Numerical Investigation of Sand Production Under Realistic Reservoir/Well Flow Conditions
Bibliographic record
Abstract
Abstract A new numerical model has been developed for investigation of sand production under realistic reservoir/well flow conditions. The model allows prediction of critical drawdown leading to the onset of sanding as well as the rate of sand production in real time. The model predictions have been validated by using laboratory data. The proposed numerical model has been embedded into ABAQUS, which is a finite element program capable of simulating interaction between fluid flow and mechanical deformation of the medium. The model has been designed to encompass a number of the factors that are influential in the process of sanding. This includes a time-dependent coupled fluid flow and deformation analysis of the rock, material disaggregation, sand removal, and operational conditions including drawdown, depletion, and water-cut. The model has been validated by using the experimental data on hollow cylinder specimens involving real time sand production measurements under various conditions. The results of the numerical modeling study show a good agreement with experimental data in terms of the operational conditions leading to the onset of sanding as well as an estimation of the sanding rate. The model presents a live picture of the ongoing alterations in the material at the wellface during the production which provides a deeper insight into the role of the various parameters involved. Introduction Several sand production prediction methods have been proposed using geomechanical models. These methods could be grouped into analytical (e.g., Risnes et al. 1982, Morita et al. 1989a, Weingarten & Perkins 1992, van den Hoek et al. 2003) and numerical models (e.g., Morita et al, 1987a, Stavropoulou et al. 1998, Papamichos & Malmanger 1999, Vaziri et al. 2002, Nouri et al. 2006). The analytical models provide formulations for the flow rate required to induce tensile failure. Tensile failure of the material due to seepage drag forces is taken as criterion for sand production. Their limitation is the general constraints with respect to geometry, boundary conditions, and implementation of intricate material behavior. Further, they fall short in providing an indication of the severity of sanding once it is triggered. Numerical models could overcome many of the limitations mentioned above. Some of these models work by modeling rock disaggregation at cavity face in post-peak strength phase of the rock (e.g. Nouri et al. 2006). Others tie sand production to the mobilized plastic strain level (e.g. Morita & Fuh 1998). Sand production in these models occurs once equivalent plastic strain exceeds a threshold. Some numerical models assume sand production to be in the form of sand erosion which is tied to mechanical damage of rock around a wellbore (e.g. Geilikman et al. 1997, Vardoulakis et al. 1996, Stavropoulou et al. 1998). A critical review of various sand production models was provided in Nouri et al. (2006). This paper presented a finite difference model which used continuum mechanics approach for modeling the process of sanding as a function of several parameters that have an effect on sand production. These include: operation conditions, i.e., drawdown and depletion, completion technique, formation strength and mechanical behavior, permeability, and a moving boundary due to solid material flow, i.e., sand production.
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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".