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Record W2069135396 · doi:10.2118/2002-079

Preliminary Laboratory Evaluation of Cold and Post-Cold Production Methods for Heavy Oil Reservoirs

2002· article· en· W2069135396 on OpenAlexaffabout
Apostolos Kantzas, G. Brook

Bibliographic record

VenueCanadian International Petroleum Conference · 2002
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsNexen (Canada)University of Calgary
Fundersnot available
KeywordsProduction (economics)Environmental sciencePetroleum engineeringGeology

Abstract

fetched live from OpenAlex

Abstract The problem of cold and post-cold production for heavy oil [Lloydminster type] reservoirs is addressed. First, an overview of cold production related material is presented. The reservoir state is postulated based on behaviour of laboratory systems. Then several experimental methods for additional heavy oil recovery are attempted in the same cold produced laboratory models. The methods tested include water flooding, gas flooding, and polymer flooding. The effect of sand production is evaluated. The results are very preliminary, but encouraging. This work is offered as a challenge for the industry to consider the state of all cold produced heavy oil reservoirs and focus on the possible alternatives for this significant Canadian reserve. Introduction The heavy oil and oil sand deposits of Western Canada represents one of the largest hydrocarbon accumulations in the world with a resource base of nearly 1.7 trillion bbls. This is 1.5 times larger than the proven reserves of the entire Middle East. The bulk of the reserves are contained in three major geologically distinct regions. These areas are the conventional heavy oil of Lloydminster area, the Carbonate Triangle, and the oil sands deposits. Enhancement of primary production of heavy oil through the so-called cold production mechanism has been a popular topic in the heavy oil industry for the past fifteen years. However, cold production alone cannot produce more than an estimated 10–15% of the original oil in place (OOIP). This paper addresses the issue of post-cold-production or in general post-primary production of heavy oil via different injection techniques that include water flooding, polymer flooding or pressure pulsing / shut-in. Several independent sets of experiments were run that include one cold production experiment in a large cylindrical model with a central production well (radial production geometry), 2 linear core floods, four experiments at ambient conditions in rectangular geometry physical models and six experiments at reservoir conditions in rectangular geometry physical models (one including sand production). LITERATURE SURVEY A large variety of heavy oil EOR methods are proposed in the literature1. Earlier work on non-thermal recovery of heavy oil did not take into account cold production mechanisms and thus it becomes questionable how such work will apply to the current state of the Canadian heavy oil fields. Notable is the work performed in the University of Alberta by the group of Prof. Farouq Ali2,3. Some more recent work includes the following: Productivity improvement through enhancements of primary production has been a relatively recent exercise of the oil industry and was led by Amoco4. Amoco's main focus has been in the development of primary production technology in areas previously thought not to be capable of such production. Most of the early reported work deals with the Elk Point / Lindberg sands, where live oil viscosities range from 2000 to 55,000 cp at reservoir temperatures. It was found that sand production increases the productivity of the producing interval and allows for greater fluid flow rates to the wells.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.281
Teacher spread0.253 · 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 designSimulation or modeling
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
Published2002
Admission routes2
Has abstractyes

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