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Record W2029392756 · doi:10.2118/00-10-02

Sand Deposition Inside a Horizontal Well-A Simulation Approach

2000· article· en· W2029392756 on OpenAlexaffabout
Q. Doan, L.T. Doan, S.M. Farouq Ali, Mehmet N. Oguztöreli

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSettlingPetroleum engineeringDeposition (geology)GeologyGeotechnical engineeringWellboreDirectional drillingEnvironmental scienceDrillingEngineeringEnvironmental engineeringSedimentGeomorphology

Abstract

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Abstract Horizontal wells have been shown to be successful in improving oil recovery for marginal heavy oil reservoirs in Saskatchewan and Alberta. One commonly encountered problem in recovery operations for these poorly consolidated reservoirs is the production of sand and fines into the horizontal wellbore, where they settle and accumulate. This paper reports the numerical modeling of gravitational deposition of sand in a horizontal well in such heavy oil reservoirs. The numerical model described in this work examines the transport process mechanistically, based on the conservation equations for the fluid phase (heavy oil) and the solid phase (sand particles). The interaction between these phases is described by empirical correlations. The equations are solved numerically to determine the concentration of sand particles and oil, and their respective pressure and velocity distributions inside the horizontal well. According to the simulation results, oil viscosity and particle size play important roles in the transport process, including controlling the gravitational settling tendency of solid particles inside the horizontal wellbore. The results provide insight into the roles different mechanisms affect the transport of sand particles; as such, they provide guidelines for production operations involving horizontal wells in poorly consolidated and unconsolidated reservoirs. Introduction The use of horizontal wells, in Saskatchewan and Alberta heavy oil reservoirs underlain with bottom-water, has been found to improve primary recovery performance prior to water coning-recovering up to 15%, in some cases, of the initial oil in place, compared with only 5% for a vertical well(1). Horizontal wells have also been successfully used for increasing steamflood recovery(2,3). Due to the unconsolidated or poorly consolidated nature of these reservoirs, solid (sand and fines) production is quite prevalent. The produced solids lead to several production problems, including sand filling up the wellbore, preventing the operation of downhole pumps and surface equipment, etc.(4) In horizontal well cases, sand production potentially poses a serious problem, as the sand could settle and accumulate inside the horizontal wellbore. This settlement and accumulation of sand particles could give rise to reduced cross-sectional areas of the wellbore open to flow. The study reported in this paper examines, using numerical simulation, the gravitational deposition of sand particles inside a horizontal wellbore. A brief survey of the relevant literature is given in the following. Solid-liquid multiphase flows are usually very complex, due to the large number of variables involved in the transport processes, and typically poorly understood interaction between the variables. There have been many experimental investigations of these (and other) flow processes, particularly focused on the deposition of the solid particles. Many of the earliest investigations of solid liquid flows focused on the settling tendency of solid particles. Richardson and Zaki(5) experimentally determined that the falling velocity of a suspension relative to a horizontal plane was equal to the upward velocity of the fluid required to maintain a suspension at the same concentration. For different flow regimes (i.e., Reynolds numbers), separate correlations were developed (from experimental data) for the exponent which corresponds to the slope of log-log plot straight lines between suspension falling velocities and suspension porosities.

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 score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.004
GPT teacher head0.186
Teacher spread0.181 · 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".

Quick stats

Citations7
Published2000
Admission routes2
Has abstractyes

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