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Record W2746082652 · doi:10.1016/j.egypro.2017.03.1765

CO2 Capture from Sulphur Recovery Unit Tail Gas by Shell Cansolv Technology

2017· article· en· W2746082652 on OpenAlexaff
Farhang Abdollahi, Ian G.C. Craig, Mania Neisiani

Bibliographic record

VenueEnergy Procedia · 2017
Typearticle
Languageen
FieldEnergy
TopicOil, Gas, and Environmental Issues
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsEnhanced oil recoveryFossil fuelWaste managementGreenhouse gasCombustionEnvironmental scienceCarbon capture and storage (timeline)Process engineeringPetroleum engineeringEngineeringClimate changeChemistry

Abstract

fetched live from OpenAlex

A significant driver for the climate change effect is CO2 emission from the sources where fossil fuel is consumed to generate energy. Capturing and sequestration of CO2 from these emission sources is a practical way to mitigate GHG emission impact. However the cost of CCS projects has been a major obstacle to implementing these technologies worldwide. Two main aspects which influence the cost of a CO2 capture project are the CO2 utilization pathway and the CO2 capture technology selection. CO2-Enhanced Oil Recovery (EOR) can be a very good potential pathway to increase the revenue of the CCS project. CO2-EOR also can be an attractive way of using CO2 in areas such as Middle East where the oil and gas reservoirs are mature. However one of the main constraints can be limited access to CO2 especially where no power plant is close to a potential oil reservoir. For technology selection, the choice is typically between Pre- and Post-Combustion. Pre-combustion CO2 capture technologies have been deployed in oil refineries & gas processing plants for decades, but the main source for CO2 emissions in these facilities is often off-gas (also known as acid gas) which is usually sent to the flare system or incinerator. These off-gases are at low pressure, so a compression system is required to pressurize the gas before sending it to the Pre-combustion CO2 capture unit. On the other hand, Post-combustion CO2 capture technology can often require an additional desulfurization step to remove SO2 which can potentially result to higher operational and capital cost as well as waste management and complexity of operation. This paper will discuss the deployment of Shell Cansolv technology to capture CO2 from off-gas downstream of the Sulfur Recovery Unit (SRU) in a single train, potentially as a new CCS application in the oil and gas sectors. The off-gas from Tail Gas Treatment Unit (TGTU) downstream of the SRU will usually contain a higher amount of CO2 compared to coal and gas power plants. The absorption affinity of Shell Cansolv solvent at low pressure off-gas compared to other pre-combustion technologies allows the elimination of the primary compression system located upstream of the CO2 capture unit. Since there is H2S slippage from the TGTU absorber overhead, the amine should be characterized in terms of absorption affinity and stability in the reduced environment. The impact of H2S on amine performance in terms of degradation has been investigated in comparison to a post-combustion application where H2S is incinerated and converted to SOx. SOx contaminates amine to form Heat Stable Salt (HSS), so it needs to be removed prior to the post-combustion CO2 capture unit in a separate FGD unit (Flue Gas Desulfurization). Shell Cansolv DC amine in pre-combustion lineup absorbs both H2S and CO2 in a single absorber so incinerator and FGD unit is not required compared to post-combustion applications. Shell Cansolv DC amine has been tested to remove up to 99% CO2 which is higher than the 90% typical capture rate for most post-combustion applications. The other advantage of this application is the ability to operate at high temperature (∼60 C). This is often a key design parameter especially in the Middle East where most applications are considered hot climate applications. All design parameters of the CO2 capture unit such as liquid per gas ratio (L/G), stripping factor at the regenerator side and absorber packing height have been evaluated and optimized to reduce both capital and operational costs of the project. Eventually, in a case study, an economic comparison was conducted and the result indicated potentially more than 40% reduction in the cost of a CO2 capture unit as well as same magnitude increase in Net Present Value (NPV) compared to pre-combustion technology.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.004

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 head0.008
GPT teacher head0.204
Teacher spread0.195 · 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 designBench or experimental
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

Citations6
Published2017
Admission routes1
Has abstractyes

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