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Asphalt quality prediction and control

With knowledge of heavy vacuum gasoil cut-point and asphalt density, asphalt quality can be inferred

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Article Summary
Much has been written about crude column product separation by advanced process control (APC) but very little about vacuum column APC. Why? Vacuum distillation unit separation is important, especially in asphalt mode, when vacuum pitch is sold as a premium product, and controlling asphalt quality is high on the list of economic priorities. One guess is that such APC applications have not been reported because of inability to infer asphalt qualities, and without such inference vacuum column APC would not be effective. Recently, Petrocontrol had the opportunity to set up asphalt quality inferential models at two refineries; this article describes the inferential techniques and shares the inferential performance data.

Both refineries are located in North America. Refinery A is a land-locked refinery and throughput is limited by asphalt sales. The product grades vary from shingles to road asphalts. Refinery B runs mostly road asphalt by blocks and only from certain crudes. In summer, asphalt is the most lucrative refinery B product.

Asphalt quality is typically measured by dynamic shear rheometer (DSR) apparatus, where the number reported as G*/Sin(delta) is a measure of viscosity at a given temperature. Our DSR inference relies on the knowledge that asphalt viscosity correlates with average boiling point and density. The average asphalt boiling point is estimated from column measurements, but for density we need the aid of a density analyser. Without online density measurement, DSR inference is not plausible.

Refinery A had installed a density meter and developed asphalt DSR inference several years ago but the model was less than perfect. It would predict adequately for a few days, and then suddenly would have to be biased substantially, even when the crude had not changed. That had caught us by surprise. What was going on? Operation has not changed much but the lab test is suddenly showing a different value. Upon studying the DSR test we realised it is carried out at several defined temperatures of 46, 52, 58, 64 or 70ºC, the specific test temperature being a part of the asphalt grade specifications. During asphalt runs the schedulers switch grades often; carried out at different temperatures, the lab test would yield different results. The operator, not being aware of the change of DSR test temperature, views the sudden lab–inference discrepancy as a sign of problematic inference and turns off the APC.

The vacuum column configuration
Figure 1 shows a typical vacuum column configuration. Reduced crude feed comes from the atmospheric crude column through a furnace and into the flash zone. There are two distillate products: light vacuum gasoil (LVGO) and heavy vacuum gasoil (HVGO). LVGO is diesel range material, going into the diesel pool. HVGO is FCC or hydrocracker feedstock. There is a possibility to also draw vacuum wax, though normally wax is circulated back to the furnace to improve the separation. As is common in vacuum column designs, the draws are from total draw trays. Part of the draw is pumped around through heat exchangers to cool the column, another part is pumped down as reflux, and a third part is taken out as product.
Density measurement
As Figure 1 shows, due to the limits of density meter temperature asphalt is cooled to a temperature of about 215-240°C (420-470ºF) before being measured. Density is a function of temperature and we need to correct the raw density reading to a standard temperature of 15°C (60ºF) before using it in a DSR correlation. The laboratory also measures asphalt density at 15°C, and this permits comparison of the analyser corrected density against lab values. Figure 2 shows a six-months trend of density related measurements. The orange line is raw density as measured online (VBAPI_A). The magenta line is the density meter temperature (TVDEN) on the right hand scale. The blue line is our correction of the density meter to 15°C (VBAPI_M), and the green squares are lab tests of asphalt density (APIVB_L). The corrected density meter reading more or less trends with lab density though that agreement is not perfect. One might expect slow drifts and a need to occasionally bias the density reading and/or DSR correlation.

The GCC inferential package
Generalised cut-point calculations (GCC) is a well established inferential package for wide cut fractionators such as the crude and vacuum distillation units. GCC uses column measurements to first identify the true boiling point curve for the feed, and then it estimates product cut-points. Being a first principles based model, GCC has performed better than other methods, and has in addition the ability to infer cut-points during crude switches. Several GCC related papers have been published,1-7 and it is not the object of this article to cover additional GCC sites beyond saying that HVGO cut-point is predicted well. That is important for the asphalt inference because HVGO back end cut-point is identical to asphalt front end cut-point. Figure 3 shows a one-year trend of HVGO 98% point inference model (HVG98_M) against lab tests (HVG98_L).

HVGO 98% is predicted from HVGO cut-point, and the high fidelity of this prediction indicates that the HVGO cut-point is well estimated. That trend is for refinery A. We cannot show the equivalent refinery B trend because refinery B does not test the HVGO distillation curve.

Is the front end asphalt cut-point good enough for this inference? Viscosity is, after all, a function of asphalt average boiling point. In calculating asphalt average boiling point our model assumes the asphalt effective back end cut-point to be 800ºC. Given that asphalt effective endpoint is indeed around 800ºC the magnitude of crude to crude inferential variation is fairly small.

DSR modelling
There is a way to consider DSR lab tests carried out not only at one temperature in isolation but also at other test temperatures. Given the sensitivity of viscosity to temperature, there is a certain temperature called TE, such that if the DSR test were to be carried out at TE the test result would have a value of precisely 1.00 KPA. The DSR- temperature model we are using is:

ln[G*/Sin(delta)test] = B * [1/TE – 1/Ttest]                         (1)

Where Ttest is the test temperature in ºK and G*/Sin(delta)test is the DSR outcome of that test.
With knowledge of coefficient B, Equation 1 permits calculation of TE from a DSR test result at any temperature. Refinery A tests the same asphalt sample at different temperatures and for a given test sample the TEs calculated from test results at different temperatures should be identical. Thus, even if the viscosity-temperature relationship is not precisely known the many lab tests at different temperatures give us the opportunity to calibrate the temperature influence.

Figure 4 tests this concept, covering 20 days of TE calculations. The lab tested samples at 46 (TE46_L), 52 (TE52_L), 58 (TE58_L) and 64ºC (TE64_L). The reported DSR results are very different at each temperature because viscosity is quite sensitive to temperature, but the calculated TE values coincide within half a degree. The fifth green square lab value in Figure 4 (DSR_L) is a laboratory calculation of TE based on interpolation among the several test results. Finally, the blue trend of Figure 4 is a TE inference as a function of VGO cut-point and asphalt density readings. While not perfect, this inference tracks the lab well and can reliably be used for control.
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