Comprehensive Transient Modeling of Sand Production in Horizontal Wellbores
Bibliographic record
Abstract
Summary Installing sand control in long horizontal wells is difficult and particularly challenging in offshore fields. It is, therefore, imperative to make decisions with regard to the most optimum completion type objectively and based on reliable assessment of the sanding potential and its severity over the life of the well for the intended production target. This paper introduces a predictive tool that forecasts not only the initiation of sanding, but also its rate and severity in real time. A series of well-documented experiments on a large-size horizontal wellbore was simulated using a finite difference numerical model. The model accounts for the interaction between fluid flow and mechanical deformation of the medium, capturing various mechanisms of failure. The model allows capturing the episodic nature of sanding and the resulting changes in the geometry and formation consistency and behavior within the sand impacted regions. Sand detachment is simulated by removal of the elements that are deemed to have satisfied the criteria for sanding based on considerations of physics, material behaviour and laws of mechanics. The proposed numerical model is designed to account for many of the factors and mechanisms that are known to influence sanding in the field and as such can be used as a practical tool for predicting the frequency and severity of sand bursts and changes in operating conditions that can be considered for mitigating or managing such problems. The model shows reasonable agreement with the experimental results in terms of borehole deformation and sanding rates. The model correctly predicted initiation of shear failure from the sides of the borehole and its propagation to the boundaries of the sample. It was further seen that the propagation of the shear failed zone resulting from sand production agreed well with the numerical pattern of failure growth upon removal of elements satisfying the sanding criteria. The approach and concepts used are considered suitable for application to field problems involving horizontal wells.
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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".