Tallinn University of Technology

The chemical composition of oil shale needs to be determined to maximise its use, but current laboratory testing methods are very time-consuming and do not meet modern expectations. Is it possible to create a fast and modern testing method for oil shale? This is exactly what Iram Tufail (TalTech) has been researching.


In the context of green transition and energy crisis, the debate about the future of oil shale extraction and production in Estonia will continue in 2023. While one of the aspects focuses on phasing out of fossil fuels and transitioning to renewable energy sources, another aspect that cannot be overlooked is the rational use of oil shale. In this respect, there are no good news either.

‘In order to use raw material in the most efficient way, we need to know its chemical composition – this would allow us to choose the best use and manner of processing for a particular rock,’ says Jaan Kalda, professor at TalTech and supervisor of the doctoral thesis of Iram Tufail. According to him, one of the main issues for the oil shale industry is the chemical composition of oil shale varying widely. ‘This is a stumbling block both in the energy sector, where oil shale is simply burned, and in the chemical industry, where it is used as raw material in various production processes.’

In his thesis, supervised by renowned Estonian physicists Jaan Kalda and Matti Laan, Iram Tufail studied optical methods for determining the composition of rocks. Experiments were carried out at the Institute of Physics of the University of Tartu. The efficiency of oil recovery as well as other forms of oil shale valorisation depend on the data on the organic and inorganic composition of the raw material. Unfortunately, current laboratory methods of oil shale testing are time-consuming and may not be adequate for the real-time monitoring and managing of an on-going production process. Optical methods, which allow the real-time monitoring of continuous processes, do not require contact and are user-friendly.

What is the LIBS process?

In the research cycle, Tufail focused on laser induced breakdown spectroscopy, or LIBS, which uses a laser to vaporise a small amount of target material and record the resulting plasma spectrum. The results are compared with those obtained by another optical method – diffuse reflectance spectroscopy (DRS). The aim of the thesis was to evaluate the feasibility of using LIBS for the determination of the calorific value and moisture content of oil shale lumps under conditions close to those of industrial ones.

‘Standard practice has been to take samples of oil shale to a laboratory to determine their composition. The production is based on the assumption that the composition of the whole larger batch is the same as the samples brought to the laboratory. However, this assumption is often not true. In the interests of the most efficient use of oil shale, it would be great if the chemical composition of the lumps moving on the conveyor could be monitored in real time and the material could be sorted according to its composition. However, the current methods of determining the composition of rocks are not fast enough and the process is too expensive,’ Jaan Kalda comments.

The complicated study required effort

Rock specimens were collected from the oil shale layers of the Narva quarry and from the conveyor belt of the Estonia mine beneficiation plant. Traditional laboratory methods were used to calibrate optical measurements. The gross calorific value was determined by calorific bomb method and the moisture content was determined by weighing. This way, a total of 75 oil shale lumps with different calorific values and/or moisture contents were collected for testing.

Experiments were carried out in ambient air in a laboratory at atmospheric pressure. Oil shale lumps of different size and orientation were placed on a rotating stage imitating a conveyor belt. The test results of the lumps were compared with those obtained from the powder pellet samples.

In the LIBS set-up, a pulsed Nd:YAG laser was used, while DRS measurements were performed with an industrial multi-purpose analyser.

How was the LIBS data processed?

The first step in the pre-processing of the LIBS data was to find the calorific value and the covariance values of the spectral lines of different elements, as well as the covariance between the different spectral lines (covariance expresses the co-variation of two quantities). Based on this information, a set of spectral lines was selected for further analysis. The correlation of the carbon line with the calorific value was strong, while the effect of moisture content was small. However, the accuracy of the calorific value prediction based on the carbon lines was found to be insufficient and a multivariate linear regression model was used to estimate the calorific value and moisture content of the lumps. The obtained results demonstrated that the minimum standard deviation of the prediction is achieved with a set of ten spectral lines.

A partial least square linear regression algorithm from the multi-purpose analyser software was selected to process the DRS data.

The calorific value prognosis of the lumps was characterised by a standard deviation of 1.76 MJ kg–1 and the standard deviation of the moisture content was 1.94%. The characteristic values for DRS were 0.85 MJ kg–1 and 1.35%, respectively. However, the standard deviation of the calorific value of air-dry powder pellets was 0.24 MJ kg–1.

Two important reasons emerged

A comparison of these figures allowed us to identify two main reasons that determine the standard deviation of oil shale lumps. The first reason was the uncertainty of measuring the moisture content. However, this uncertainty can probably be significantly reduced when using a real conveyor belt.

The second reason was the assumption that the relationship between spectral lines and calorific value is linear, but by using quadratic dependence to estimate the dependence between these values, the standard deviation of the calorific value was found to be close to the standard deviation of the DRS.

In addition to the determination of calorific value and moisture content, LIBS allowed the determination of the concentrations of the main chemical compounds of oil shale with an accuracy of 5%.

The new method delivers speed and quality

The research results showed that LIBS is a method that allows the real-time monitoring of oil shale properties. Professor Jaan Kalda, who supervised the thesis, admits that the laser ablation method is indeed well-suited for the real-time analysis of rocks. ‘The principle of the novel technology is that short laser pulses vaporise the surface layer of the rocks; the laser pulse also excites the vaporised molecules and the spectrum of the resulting radiation can be used to determine the chemical composition of the rocks with data analysis methods.’

Iram Tufail’s PhD thesis ‘Fast Assessment of Oil Shale Quality by Spectral Methods’ is available in the digital collection of TalTech.