A Novel Coreless Injectivity Technique for Evaluating Formation Damage in Argillaceous Reservoirs
Bibliographic record
Abstract
Abstract For waterflooding in argillaceous reservoirs, the injection water needs to be carefully designed to avoid formation damage by clay swelling and migration. Common methods of achieving this are compatibility tests of injection water with formation water and rocks and injectivity tests. However, such tests are often not practical nor even possible due to the limited availability and prohibitive cost of obtaining actual reservoir cores. The objective of this work was to develop a cost-effective method to evaluate injectivity that does not require the use of reservoir core. In this study, a novel coreless injectivity method was developed and validated. The method utilizes field-produced drill cuttings to make synthetic core plugs, which are universally available during well drilling and commonly considered as waste. A specially designed cleaning process was performed for the drill cuttings. They were then wet compressed with a high-pressure hydraulic press and dried in a constant-humidity oven to make core plugs with standard dimensions. Drill cutting plugs prepared in this way can then be used for injectivity tests as an alternative to actual reservoir core plugs. The routine core analysis revealed that, although sedimentary structures were lost, the drill cutting plugs preserved the mineralogy and maintained comparable porosity and permeability to the reservoir plugs. To validate the representativeness of the formation damage tendencies of the drill cutting plugs, water injectivity tests were carried out on both preserved reservoir cores and compressed drill cutting cores, using simulated injection water with successively lower salinities. The results showed that injectivity loss as indicated by increasing pressure drop was consistent with both types of cores. The "coreless injectivity evaluation" technique can be applied for argillaceous reservoirs with formation damage concerns. It is a cost-effective and viable technique for evaluating water injectivity when reservoir cores are unavailable.
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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 | 0.001 | 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".