Multidimensional Velocity-Based Model of Formation Permeability Damage: Validation, Damage Characterization, and Field Application
Bibliographic record
Abstract
The loss of injectivity in produced water and seawater injectors due to formation plugging is well documented in the literature. Reliable modeling of the permeability loss is the key to the analysis of field data and to design and economics of projects.Standard formulation of damage mechanics is based on the classical deep bed filtration (concentration-based) model, which requires two parameters: filtration coefficient λ and formation damage coefficient β. Determinationof these paramteters is expensive and difficult. Moreover, the model is not easily implemented in reservoir simulators.This paper presents an alternative approach to modeling damage based on the formulation proposed by Bachman et al. (SPE 79695). The numerical implementation and validation of this empirical, velocity-based model is extended to two dimensions. The model was extended to 2-D flow and validated by a comparison with the deep bed filtration model. The velocity model gives remarkably accurate approximation to the more complex concentration model. Unique relation between the parameters of the two models was found, and used to develop a new methodology to characterize damage by matching lab or field data.Application of the model to the published data from offshore Gulf of Mexico is presented. The velocity method allows more accurate history matching and the damage characterization by history matching yields parameters close to those measured.
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.
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 | 0.001 |
| 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".