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Record W2050314196 · doi:10.2118/2000-040

Applying Canadian Heavy Oil Technology to an Argentine Heavy Oil Reservoir

2000· article· en· W2050314196 on OpenAlexaboutno aff
K.A. Miller, A.J. Holub

Bibliographic record

VenueCanadian International Petroleum Conference · 2000
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCitationPetroleumLibrary scienceMillerComputer scienceGeologyPaleontology

Abstract

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Abstract With the exception of the highly developed world class deposits in Venezuela, production of heavy oil is not common in South America. YPF S. A. (now Repsol YPF), the largest oil producer in Argentina, operated its Cerro Fortunoso heavy oil reservoir for a number of years using techniques primarily adapted from light oil reservoirs. The economic performance was sufficient for periodic expansion, and for construction of the surface infrastructure necessary to collect and pipeline the oil offsite for treatment. Recently, YPF recognized the possibility that technology from the highly developed Canadian heavy oil industry could aid exploitation of the Cerro Fortunoso reservoir. This paper discusses the challenges and successes of the reservoir engineering portion of a multifaceted one-year project between Tecknica Overseas Ltd. of Calgary and YPF S.A. Introduction The Cerro Fortunoso Field is located in the northwest portion of the Neuquen Basin of Argentina (Figure 1). Cerro Fortunoso was discovered in 1985, and first produced in 1986. Since that time, the project has been expanded to include over 120 wells(Figure 2). Cumulative oil production through June 1997 exceeded 1.5 million m3. Multiple sand zones have been routinely completed, stimulated, and co-mingled for production of 14 to 17 ° API oil. Reciprocating pumps and pump jacks have generally been used, although gas lift has been used in several wells with high GOR's. Individual well production is gathered into two batteries using heated or buried flow lines. Field production is shipped by pipeline to a regional treating facility. YPF contracted Teknica Overseas Ltd. to perform an in depth review of the Cerro Fortunoso project. One of the primary engineering goals was to determine how engineering technology from the mature Western Canadian heavy oil industry could be applied to improve contains a summary of the results. LANGUAGE AND CULTURAL ISSUES All the prior data, reports, and analyses for the Cerro Fortunoso Project were written in Spanish. This was overcome in two ways. YPF S. A. asssigned an engineer and a geologist with training in English to reside in Calgary for the duration of the study. Teknica employees received ongoing formal and informal training in Spanish. A dictionary of Spanish - English oil field terms was created and continually updated. The units used to describe Cerro Fortunoso Project data were a combination of English, Metric, and European practice. Conversion Tables were created to allow data to be expressed in each system (Table 1). Contacts with project staff in Argentina were established to obtain missing data and request additional information and tests. Email was effective for many tasks, but some locations did not have that capability. Faxes and telephone conversations were limited to high need occasions due to higher costs and occasional transmission problems. Overall, contact with field personal was not significantly different from that experienced working with remote Canadian projects. Interaction between the two groups was excellent. No cultural difficulties occurred. GEOLOGY AND PETROPHYSICS The geology and petrophysics of the Upper Cretaceous Neuquen Group reservoir at Cerro Fortunoso are strikingly different from those in Lower Cretaceous Western Canadian heavy oil and bitumen reservoirs.

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 score0.558
Threshold uncertainty score0.879

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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