Determination of Increase in Pressure Drop and Oil Recovery Associated with Alkaline Flooding for Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract Alkaline flooding is a promising technique for enhancing heavy oil recovery, especially for thin reservoirs where other processes are not practicable. During alkaline flooding, oil recovery is increased by improving sweep efficiency as a result of in-situ formation of water-in-oil (W/O) emulsions. Even though flow of oil-in-water (O/W) emulsions in porous media has been extensively studied and well simulated, few attempts have been made for studying flow of W/O emulsions. In this study, techniques have been developed to determine increase in pressure drop and oil recovery associated with alkaline flooding for heavy oil reservoirs. Experimentally, both differential pressure and oil recovery are measured in an alkaline flooding process for heavy oils, while the associated emulsification is also studied. More specifically, the alkaline solutions are prepared with different concentrations of NaOH, while increase in pressure drop and oil recovery are measured and analyzed. Two different porous media are well prepared and accurately measured for their physical properties. Theoretically, a simulation technique is developed to model and match the experimental measurements for the alkaline flooding processes. Increase in differential pressure and oil recovery are found to be the two key parameters for determining the overall efficiency of the alkaline flooding for enhancing heavy oil recovery. The in-situ emulsification is found to be closely related to reduction of the injected water mobility so that increase in pressure drop is observed and the oil recovery is improved due to blocking the high permeability zone (or water channels) induced by the preceding waterflooding. Introduction Enhanced oil recovery (EOR) plays an increasingly important role in the petroleum industry for both light and heavy oil reservoirs. In general, after primary recovery and secondary recovery, it is found that the oil remaining in the light and medium oil reservoirs is generally in the range of 50–60% of the original oil in place (OOIP) and that the oil left in the heavy oil reservoirs is much higher. Among the EOR methods, alkaline flooding for the light and medium oil reservoirs have been studied extensively[1]. In spite of some technical successes in the oilfields, few economic successes have been documented because of the high cost of the injectants[2]. At present, conventional oil reserves are depleting, while there exists huge challenge to develop the heavy oil reservoirs. In practice, few attempts have been made to study the alkaline flooding for heavy oil reservoirs mainly due to the fact that the multiphase flow of heavy oil in reservoir formation is a more complicated process than that in conventional oil reservoirs. Therefore, it is of fundamental and practical importance to study the alkaline flooding process for heavy oil reservoirs. Alkaline flooding, also known as caustic flooding, is an EOR technique where an alkali, such as sodium hydroxide, sodium orthosilicate or sodium carbonate, is injected into hydrocarbon reservoirs during waterflooding stage[3]. Although dominant mechanisms for heavy oil production have not been well understood, emulsification mechanism is discovered to be one of the most important phenomena occurring in alkaline flooding process[4–6].
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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".