Identification of Mechanisms and Parameters of Formation Damage Associated with Chemical Flooding
Bibliographic record
Abstract
Abstract This paper presents a practical methodology and its verification for determination of the mechanisms and parameters of chemically induced formation damage. It is based on interpretation of laboratory core flood tests by diagnostic straight-line plotting schemes. Laboratory tests were conducted to measure the permeability impairment and effluent conditions as a function of time by flooding sandstone and limestone outcrop rock samples with various alkaline solutions (NaOH, KOH, NaSiO4) and alcohol (ethanol) as might be used for improved oil recovery. The single-phase permeability variation data were plotted according to prescribed diagnostic straight-line plotting schemes proposed by Wojtanowicz et al. and Civan. Plots that result in satisfactory straight-line trends reveal the predominate mechanisms of the formation damage. Further, the values of the parameters of the governing formation damage processes are determined from the intercept and slope of the straight-lines. Higher pH solutions were observed to have caused greater reductions in rock permeability. Civan's model better described the permeability variation due to scale dissolution and precipitation processes. The Wojtanowicz et al. model identified the formation damage mechanisms as pore surface deposition and sweeping. Different rock damage conditions were observed for the initial and the later test periods, indicating that more than one formation damage mechanism was involved. The analysis of the same experimental data reveals that a numerical model such as UTCHEM will require significantly more information to perform a similar analysis of the laboratory flood results. However, the diagnostic equations provide a practical and rapid means for the determination of the formation damage mechanisms. The methodology developed in this paper can be used for rapid detection and quantification of the formation damage mechanisms from core tests. The technique can be useful in the design of alkaline-surfactant-polymer (ASP) and/or micellar flooding chemical systems for field applications.
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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".