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Record W1994147348 · doi:10.2118/00-09-04

CO in Alberta-A Vision of the Future

2000· article· en· W1994147348 on OpenAlexaboutno aff
Kevin J. Edwards

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEnhanced oil recoveryCarbon dioxideFossil fuelScale (ratio)Environmental scienceCarbon dioxide in Earth's atmosphereCapital costPetroleum industryNatural resource economicsBusinessWaste managementPetroleum engineeringEnvironmental engineeringEngineeringGeographyChemistryEconomics

Abstract

fetched live from OpenAlex

Abstract An exciting new future of large-scale carbon dioxide enhanced oil recovery awaits Alberta's depleted oil fields. This paper presents the potential and how the necessary infrastructure could be developed. Such an infrastructure currently exists in the Permian Basin of West Texas and Southeast New Mexico, where over 28.17 106m3/day of carbon dioxide is injected for enhanced oil recovery. A number of factors have come, or are coming, together to form the environment where a comparable infrastructure may be possible in Alberta. A scoping evaluation of carbon dioxide sources and locations, reservoir locations, potential oil recovery, and capital costs to develop the infrastructure is carried out. The factors leading to a large-scale carbon dioxide industry are compared to the factors in place during the 1970s and 1980s, when most of the hydrocarbon miscible floods were initiated in Alberta. Finally, conclusions are drawn regarding the viability of the infrastructure proposed in this paper. Introduction Carbon dioxide (CO2), a simple molecule composed of one carbon and two oxygen atoms, has been the subject of interest by the oil industry for over 25 years. Original interest was in its potential for enhanced oil recovery (EOR). More recently, that interest has been eclipsed by its perceived role in global climate change, and the potentially negative business and economic implications of emitting CO2 into the atmosphere. A win-win situation could develop by constructing a province-wide infrastructure for CO2 collection and transmission that will address both interests: increased light oil recovery through EOR, and reduced CO2 emissions. Factors leading in this direction include:Declining reserves of light-medium oil. Alberta has enjoyed a long history of light oil production. However, new discoveries are not replacing production and reserves are declining, as illustrated in Figure 1. Current reserves are now approximately one third of proved reserves in 1977.FIGURE 1: Historical light-medium oil reserves for the province of Alberta. (Available in full paper)Environmental issues related to CO2 emissions into the atmosphere. There is an increasing concern by the public and government about controlling CO2 emissions to the atmosphere. The government of Canada showed its concern on the subject by signing the Kyoto Accord, which, if ratified, will commit Canada to reducing greenhouse gas (GHG) emissions to 94% of 1990 levels by 2012.Buoyant natural gas markets. Use of natural gas in hydrocarbon miscible floods (HCMF) was feasible in the past due to lack of markets and low prices. Current markets and prices most likely preclude its use in miscible flooding.Application of a Proven Technology. CO2 flooding has been used commercially since 1972 in the Permian Basin of Texas and New Mexico, when injection began into the SACROC and North Cross projects(1). By early 1998 there were over 40 CO2 projects operating in the Permian Basin, with total CO2 injection of 28.17 106m3/d and incremental production of 23,850 m3/day. Factors that led to the success of CO2 in the Permian Basin include:Well developed CO2 infrastructureHigh quality, high productivity CO2 sources

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.164
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0100.003
Open science0.0020.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0190.002

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 head0.002
GPT teacher head0.174
Teacher spread0.173 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations7
Published2000
Admission routes1
Has abstractyes

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