Potential Microbial Enhanced Oil Recovery Processes: A Critical Analysis
Bibliographic record
Abstract
Abstract This paper summarizes a critical review of possible microbially enhanced oil recovery (MEOR) methods and mechanisms to identify the most plausible utilization of microbial technology to enhance oil recovery. This paper is intended to stimulate discussion about broad applications of MEOR to field-wide improvement of oil displacement and recovery. The potential benefits of different MEOR mechanisms were examined for a representative North Sea reservoir of sandstone containing a light crude oil. In each case, the material input requirements for nutrients and inoculum were calculated in relation to the projected incremental oil production, assuming that the key components (bacteria, nutrients, or bacterial products) were uniformly distributed in the swept zone of the reservoir. The capillary number for the reservoir suggested that incremental oil recovery by biosurfactant production in situ would be modest under ideal conditions. The achievable yields would be lower because the Microbiol. in the reservoir would not be controllable to achieve sustained surfactant production. Losses of biosurfactants by adsorption to reservoir rocks and in situ biodegradation would further limit performance. The stimulation of surface active bacteria in the reservoir may affect the flow of fluids by producing emulsion droplets of oil coated with bacteria. The formation of a biofilm at the oil water interface changes the rheology of the interface, and may provide a useful mechanism to control mobility and areal sweep in reservoirs. Any mechanisms that required changes to large volumes of reservoir material, to produce gases, solvents, acids, or to significantly alter permeability, were not considered to be feasible. The limiting case of plugging fractures with bacteria and their polymeric byproducts does have considerable potential, but only for reservoirs which offer significant improvements in production with minimal injected volumes. The biological deposits must retain longer term resistance in situ to ensure that the anticipated production increase is achieved. This study provides a methodology for the systematic assessment of MEOR proposals using well-established reservoir engineering principles.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".