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In this work, low-temperature oxidation (LTO) of a heavy oil sample from Alaska has been investigated. Six isothermal and one non-isothermal experimental runs were conducted between 100 and 350 °C, where LTO dominates. The combustion data obtained from a thermogravimetric analyzer (TGA) was analyzed, and a comparison has been made between the kinetic parameters (reaction order, rate constant, and activation energy) from a first-order, general reaction rate and Segal and Fatu's approach. The temperature scan of the oxidation process revealed that there were four temperature intervals during which different modes dominated the LTO process. The first temperature interval, ranging from 100 to 150 °C, and the third interval, ranging from 200 to 250 °C, both had overall reactions that were endothermic. However, in the second zone from 150 and 200 °C and the fourth subzone from 250 to 350 °C, exothermic reactions were dominant. The peak LTO rate occurred during the fourth interval, from 250 to 350 °C, and exhibits a decreasing rate versus temperature: the greater the temperature, the lower the reaction rate. The results obtained from the isothermal runs reveal that the reaction rate constant, activation energy, and pre-exponential factor for each temperature (determined from the first-order rate model) are all higher than those measures obtained in the general reaction rate model. The results from the non-isothermal runs showed that the values of the reaction rate constant, activation energy, and pre-exponential factor obtained from the approach by Segal and Fatu are similar to those calculated from the general reaction rate model. This was particularly true for the LTO peak temperature. The analysis of the results yields the mean activation energy for the LTO peak equal to 1130.2 cal/mol for isothermal experiments.

In situ combustion (ISC) based enhanced heavy oil recovery is complex because there are numerous chemical reactions taking place simultaneously, in addition to mass transport and flow mechanisms, within the context where oil mobility is controlled largely by its temperature which in turn is controlled by heat transfer all occurring in a reservoir typically several hundred meters deep where geological heterogeneity is uncertain. From a reaction point of view, the complexity arises due to the immense number of components reacting through many different reaction paths in an underground system where the geology and heavy oil saturation vary spatially within the reservoir. It is known that there are four major classes of reactions taking place within an ISC process: low temperature oxidation (LTO), high temperature oxidation (HTO), thermal cracking (TC), and aquathermolysis. Within the reservoir, during ISC, LTO and TC reactions play a major role by providing fuel for HTO. In many documented reaction schemes in the literature, the LTO interval is considered as a single reactive zone spanning a single temperature range. In this work, a new reaction scheme is proposed based on analysis of thermogravimetric data where the LTO reaction temperature range has been separated into three temperature subranges each with their own dominant set of reaction products. The results demonstrate that models of LTO with a single range are inadequate for LTO modeling whereas multiple subranges were capable of representing the behavior of LTO effectively.

We demonstrate a new methodology for quantitative trend analysis (QTA) to analyze and interpret SARS-CoV-2 RNA wastewater surveillance results concurrently with clinical case data. This demonstration is based on the work completed under the Ontario (Canada) Wastewater Surveillance Initiative (WSI) by two laboratories in four wastewater treatment plants (WWTPs) at each of four large sewersheds, which were sampled over a 9-month period, along with sewershed-specific clinical case counts. The data from the last 5-months, representing a range of high and low case counts, was used for this demonstration. The QTA integrated clinical and wastewater virus signals, while combining recommendations from the United States Centers for Disease Control and Prevention (US CDC) and the Public Health Agency of Canada (PHAC). The key steps in the QTA consisted of signal normalization with pepper mild mottle virus (PMMoV), as a fecal biomarker, statistical linear break-point trend analysis and integration of both wastewater virus signal and clinical cases trend results. Using this approach, the wastewater virus and clinical cases trends, direction, and magnitude were clearly identified and provided a unified complementary tool to support public health decisions on a targeted, sewershed-specific basis.