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Record W2006461283 · doi:10.2118/2007-124

Basic Investigations on Enhanced Gas Recovery by Gas-Gas Displacement

2007· article· en· W2006461283 on OpenAlexaboutno aff
Alex Turta, S. Sim, A.K. Singhal, Blaine F. Hawkins

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsDisplacement (psychology)Petroleum engineeringEnvironmental scienceGas analysisMaterials scienceProcess engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

Abstract The paper presents basic data on Enhanced Gas Recovery (EGR) by gas-gas displacement for nearly depleted natural gas reservoirs, by injecting waste gases. The soundness of the concept of gas-gas displacement for enhancing gas recovery was investigated via laboratory investigations, compositional modeling and economic analyses. Paramount Resources is field testing the concept in their GRIPE Project in the Athabasca region of Alberta, to enhance production from a gas bearing stratum overlying the oil sand interval. This paper is a part of a series of papers presenting results of EGR research conducted over a four year period (2003- 2006). The main targets were volumetric (closed) reservoirs, in advanced phases of exploitation. Results of basic research on methane displaced from core samples by pure gases (pure CO2 or pure N2), as well as flue gases (mixtures of CO2 and N2) and a CO2/ SO2 mixture, are presented. A series of 13 gas/gas displacement tests in 30cm-long, 4cm diameter, Berea cores were conducted at a temperature of 700C and a pressure of 6,200 kPa. Most of the tests were conducted in the presence of connate water, while others were conducted without connate water (dry cores) to confirm and bench mark the results by other investigators. The tests on consolidated cores showed that for pure nitrogen and pure CO2, used as the displacing medium, the recovery was comparable. In case a mixture of CO2 and nitrogen displaced the natural gas, it was observed that there was a delay in CO2 breakthrough, associated with a period when only a mixture of methane and nitrogen was produced. This is so because solubility of CO2 in connate water is considerably higher than that of nitrogen. This directly leads to a higher gas recovery due to a longer exploitation period, given the fact that up to 20% nitrogen can be tolerated in the produced stream, as opposed to only 1% for CO2 case. For this period of methane and nitrogen production, there are no operational problems associated with the corrosive nature of CO2. EGR by gas-gas displacement is seen as a promising way of prolonging the productive life and economic recovery of many depleting volumetric gas reservoirs. Introduction Alberta currently has 26,000 gas pools, which are in different stages of exploitation. For these gas reservoirs, the pools that should be considered first in the implementation of large-scale EGR-CO2 and CO2 storage have not yet been identified, and no screening criteria have yet been developed. Currently, only the concept of "disused gas reservoirs" has been advanced1 for CO2 storage. This concept implies that only those reservoirs that are in an advanced stage of depletion (with very little marketable gas left), traditionally with extremely low current pressure, or which are water invaded, should be considered. In this context, they have been considered exclusively for CO2 storage and not for enhanced gas recovery (EGR). This paper brings a new concept: that of simultaneous EGR and CO2 storage.

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)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations44
Published2007
Admission routes1
Has abstractyes

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