New Insights on Catalysts-Supported <i>in situ</i> Upgrading of Heavy Oil During <i>in situ</i> Combustion Oil Recovery
Bibliographic record
Abstract
Abstract As part of GHG reduction initiatives, there have been many publications on CO2 capture, utilization, and storage (CCUS), reducing the carbon footprints in the oil and gas production, switching to renewable energies, and generating carbonless fuel (e.g., H2) via in situ processes. In situ upgrading of bitumen and heavy oils and converting them into low sulfur, low N2, and low asphaltene can help with both producing cleaner fuel as well as utilizing vast resources of energy that could otherwise be wasted due to extreme measures of no fossil fuel policies. Additionally, such processes could produce valuable products, enhanced shipping/pipelining, and less demanding downstream processing. Generating hydrogen could be another focus area for in situ upgrading. This paper provides new insights into the results of several combustion tube tests that were performed for Alberta Ingenuity Centre for In Situ Energy (AICISE) using different heavy oils with fresh supported catalyst. The catalysts were placed in the production end of the combustion tube so oil would pass over the catalyst bed before being produced. In practice, solid catalyst particles could be placed into the oil-bearing formation adjacent to the producing wellbore, ensuring that crude oil will flow over the catalysts during oil production. This paper utilizes many of the lab results that have never been published before. The objective is to understand whether using catalysts has merits in our future oil production activities under the current environmental restrictions. A commercial Ni/Mo catalyst was used in these tests. The results of these tests indicated at least temporary significant occurrence of reactions such as: hydroprocessing (HP), hydrotreating reactions, such as hydrocracking (HC), hydrodesulfurization (HDS), hydrodenitrogenation (HDN) and hydrodeoxygenation (HDO). We will discuss the impact of pressure, temperature, water injection and dispersed versus supported catalysts on the degree of oil upgrading. Also, the key parameters that could impact in situ hydrogen generation will be presented. Specifically, the role of reactions such as Aquathermolysis (AQ), thermal cracking (TC), water-gas shift reaction (WGS) and coke gasification (CG) will be discussed. Notice that the products of these reactions could undergo additional methanation reactions (ME) which could reduce the H2 concentration in the produced gas. Finally, methods of upscaling these results to the field conditions will be presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".