algorithm called the Fourier transform. The interferogram belongs in the length domain. Fourier transform inverts the dimension, so the transform of the interferogram belongs in the reciprocal length domain, that is the wavenumber domain. (end of Wiki extract)

Once the FTIR spectrum has been obtained, the peaks and valleys on the wave number graph can be compared to standard graphs for pure minerals recorded in a catalog. By identifying particular peaks, the minerals present can be identified. The amplitudes of the peaks are used to estimate the quantity of each mineral. Hardware suppliers have created proprietary software that can quickly compare thousands of possible combinations to find a match to the measured spectrum. The task is simplified by choosing an appropriate mineral "package" that best represents the rock sequence, thus reducing the number of comparisons required. That mineral package contains the spectra for a few to a few dozen pure minerals.

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