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X-Ray Analysis Used to Predict Sulfur Corrosion Rates in Crude Oil

Engineers are hoping to better predict the corrosion rates from crude oil that passes through various pieces of refinery equipment.

Scientists at the U.S. Department of Energy’s SLAC National Accelerator Laboratory (Menlo Park, California, USA), operated by Stanford University (Stanford, California, USA), are working on the development of a new analysis tool to better predict the corrosion rates of sulfur compounds in crude oil.

Driven by x-ray analysis, the work is part of ongoing experiments with the SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL) division. In the project,1 researchers from Chevron (San Ramon, California, USA) and the University of Saskatchewan (Saskatoon, Saskatchewan, Canada) are performing a series of studies at SSRL to closely examine different forms of sulfur in crude oil.

“By looking at crude oil with a combination of x-ray spectroscopy techniques, we were able to examine and describe the complex chemistry of the sulfur compounds with high specificity,” says Monica Barney, a materials research engineer at Chevron who led the project. Compounds found frequently in crude oil include thiophenes and aromatic sulfides.

Barney’s company processes oil each day at many of its refineries and petrochemical sites around the world, and a better understanding of precise corrosion rates at the high temperatures found in processing plants could allow the company to take better preventive measures for its equipment.

Historic Data Collection Methods

According to Barney, the sulfur present in crude oil can react with the metals in various types of equipment at the company’s plants and cause damage. As such, these reactions must be considered and accounted for by engineers to ensure safe and reliable processing.

While the total amount of sulfur can be measured in crude quite easily, high sulfur concentrations do not always correlate with high levels of corrosion, she says. As a result, this makes it challenging to anticipate how corrosive a particular crude oil will be at elevated temperatures.

“We can measure the concentration of sulfur, but it doesn’t tell you about the reactivity,” Barney says. “Knowing the type of sulfur in crude oil is critically important for predicting properties related to corrosion.”

The collaboration between representatives of the operator and university began when Barney was working on a separate corrosion study at SSRL. After collecting the data, she says her team struggled with how to interpret the complexities they saw in the results.

For years, Barney says, the industry practice has been to use a compilation of field data showing the corrosion rate as a function of time for a set of various commonly used alloys. Known as “modified McConomy curves,” this practice shows the corrosion rate as a function of temperature, using empirical data of crudes with 0.6 wt% sulfur. To account for differences in sulfur content, there is a correction factor that scales these rates with total sulfur content.

However, this method does not account for different types of sulfur, whose reactivity can vary by more than an order of magnitude depending on the composition—particularly at elevated temperatures, Barney says.

Spectroscopic Analysis Technique

In seeking answers, Barney’s team searched online and came across a diagram from University of Saskatchewan professors Graham George and Ingrid Pickering, who were formerly on the SSRL staff. Both professors had conducted molecular biology and toxicology experiments at the SSRL facilities.

The diagram showed spectroscopy information gathered from the superimposition of data on many sulfur types, similar to what is seen in crude oil. It showed how comparing an overall spectrum to a library of standards could identify individual types of compounds—thus allowing for a more detailed breakdown of the sulfur composition in various crude oil types.

“When I came across this figure, I thought, ‘This is it. This is what we need.’ It’s what we’d been seeking for years—a characterization method that could quantify the amounts of each type of sulfur,” Barney says.

The idea was to use the same technique—sulfur K-edge x-ray absorption spectroscopy—to measure and determine the types of sulfur in crude oils. Both university professors had worked previously in oil and gas, and Barney says their expertise was a perfect match with what Chevron wanted to study.

To address the problem, they developed an approach to examining oil with “tender x-rays,” which represent an intensity between high-energy and low-energy x-rays. Tuned to the correct energy, x-rays allow the researchers to collect detailed information about the sulfur and its chemical neighbors and help search through the overlapping information generated by similarities in the sulfur compounds. The strategy involves subjecting a thin layer of sample to the tunable x-ray beam, which collects certain signals from the sample and allows researchers to accurately predict the composition.

In their method, the sample can be crude oil, distilled fractions of oil, samples produced from its processing or extraction, or water samples made with crude oil. The sample can contain concentrations of sulfur and other elements ranging from as small as 100 ppm to about 2 wt%. The corrosion rate of the sample is then measured while the sample is exposed on the metal at high temperatures.

As one example, they say a sample can be introduced into an autoclave along with a coupon of the metal alloy being studied. The metal coupon can be in any size or shape, and the coupon is weighed and measured both before and after the autoclave test.

Alternatively, the sample and the alloy being studied can be contained in a probe to measure the real-time corrosion rate through examining changes in the resistance across the anode. In this case, the autoclave is capable of maintaining a temperature of up to 750 °F (398.9 °C), with a pressure of 1,000 psi (6.89 MPa). A coupon of the alloy is inserted into the crude oil-derived sample, and the autoclave is then sealed. The test temperature is then applied, thus agitating the oil. The metal is exposed to these conditions for a period of time, typically between 8 h and six months.

The corrosion rates of all of the samples are compared to the relative amounts of each species identified in all of the samples, respectively, to develop a correlation model or equation. This model relates the corrosion rates to the amounts of various elements found in a sample, such as sulfur, nitrogen, oxygen, and chlorine at specific ppm levels.

Improved Sulfidation Corrosion Predictions

The findings provide more detailed information about the relative amounts of sulfur in certain types of oil, which can be incorporated into current models to improve corrosion predictions.

In their initial studies thus far, results have shown large differences in high-temperature tests of steel coupons exposed to gaseous streams of individual sulfur compounds containing certain functional groupings found in different types of crude. For example, among these groups, disulfides have shown a greater sulfidation rate than thiophenes by at least an order of magnitude.

“This is an example of using state-of-the-art spectroscopy for a real-world application,” George says, adding that further tests are ongoing in 2018.

The x-ray analysis work is part of a larger collaboration by the operator, which says it is also using several other techniques in an attempt to better understand the chemistry of sulfur in crude oil. The operator's goal is to combine and compare experimental data from multiple chemical characterization methods with data from corrosion studies and predictions from computer modeling.

Source: SLAC National Accelerator Laboratory, www.slac.stanford.edu. Contact Graham N. George, University of Saskatchewan—email: g.george@usask.ca.

Reference

1 “Researchers Develop a Way to Better Predict Corrosion from Crude Oil,” 2017 News Feature Archive, Sept. 25, 2017, https://www6.slac.stanford.edu/news/2017-09-25-researchers-develop-way-better-predict-corrosion-crude-oil.aspx (Jan. 15, 2018).

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