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Record W4214679894 · doi:10.2523/64747-ms

Sand Production Simulation in Heavy Oil Reservoirs

2000· article· en· W4214679894 on OpenAlexaff
Zhang Liangwen, Maurice B. Dusseault

Bibliographic record

VenueProceedings of International Oil and Gas Conference and Exhibition in China · 2000
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsExhibitionChinaCitationBeijingZhàngProduction (economics)Discrete element methodComputer scienceLibrary scienceOperations researchEngineeringMining engineeringArchaeologyGeographyPhysics

Abstract

fetched live from OpenAlex

Sand Production Simulation in Heavy Oil Reservoirs Liangwen Zhang; Liangwen Zhang University of Waterloo Search for other works by this author on: This Site Google Scholar Maurice B. Dusseault Maurice B. Dusseault University of Waterloo Search for other works by this author on: This Site Google Scholar Paper presented at the International Oil and Gas Conference and Exhibition in China, Beijing, China, November 2000. Paper Number: SPE-64747-MS https://doi.org/10.2118/64747-MS Published: November 07 2000 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Zhang, Liangwen, and Maurice B. Dusseault. "Sand Production Simulation in Heavy Oil Reservoirs." Paper presented at the International Oil and Gas Conference and Exhibition in China, Beijing, China, November 2000. doi: https://doi.org/10.2118/64747-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Oil and Gas Conference and Exhibition in China Search Advanced Search AbstractA new sand production model is developed based on inter-particle contact force variations at the discrete micromechanical level. Two mechanisms for sand production can be expected in the field, dynamic detachment and equilibrium yield. The model discussed in the paper describes the sand production mechanism in the dynamic detachment process. Within the new model formulation, sand is considered to be produced because of either a large porosity gradient or a large pressure gradient. The 1-D steady-state solution of the new model is also presented; it may be used for simple sensitivity analysis for parameters such as the field stress and pressure depletion effect.IntroductionProduction of sand during oil production is simultaneously a major concern1 and benefit2,3 for both conventional and heavy oil production operations. It is now well known that sand influx enhances production, yet it can cause problems such as increasing difficulty in well work-overs, well clean-up, and additional costs for waste sand disposal. A sudden influx of a large amount of sand toward the well can even destroy progressing cavity pumps or plug tubing.Sand production problems can be experienced in various ways. Transient sand production, where the sand production rate rapidly declines with time, is frequently experienced during the clean-up period after processes such as perforating or acidizing, after rapid bean-up of production, or after water breakthrough due to removal of weakened or produced sand.Sand production has been classified on the basis of distinct reservoir evolution stages:4,5,6,7Early transient sand production period when little perforation-induced damage has been removed and the cavities have a zone of reduced permeability around them;Stable production period with enlarged cavities, when the damaged zone has been removed;After water cut increase, considered to be capillary force and flow rate-induced sand production; andUnstable sand production period due to reservoir pressure depletion, considered to be effective stress change induced sanding.In the latter, strain reduces the strength of the sand through cohesion destruction, and it may also be subjected to a lower effective confining stress near the wellbore because of stress redistribution.In the transient sand production period, failed sand removal from cavities is a process limited by the volume of the damaged rock. In such situations, leftover failed sand may also act as a support to the intact sand skeleton in the vicinity of the cavity. However, if this sand is removed for some reason, the stable cavity structure may be destabilized; this can lead to a single sand burst and restabilization, to episodic sand bursts, or even to continous sand production.There are many factors affecting sand production rate, they may be classified as the driving factors, the resisting factors and the well completion factors. Driving factors are those acting to increase sand detachment potential from the solid reservoir skeleton. They include stress magnitude and stress deviator (s1-s3), pressure gradient (or flow rate or velocity) and capillary forces associated multiphase flow and wetness.Resisting factors include those that act against sand detachment, such as material strength, inter-particle friction (function of effective stress), structural (geometrical) arching and opposing pressure gradients, should they locally arise.The well completion factors affect sand production by modifying fabric, production rate, stress equilibrium, and production history. They include perforation size, intervals, spacings, depth of penetration, size of damaged zone, and perforation orientation. Furthermore, production practices such as well shut-in and bean-up methods are relevant, as they impose sudden gradients and cross-flow among perforation groups. Keywords: upstream oil & gas, sand production, bitumen, rev, drillstem/well testing, mechanism, drillstem testing, equilibrium, porosity gradient, particle Subjects: Reservoir Characterization, Formation Evaluation & Management, Unconventional and Complex Reservoirs, Perforating, Drillstem/well testing, Oil sand, oil shale, bitumen, Completion Installation and Operations, Completion Operations This content is only available via PDF. 2000. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.231
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations1
Published2000
Admission routes1
Has abstractyes

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