Stimulation of Unconsolidated Reservoirs: Sensitivity Analysis of Petrophysics Using Experimental and Numerical Methods
Bibliographic record
Abstract
Throughout the lifespan of oil fields, stimulation techniques play a crucial role in altering the petrophysical properties of the reservoir sections, hence impacting their productivity. Several studies have highlighted the significance of incorporating geomechanical effects in reservoir simulations, yet conventional simulators still fail to adequately account for this aspect. The majority of recent methods that connect fluid flow and rock mechanics focus on updating the porosity and absolute permeability while overlooking alterations in relative permeability, leading to a limited comprehension of the reservoir performance during production or stimulation phases. This study attempted to present an extensive method ranging from experimental to mathematical and ultimately numerical work that allowed for a better understanding of the geomechanics function in the behavior of an unconsolidated sandstone reservoir. Initially, a series of consolidated drained triaxial compression tests were conducted following different stress paths. Absolute and relative permeability measurements were systematically performed at several levels of volumetric strain. The experiment results showed high sensitivity, with an increase of 80% in absolute permeability and a 30% change in oil relative permeability have been reported. A robust empirical correlation relating absolute and relative permeabilities to volumetric strains was then established prior to being implemented into the reservoir simulator through a code developed internally. The results obtained during the current study have clearly demonstrated that the precision of production forecasts has significantly improved by employing coupled models that consider changes in relative permeability in concurrence with permeability and porosity. Correlations and codes developed throughout this research work can provide the decision-makers with a strong tool to acquire a better understanding of the interaction between the mechanics and fluid movement within the reservoir. Hence, a better management plan can accordingly be recommended and ultimately adopted to improve field productivity.
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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 | 0.001 | 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 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".