An Experimental Study on Three-Phase Flow in High-Pressure Air Injection (HPAI)
Bibliographic record
Abstract
Abstract High Pressure Air Injection, (HPAI) is an improved oil recovery process in which compressed air is injected into typically deep, light oil reservoirs. Part of the oil reacts exothermically with the oxygen in the air to produce flue gas (mainly composed of nitrogen, carbon dioxide and water). Literature explaining the reaction mechanisms and phase interactions is available. Nevertheless, little effort has been devoted to describing gas, oil, and water three-phase flow behavior under HPAI reservoir conditions. Three coreflood experiments were conducted on Berea sandstone core. The first experiment consisted of injecting flue gas into core at initial oil and connate water saturations to obtain liquid-gas relative permeability data. The second experiment was designed to evaluate oil re-saturation, after gas sweep, simulating an HPAI thermal front. The third experiment consisted of gas displacing both oil and water completing the data necessary to plot the three phase relative permeability curves. Reservoir simulation was used to adjust relative permeability curves and hysteresis parameters by matching the pressure drop and production data. Introduction It is well known that the oil recovery mechanisms in HPAI are a combination of the highly efficient displacement by the reaction front and the light oil/flue gas compositional interactions such as oil swelling and/or vaporization and nearmiscible behavior1. However, the contribution of each of these recovery mechanisms has not been properly assessed2. Although an important amount of effort has been devoted to the characterization of oxidation kinetics3-5 and flue gas/light oil compositional interactions6,7, the process remains challenging to simulate even under controlled and ideal conditions, i.e. a combustion tube test. Some of the difficulties include the limited availability of experimental data to feed the numerical simulators with the required parameters, as well as the interdependence of these parameters and their variation with temperature. Assuming that these difficulties can be overcome by carrying out a study that allows a judicious analysis of experimental information and a careful treatment of the matched parameters in a numerical simulator, there is still a piece of information that has a strong influence on the simulation results and cannot be defaulted or left as a final matching tool: relative permeability. In an earlier study2, it was suggested that for a combustion tube match, the steps previous to air injection (water flood, and inert gas flood) can be used to find a reliable set of relative permeability curves for the run. It was also pointed out that the rock-fluid dataset should include a variation of relative permeability data with interfacial tension to account for changes in pressure, composition, and most importantly, temperature. While being this necessary, it still would not be sufficient to ensure a correct representation of the flow of phases in a porous medium subjected to HPAI. Ahead of the reaction front, the high mobility flue gas (mainly composed of nitrogen and carbon oxides) displaces oil and water at nearly reservoir temperature, while in the high temperature zone the gas flooded volume is re-saturated with oil and water that have been removed from the burnt or reacted volume. In both zones, three-phase flow is occurring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".