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Record W2284849214 · doi:10.2523/iptc-11490-ms

Development of highly contaminated gas & oil fields, breakthrough CO2/H2S Separation Technologies

2007· article· en· W2284849214 on OpenAlexaboutno aff
Theo Klaver

Bibliographic record

VenueInternational Petroleum Technology Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbu dhabiCrude oilMiddle EastEmerging technologiesFossil fuelNatural gasContaminationNatural gas fieldResource (disambiguation)Environmental sciencePetroleumInvestment (military)Petroleum engineeringComputer scienceNatural resource economicsEngineeringGeologyWaste managementGeographyEconomics

Abstract

fetched live from OpenAlex

Abstract Description Shell Global Solutions International B.V ("Shell") has been involved for many years in the development of new technologies to separate CO2 and H2S from highly contaminated natural gas streams. This program has been significantly accelerated in recent years and major milestones have been achieved. The program focuses on technology solutions that are critical to develop (stranded) contaminated hydrocarbon gas and oil fields. Several key technical challenges in the development of highly contaminated gas & oil fields have been overcome with new technologies developed by Shell. These challenges include: contaminant separation at minimal energy consumption and losses at minimum capital investment. This paper will present these challenges and introduce new technologies that can help to reduce project development cost by as much as 40% compared to conventional technologies Application External studies (Steiner, 2005) estimate a global (recoverable) resource of some 500 B boe (= 3000 tcf), as per bar chart figure 3 below, of gas that is 'contaminated' by the previously defined levels H2S and/or CO2. These resources will require specific technologies to develop these fields economically. The bulk of these resources are in the Middle East, Canada, CIS, Asia and Australia. In general, one could say that the predominantly H2S contaminated fields can be found in the northern Americas (Canada), the Middle East (Abu Dhabi, Kuwait, Oman, Saudi Arabia, Qatar), and the Caspian regions (Kazakhstan, Russia). The indicated size exclude resources that could be accessed via H2S / CO2 Enhanced Oil Recovery (EOR). The application of the newly developed technologies will be in the area of contaminated gas fields. With new technologies highly, contaminated gas fields can be economically developed to remove the contaminants from the hydrocarbon gas and re-injection of the contaminants. Since conventional technologies become less economic at increasing percentages of contaminant, the new technologies are specifically targeted at high concentrations of contaminants (>30%). The new technologies aim for efficiencies above 85 %, where efficiency is expressed as a percentage of hydrocarbon sales gas divided by the hydrocarbon feed stream. (Losses are due to fuel gas and hydrocarbons left in the contaminant stream)

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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 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

Citations1
Published2007
Admission routes1
Has abstractyes

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