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Record W2017515764 · doi:10.2118/2008-175

Synergies and Environmental Benefits of Lignite Gasification in Ptolemais with Combined CO2 Sequestration and Enhanced Oil Recovery in the Prinos Oil Fields in Macedonia-Greece

2008· article· en· W2017515764 on OpenAlexaboutno aff
J. Tingas, S. Logothetis, A.A. Tingas

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
FundersNational Technical University of Athens
KeywordsCarbon sequestrationEnvironmental scienceEnhanced oil recoveryWaste managementFossil fuelPetroleum engineeringGeologyEngineeringCarbon dioxideChemistry

Abstract

fetched live from OpenAlex

Abstract Lignite is Greece's main fossil fuel source and accounts about 30 % of primary energy consumption. The Ptolemais lignite fired power complex in Western Macedonia-Greece uses lignite and it is the main Greek power generation complex. The lignite thermoelectric power generation units in Ptolemais are among the most polluting in the European Union in terms of relative emissions per produced KWh, releasing significant quantities of green-house effect gases, CO2, CH4, and toxic ash and dust. However, the worst coal fired power stations in absolute emissions causing severe environmental problems are in Central and North Europe. All the coal fired power stations in Europe need upgrading of their technology. Hence, the Canadian industry has an ideal opportunity to export field tested Canadian carbon capture technology. Prinos sour oil fields in Eastern Macedonia-Greece are mature oil fields with declining oil production approaching the field economic limit. Water-flooding has been implemented to the Prinos oil field from the production start-up. High residual oil saturation indicates significant EOR potential by injection of gases, such as CO2 and H2S, which may exceed 100 MM Bbls of recoverable oil. Synergies of an initial coal bed methane production followed by lignite gasification or oxy-combustion and CO2 sequestration in the Prinos fields combined with enhanced oil recovery (EOR) can be examined. The proposed carbon capture and sequestration technology is an improved one but similar to the Weybourne EOR and CO2 sequestration project in Canada/US, which is combined with lignite gasification in North Dakota, USA and it is valuable technological experience for European projects. The Carbon capture technology for the Ptolemais-Prinos lignite gasification and EOR/CO2 sequestration will solve the severe environmental problems by eliminating the lignite ash and dust and the released of green-house gases in the atmosphere in Ptolemais, while significant incremental Prinos petroleum production will be recovered. The implementation of the proposed technology will allow CO2 sequestration from future coal fired power plants in Eastern Macedonia-Greece using indigenous coal. Additional environmental benefits of the Ptolemais-Prinos project may include CO2 sequestration of the CO2 emissions from the industrial area of Thessaloniki in central Macedonia-Greece. The compliance to Kyoto protocol obligations by Greece and other European Union countries is unachievable without the implementation of the carbon capture technology in power stations. The approved plans to build new hard coal power plans without carbon capture is a step to the wrong direction, which instead of reducing will increase at an increased rate the emission of green-house gases at national level. Geothermal power plants can provide the required expansion in power generation capacity and replace partially existing coal fired power stations. Geothermal energy is a renewable energy with zero carbon foot-print. The Greek geothermal power generation may exceed 4 GW and the relevant reduction in CO2 emissions to the atmosphere may exceed 30 metric tonnes CO2 per annum by replacing coal fired power plants. Introduction CO2 sequestration in countries with small number of depleted oil and gas reservoirs such as Greece may seem difficult. However, even in this case there are viable options.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.953

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 head0.009
GPT teacher head0.177
Teacher spread0.168 · 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 designObservational
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

Citations2
Published2008
Admission routes1
Has abstractyes

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