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Record W4239993723 · doi:10.2523/94986-ms

Recent In-Situ Oil Recovery-Technologies for Heavy- and Extraheavy-Oil Reserves

2005· article· en· W4239993723 on OpenAlexaffabout
Luciane Cunha, J.C. Cunha

Bibliographic record

VenueProceedings of SPE Latin American and Caribbean Petroleum Engineering Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCitationPetroleumLatin AmericansLibrary scienceComputer scienceEnvironmental scienceGeologyPolitical science

Abstract

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Recent In-Situ Oil Recovery-Technologies for Heavy- and Extraheavy-Oil Reserves Luciane Bonet Cunha; Luciane Bonet Cunha U. of Alberta Search for other works by this author on: This Site Google Scholar Jose C.S. Cunha Jose C.S. Cunha U. of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Rio de Janeiro, Brazil, June 2005. Paper Number: SPE-94986-MS https://doi.org/10.2118/94986-MS Published: June 20 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Cunha, Luciane Bonet, and Jose C.S. Cunha. "Recent In-Situ Oil Recovery-Technologies for Heavy- and Extraheavy-Oil Reserves." Paper presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Rio de Janeiro, Brazil, June 2005. doi: https://doi.org/10.2118/94986-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Latin America and Caribbean Petroleum Engineering Conference Search Advanced Search ProposalThe heavy and extra heavy oils in Canada represent an amount of recovery oil resources of about 300 billion barrels. These vast quantities of heavy and extra heavy oil are trapped in shallow, accessible reservoirs, but are difficult to extract. Producers involved in heavy oil recovery face special challenges in producing these high-viscosity crudes.Conventional heavy oil recovery methods have showed to provide limited oil displacement efficiencies in Canada's heavy and extra heavy oil deposits. To overcome their inherent difficulties several variations of steam, air and solvent injection methods have been proposed. The most interesting ones appeared along with developments in horizontal well technology. These methods combine the concept of oil gravity drainage with the conventional air-steam and solvent-based heavy oil recovery processes and the horizontal well technology. Methods known as cyclic steam stimulation - CSS, steam-assisted gravity drainage - SAGD, solvent vapor extraction - VAPEX, and top-dow combustion, are examples of this class of methods.This article presents an overview of the recent production technologies for extra heavy oil reserves. Some of the properties of heavy oil are summarized and a review of the drilling/completion and production techniques that help to make heavy-oil reservoirs profitable assets is presented. Both, limitations and potential benefits of these techniques are described.IntroductionAlberta's Oil Sands contain the largest crude bitumen resource in the world, approximately 1,628 billion barrels of initial in-place and 174 billion barrels of remaining established reserves. Over 80% of these reserves can be produced only by using in-situ recovery methods and research to find more effective in-situ recovery methods is incetivated.Majority of oil sands in Canada are deposited in Alberta, in three areas called Athabasca, Cold Lake, and Peace River. In-situ steam-based recovery methods have been required to produce bitumen more effectively and economically, each adapted to the specific geologic conditions of the reservoirs.This work includes a literature review on the recent in-situ oil recovery-technologies for heavy and extraheavy-oil reserves. Oil sands development and production statistics data for the three main oil sands areas will be covered. Also, the typical in-situ recovery methods, drilling/completion and production techniques which are applied in Canadian oil sands areas will be reviewed.Alberta Oil Sands Geology, Reserves and ProductionThe Alberta oil sands geology has been described in several reports(1),(2). The Alberta oil sands deposits are mostly contained in the Lower Cretaceous sands and are located in three geographic areas: Athabasca, Cold Lake, and Peace River(3) (Figure 1). Table 1 shows geological features in Canadian oil sands areas(2).Canada has 179 billion barrels of proved reserves, the second largest proved reserves in the world, as of the end of 2003 (Table 2)(4). Alberta oil sands has 1.6 trillion barrels of initial volume in-place of crude bitumen and reserves of about 174 billion barrels. It is estimated that eighty-one percent of the 174 billion barrels of remaining established reserves can be recovered by applying in-situ recovery methods (Table 3)(5). Oil sands production in Alberta is about 900 thousand barrels per day from the Athabasca, Cold Lake and Peace River deposits at the end of 2003 (Figure 2)(5),(6),(7). Figure 3 shows the locations of the significant oil sands projects including the mining projects. From the total production, about 60% is from surface mining, only in the Athabasca area, and the other 40% from in-situ recovery methods which consist of thermal recovery (27%) and primary production (13%). Keywords: in-situ recovery method, operation, enhanced recovery, heavy oil, oil sand, upstream oil & gas, cold lake, bitumen, drainage, recovery method Subjects: Improved and Enhanced Recovery, Unconventional and Complex Reservoirs, Oil sand, oil shale, bitumen This content is only available via PDF. 2005. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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.

Study designOther design
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".

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Citations2
Published2005
Admission routes2
Has abstractyes

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