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Record W2402499926 · doi:10.2118/180755-ms

Enhanced SAGD Startup Techniques for Improved Thermal Efficiency and Conformance - A Field Test Based Investigation

2016· article· en· W2402499926 on OpenAlexafffundabout
Jarrett Dragani, K. T. Drover

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsCenovus Energy (Canada)
FundersCenovus Energy
KeywordsSteam injectionInjectorPetroleum engineeringProcess (computing)EngineeringTransient (computer programming)Heat transferMechanical engineeringComputer scienceMechanics

Abstract

fetched live from OpenAlex

Abstract The SAGD process can be defined to have three sequential phases to its operating mode, namely: startup, SAGD mode and wind-down. The startup phase most commonly has the shortest operating period, yet it has significant influence on the success of the subsequent operating modes. Historically, there are two primary means to achieve startup of a SAGD well pair and are commonly referred to as circulation and bullheading. The circulation process was employed at the Grand Rapids SAGD Pilot on Well Pair 1 and Well Pair 2 in 2010 and 2012 respectively. The circulation process is complex to optimize from a heat transfer perspective. Parameters such as well length, tubular sizing, steam injection rates, steam injection pressures, steam blanketing, and reservoir dynamics all influence the performance of the process. Transient reservoir simulation models with fully coupled well and reservoir grids are required to effectively model the process, relying on key inputs from field data to calibrate models. Typically, the objectives of circulation are to achieve a uniform heating profile along the entire length of the lateral portion of the SAGD well pair and establish fluid transmissibility between the injector and producer. A study on startup methods was conducted with the intent of optimizing temperature conformance, thermal efficiency and circulation time. The study generated several alternative startup designs, many of which employ insulated tubing strings and varied operating conditions to optimize heat exchange and energy efficiency. A field based trial was conducted using the closed circuit startup design (Canadian patent pending) at the Grand Rapids SAGD Pilot in 2015. Results of the study and field trial suggest that the closed circuit design offers several advantages; it is a thermally efficient, able to operate at higher temperatures, can use less steam per well pair, is scalable up to 1,200 meter long laterals, and can achieve excellent thermal conformance during startup. The findings of this field based investigation add to the knowledge base related to startup techniques and well conformance. The closed circuit technology employed at the Grand Rapids SAGD Pilot is an innovative startup design that may be used in other heavy oil and oil sands reservoirs to enhance startup and promote recovery.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 designObservational
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
Published2016
Admission routes3
Has abstractyes

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