MétaCan
Menu
Back to cohort
Record W2040273064 · doi:10.2118/08-01-07-tn

Prediction of Hydrogen Sulphide Production in SAGD Projects

2008· article· en· W2040273064 on OpenAlexaboutno aff
H.F. Thimm

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2008
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltSulfurHydrogenHydrogen productionHydrogen sulphideChemistryPetroleum engineeringEnvironmental scienceMaterials scienceGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The production of hydrogen sulphide and carbon dioxide is a feature common to all SAGD projects. Both gases are formed by a chemical reaction of steam condensate with bitumen in the SAGD steam zone in Athabasca; they are not normally present as solution gases. The production rates of these gases are therefore strongly dependent on operating characteristics of individual projects, primarily the steam pressure. The potential need for sulphur recovery plants in the larger SAGD project expansions creates the need for first order predictions of H2S production rates, so that appropriate sulphur recovery technologies can be identified. A simple method for the prediction of hydrogen sulphide production has been derived, such that, for most Athabasca projects in the 180 to 240 ºC range of steam zone temperatures, a probable production rate estimate can be read off a simple graph. The graph is built from laboratory data on aquathermolysis, first provided by Hyne, and the assumption of pseudo-zero order kinetics of the aquathermolysis reaction that generates hydrogen sulphide. A temperature dependency is predicted, and is confirmed by field measurements of projects in the 180 to 240 ºC range. Introduction The solvolytic reaction of Athabasca bitumen with steam condensate has been observed since the earliest days of piloting the recovery of this bitumen resource. The first laboratory studies were performed by Hyne et al.(1–3), who coined the now widely-used term "aquathermolysis". More detailed mechanistic studies followed from Hyne's group, and also from the group led by Strausz at the University of Alberta(4). The quantitative aspect of Hyne's work has been largely ignored, possibly because his work was, for the most part, done at 240 ºC steam temperatures, whereas the steam zone temperatures in SAGD pilots and commercial operations have varied from that. Obviously, the steam zone temperature must have an effect on production of the acid gases because the kinetics of generation are temperature dependent. A previously published method of estimating hydrogen sulphide production in SAGD is provided by the method of Thimm(5), which is based on the Henry's Law behaviour of gases in a SAGD steam zone. That method is capable of prediction of produced gas and steam zone gas compositions over time, including situations where the steam zone pressure changes or where gas is injected. However, it involves relatively lengthy computations in solution thermodynamics. For the purpose of identifying potential sulphur recovery technologies, a quicker method of estimating hydrogen sulphide production is required; at least, as an approximate guide. Moreover, it would be useful to express the hydrogen sulphide production on a mass or volume per unit bitumen basis to provide a simple guide for expansion planning. Reaction Order Although neither Hyne nor Strausz have published a reaction order, the following considerations suggest a zero order reaction in the SAGD steam zone. Consider that one might expect a reaction rate equation of the type: (1) rate = k [ sulphur ] [ steam condensate ] where the concentrations may be expressed in terms of various terms suitable for reservoir engineering.

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)0.002
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 score0.989
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.207
Teacher spread0.190 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Canadian Petroleum TechnologySame topicPetroleum Processing and AnalysisFrench-language works237,207