MétaCan
Menu
Back to cohort
Record W2344993549 · doi:10.2118/180459-ms

Design, Optimization and Operation of SAGD Wells Using Dynamic Flow Simulations

2016· article· en· W2344993549 on OpenAlex
Carlos Nascimento

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSPE Western Regional Meeting · 2016
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringInjectorSteam-assisted gravity drainageMultiphase flowSteam injectionInjection wellReservoir simulationCasingEnvironmental scienceDynamic simulationFlow (mathematics)EngineeringAsphaltSubmarine pipelinePetroleumOil sandsGeologyMechanical engineeringGeotechnical engineeringSimulationMechanicsMaterials science

Abstract

fetched live from OpenAlex

Abstract Canada has the third largest oil reserves in the world and attracts a global attention because the majority of the reserves are bitumen and heavy oil production in western Canada. Steam assisted gravity drainage (SAGD) has been the established method to produce the bitumen and heavy oil. As the number of applications of SAGD continues to increase in Canada, there is an ongoing evolution and implementation of new technologies including those related to new improvements in design, optimization and operation. One of these new approaches involves the application of a dynamic multiphase flow simulator. Dynamic multiphase flow simulation has been widely used around the world for conventional oil and gas production since the 1990s for primarily offshore applications related to flow assurance issues. It has been used since 2012 for simulating SAGD wells, mainly in Canada. Dynamic simulation has been used to design SAGD wells, look at normal production and to identify and mitigate problems for both injector and producer wells in pre-circulation phase (also called pre-heating phase, or early-period). For the pre-circulation phase when steam is circulated in both wells (injector and producer), dynamic flow simulation shows how the wellbore (casing, cement and formation) is heated from the beginning of steam injection. As well, this simulation makes possible to verify the displacement of water in liquid phase by the steam as a function of time, identifying places where it is cumulated together with its impact on the temperature profile (inside and outside of well). In addition, for shut-in events, transient analysis combined with field data can help to estimate the thermal properties of formation (e.g. thermal conductivity) and steam leakage to the reservoir. For normal production operation, dynamic flow simulation can be used to evaluate the efficiency of steam injection to the formation by considering different steam splitters configurations and to determine the required injection pressure at wellhead. As well, for a producer pad (with all wells having electric submersible pumps installed), simulation shows how some operational parameters (such as flow rate, pressure and temperature at wellheads and separator) are influenced during different shut-in and start-up operations. In summary, this paper shows the value of dynamic flow simulations in improving SAGD subsurface systems and operations.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.413
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

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

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 head0.036
GPT teacher head0.281
Teacher spread0.245 · 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