Modelling Sand Production Within a Continuum Mechanics Framework
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Bibliographic record
Abstract
Abstract The paper presents a continuum mechanics framework in which sand production can be modelled on the basis of an erosional mechanism. A representative elementary volume comprised of three constituents namely solid, fluid, and fluidized solids is chosen upon which mass balance and particle transport equations are written. The erosional process is described by a particle generationconstitutive law. The coupled non-linear governing equations are finally solved using the finite element technique with a Netwon-Raphson scheme. In order to illustrate the capabilities of the model, the evolution of controlling field variables such as porosity, fluidized sand concentration and pressure distributions are computed for a wellbore subjected to a pressure gradient corresponding to fluid draw down during pumping. In the case of anisotropic permeability conditions, sand production is at its peak value at different points around the wellbore and there is a time lag between the times at which each point reaches its peak. This is due to the averaged fluid and fluidized sand fluxes being non radial. Introduction Sand production from unconsolidated formations occurs when the well fluid being produced under high pumping rate dislodges a portion of the formation solids leading to a continuous flux of formation solids. In Alberta, the formation from which fluid (hydrocarbon) is being produced is oil sand, while the solids coming out with the fluid is sand, though solids can be produced from a variety of other formation types such as sandstones. Sand in the well fluid can erode casing, pipes and pumps or plug the well if sufficient quantities are produced. The distinct periods of sand production in the well and reservoir life as pressure is being depleted were discussed by Morita et. al. (1987)[1]. There are a number of schemes to address sand production. Exclusion schemes involve the installation of gravel packs or screen filters in order to catch the sand as it enters the well. However, by doing so, the flow rate of heavy oil in the well can drastically fall from 7–15 m3/day to may be 0.5-5 m3/day. On the other hand, avoidance schemes include pressure and fluid rate control, selective perforations, and resin injection to coat sand. As operators are following more aggressive production schedules, this has led to a demand for understanding the phenomenon of sand production mechanisms so that correct predictions of the anticipated amount of produced sand as a function of time, applied stress, and fluid flow rates can be made. The challenge is to develop a mathematical tool with a predictive capability that will allow oil operators to devise pumping schemes that produce hydrocarbons at a flow-rate just below one that will produce sand. The physics of sand production is not clearly understood although that oil rate enhancement is often linked to solution gas effects, sand movement and growth of large high-permeability regions or cavities known as wormholes[2]. It is believed that wormhole formation is driven by fluid flux as it exerts a drag force strong enough on the oil sand matrix to overcome frictional forces that hold the grains together.
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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) | 0.001 | 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