Simulation Studies on the Mechanisms and Performances of MEOR using Polymer Producing Microorganism <i>Clostridium</i> sp. TU-15A
Bibliographic record
Abstract
Abstract Polymer-producing microorganism Clostridium sp. strain TU-15A was isolated from reservoir brine of Jilin Oilfield, China. TU-15A produces polymer in a molasses medium and increases the viscosity of the culture solution to 70cP by 10days cultivation. It's expected to be an effective microorganism for MEOR. In this study, a simulator was developed in order to analyze the mechanisms of MEOR using polymer-producing microorganism. The numerical model in this simulator consists of 2-phases(oil and water) and 5-components(oil, water, microorganism, nutrient and polymer). This model includes almost all processes of MEOR such as growth and death of microorganism, nutrient consumption, polymer production, water viscosity increment, improvement of the flow profile in a reservoir and enhancement of oil recovery. The validity of this simulator was shown by a comparison of both results of the numerical simulation and a flooding experiment. The quantitative change of microorganism, nutrient, polymer(water viscosity) and oil saturation were analyzed by a simulation of MEOR using polymer-producing microorganism on quarter of fivespot pattern flooding. Regarding the alteration of flow pattern in the reservoir, it was found that (1) the polymer produced by microorganism in reservoir flew into the main flow channel along the shortest way between the injection and production wells and water viscosity there increased, (2) subsequently more uniform flow profile of injected water as a postflash was established, and (3) the residual oil was mobilized to the production well. The additional oil recovery of 10% or higher was obtained at the early stage of the postflash. Our simulator will be a first comprehensive simulator for MEOR using an existing strain that produces polymer strongly. By using this simulator, the phenomena occurred in a reservoir on MEOR using a polymer-producing microorganism have been clarified and the high performance of this MEOR process have been demonstrated.
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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".