A Comprehensive Approach to Modeling Sanding During Oil Production
Bibliographic record
Abstract
A Comprehensive Approach to Modeling Sanding During Oil Production Alireza Nouri; Alireza Nouri Dalhousie University Search for other works by this author on: This Site Google Scholar Hans Vaziri; Hans Vaziri Dalhousie University Search for other works by this author on: This Site Google Scholar Hadi Belhaj; Hadi Belhaj Dalhousie University Search for other works by this author on: This Site Google Scholar Rafiqul Islam Rafiqul Islam Dalhousie University Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. Paper Number: SPE-81032-MS https://doi.org/10.2118/81032-MS Published: April 27 2003 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Nouri, Alireza, Vaziri, Hans, Belhaj, Hadi, and Rafiqul Islam. "A Comprehensive Approach to Modeling Sanding During Oil Production." Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, April 2003. doi: https://doi.org/10.2118/81032-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Latin America and Caribbean Petroleum Engineering Conference Search Advanced Search AbstractSand production has been a major dilemma facing operating oil companies over many years, sometimes substantially increasing production costs. On the other hand, a very controlled solid production can enhance oil production. A dependable predictive model is vital for planning production strategies in order to optimize well production. To date, despite several research studies, sand production remains the nightmare of petroleum engineers.Even though many researchers have tried to predict sand production in the past, none of them suggested a comprehensive model that takes care of a variety of mechanisms at different points and different times. Moreover, rare models predict sanding rate and volume along with sanding initiation. This paper presents a comprehensive numerical modeling of sand production that appreciates the different behavior of the medium near and far well-bore from early to late life-time. Sanding criteria were adopted according to the physics of the problem, by taking the sequential nature of sand production into consideration.The numerical model that was used not only assesses sand production qualitatively but can also give the sanding rate at different times. This was used to model the observations of sand production in a large block test, and the sanding rate and volume generated from numerical modeling agreed with experimental results. With each stage of increased drawdown or depletion, a burst of sand took place which enlarged the cavities initiated from the perforations. The expansion of the cavity was soon stabilized and this behavior was predicted by numerical modeling. Moreover, besides considering shear and tensile failure of the material, the possibility of volumetric failure has been discussed.IntroductionSand Production in the petroleum industry is a phenomenon of solid particles being produced together with reservoir fluid. This phenomenon is costing the industry billions of dollars every year. Corrosion of pipelines and other facilities, sand-oil separation costs, possible wellbore choke, environmental effects, reduction of production rate and possible work-overs for clean-up operations are some examples of these costs. On the other hand, a controlled sanding or even sand production invocation has proved to be very effective in increasing production rate, especially in heavy oil recovery, asphalt wells and low PI wells 1,2,3.Sand production takes place if the material around the cavity is disaggregated and then there is enough fluid flow rate to produce the grain particles. Disaggregation of the material initiates from cavity faces and propagates inside the medium. Material disaggregation can take place if the material fails under excessive drawdown or depletion or a combination of them. Depletion and drawdown fail the medium under either of shear or tensile or volumetric failure mechanisms or a combination of them. After failure of the rock disaggregates the material, the resulted grains are produced by the existence of enough pressure gradients in tension. Friction between the grains and capillary tension are the resisting forces against grains movements 4,5.To date, there has been no comprehensive mathematical model that considers all the mechanisms associated with sand production. A model is presented in this paper that takes into account different failure mechanisms that may play a role in sanding. Therefore, in the rest of this paper, first, possible failure mechanisms associated with sanding are explained. For that, a comprehensive model for simulating the behavior of the formation against the applied loads in early and late life, near and far well-bore is presented. The significance of this numerical model is providing a tool for better understanding and modeling of sand production by better prediction of the failure mechanism, sanding rate, and volume. Keywords: drawdown, numerical modeling, mpa, porosity, gradient, cavity face, completion installation and operations, modeling, shear failure, reservoir geomechanics Subjects: Reservoir Characterization, Perforating, Reservoir geomechanics, Completion Installation and Operations, Completion Operations This content is only available via PDF. 2003. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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 | 0.001 |
| 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".