Effects of Memory on the Complex Rock-Fluid Properties of a Reservoir Stress-Strain Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The memory based stress-strain model developed earlier by Hossain et al. (2007) Hossain, M. E., Mousavizadegan, S. H., Ketata, C. and Islam, M. R. 2007. A novel memory based stress-strain model for reservoir characterization. Journal of Nature Science and Sustainable Technology, 1: 653–678. [Google Scholar] has been solved numerically in this study. The derived mathematical model introduces the effects of temperature, surface tension, and pressure variations and the influence of fluid memory on the stress-strain relationship. The variation of shear stress as a function of strain rate is obtained for fluid in a sample oil reservoir to identify the effects of fluid memory. The stress-strain formulation related with the memory is taken into account, and we obtain the variation of it with time and distance for different values of α. The dependency of the stress-strain relation on fluid memory is considered to identify its influence on time. As pressure is also a function of space, the memory effects on stress and strain are shown in space with the pressure gradient change. The computation indicates that the effect of memory causes nonlinearity, leading to chaotic behavior of the stress-strain relationship. This model can be used in reservoir simulation and rheological study, well test analysis, and surfactant and foam selection for enhanced oil recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it