MétaCan
Menu
Back to cohort
Record W2587072046 · doi:10.2118/184998-ms

Numerical Prediction of H2S Production in SAGD: Compositional Thermal-Reactive Reservoir Simulations

2017· article· en· W2587072046 on OpenAlex
Simon Ayache, Christophe Preux, Nizar Younes, Pauline Michel, Violaine Lamoureux-Var

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 Canada Heavy Oil Technical Conference · 2017
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringAsphaltHydrogen sulfideSteam-assisted gravity drainageSteam injectionThermalReservoir simulationPyrolysisEnvironmental scienceSulfurEnhanced oil recoveryOil sandsChemistryGeologyMaterials scienceThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Nowadays EOR methods such as thermal techniques are widely used to recover the viscous hydrocarbons from heavy oils and bitumen reservoirs. One of the thermal methods is the Steam-Assisted Gravity Drainage (also called SAGD), which consists in injecting steam into the reservoir to melt the viscous oil and allow its mobility. The melted oil falls by gravity to the production well. The injected hot steam, once it reaches the heavy oils/bitumen, induces chemical reactions called aquathermolysis. These reactions generate gases such as hydrogen sulfide (H2S) or carbon dioxide (CO2). The H2S is known to be highly toxic and corrosive. Hence it needs to be given a particular attention when it is produced at the surface. Reservoir models have been built to simulate thermal effects during a SAGD process but only few publications in the literature deal with the aquathermolysis reactions occurring in reservoirs where steam is injected. This paper focuses on building a reservoir simulation model to forecast the H2S production. The example of the Hangingstone heavy oil field in Canada has been chosen. This simulation model is based on a compositional PVT description for heavy oil/bitumen and on a recently developed sulfur-based compositional kinetic model to describe the aquathermolysis reactions. The description of the heaviest components found in heavy oils/bitumen is made through a SARA decomposition. The reactive model that describes the aquathermolysis reactions is firstly presented. Then a section of this paper is dedicated to the building of a PVT model for heavy oil. Another chapter presents the 2D heterogeneous reservoir models used for the simulations. Finally the simulations results are presented. A sensitivity analysis has been performed to investigate the effect of the rock conductivity and the pressure/temperature of the injected steam on the H2S production. The different simulations have given consistent results with production data in terms of H2S production at surface. This shows that both the fluid description and the aquathermolysis kinetic model used in the study are relevant for the prediction of H2S production in the context of steam injection.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.840

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 head0.028
GPT teacher head0.273
Teacher spread0.244 · 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