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Record W2136580303 · doi:10.7939/r3jh3d86k

Development and Applications of a Semi-analytical Approximate Thermal Simulator

2014· article· en· W2136580303 on OpenAlexaboutno aff
Vahid Dehdari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsSteam-assisted gravity drainageRanking (information retrieval)Petroleum engineeringTask (project management)Steam injectionReservoir simulationProduction (economics)Flow (mathematics)AsphaltRank (graph theory)Oil sandsComputer scienceSimulationEngineeringMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Oil sand reservoirs play an important role in the economy of Canada due to their significant recoverable reserves. Due to the high viscosity of the oil in these reservoirs, conventional methods cannot be used for production. The steam-assisted gravity drainage (SAGD) method is an efficient way of producing oil from these reservoirs. Predicting oil production and steam injection rates is required for planning and managing a SAGD operation. This can be done by simulating the fluid flow with flow simulation codes, but this is very time consuming. The run time for a 3D heterogeneous model with one well pair can exceed 2 days. Another important task in SAGD operation is the optimization of the trajectory of the wells; the production forecasts for different well positions would require running the flow simulator multiple times, but that is too expensive. Yet another task is to quantify the uncertainty in steam requirements and bitumen production due to multiple realizations of the geological properties. Another task is to rank the multiple realizations from poor performing to good performing. This ranking could be used to help select a subset of realizations for more careful analysis. Finally, forecasting the location of the steam chamber at different time steps is a very important task for considering geomechanical effects. For these reasons, an approximate model that reasonably predicts oil production and steam injection rates with low computational effort would be valuable. In this dissertation, a reliable SAGD approximate simulator for predicting SAGD performance with 3D heterogeneous models of geologic properties is developed. This approximate simulator can handle different types of operating strategies. The approach is an approximate solution using a semi analytical model based on relevant theories including Butler's SAGD theory. The proxy is much faster than the full simulator and it gives accurate estimated oil production and steam injection rates at different time steps. Theoretical and numerical research has been undertaken to develop the proxy, implement it in fast code, demonstrate the accuracy of prediction and apply to realistic examples.

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 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: Empirical · Consensus signal: none
Teacher disagreement score0.619
Threshold uncertainty score0.242

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 head0.015
GPT teacher head0.261
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations3
Published2014
Admission routes1
Has abstractyes

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