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Record W2072774160 · doi:10.2118/04-08-discussion

Author's Response to Discussion of "When Is It Important to Consider Geomechanics in SAGD Operations?"

2004· article· en· W2072774160 on OpenAlexaff
P. Li

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeomechanicsSteam injectionPetroleum engineeringOil sandsGeotechnical engineeringPore water pressurePermeability (electromagnetism)Shear (geology)GeologyShear stressEnhanced oil recoveryMechanicsMaterials scienceChemistryPetrology

Abstract

fetched live from OpenAlex

Congratulations to Rick and Pingke on their excellent paper(1), which was very impressive and enjoyable. Many technical papers were presented on the reduction of effective stress through elevating pore pressure and forcing oil sands to shear failure. However, the role of heating was not discussed in other papers. I now clearly understand the effect of reservoir heating and associated thermal expansion on stress-strain behaviour. For a long time, I have believed that heating should assist sands to reach shear failure in the reservoir. The contents of their paper are the latest and highest quality information on the geomechanical properties of oil sands. I have had different experiences with the geomechanical properties of oil sands and I would like to introduce my thoughts and recommendations for future study. I define geomechanical behaviours as changes in fluid flow properties due to a change in pore pressures and temperatures. Most changes are detectable through the analysis of temperature variations at observation wells and can be confirmed by rigorous numerical simulation studies. Some examples of geomechanical behaviours are as follows:Steam chambers are detected to stop rising or shrinking when injection pressure is reduced.Steam chambers resume rising when pressure is increased.Steam injection rates sharply increase when pressure is increased during a cyclic steam stimulation process.Other phenomena at high pressure and high temperature operations that are hard to understand through the examination of reservoir properties determined from core and log analysis. These phenomena are difficult to explain by assigning 10 to 20﹪ changes in absolute permeability. When the effective stress is reduced in geomechanical laboratory tests, the sands start to dilate and absolute permeability increases. When effective stress is reduced by injecting high mobility fluid (such as steam) into the reservoir, the dilated space becomes occupied by the injection fluid (steam and water) and generates wormhole type flow paths. Under these conditions, the mobility of the injection fluid is enhanced but that of the resident fluid (bitumen) is not changed.This speculation could be confirmed by analyzing actual field performance data. The first example in demonstrating the geomechanical behaviour of oil sands is the characteristic fluid flow of a cyclic steam stimulation process. Injectivity of steam under the native reservoir pressure is extremely low but can be dramatically improved when ore pressure is increased. According to the Sand Deformation concept(2), this is due to the creation of wormhole type flow channels by increasing injection pressure (Figure 1). Steam injection provides rising reservoir pressure thus lowering effective stress and resulting in the dilation of the formation. The generated space is then occupied by steam and its condensate. This is how the enormous increase in steam injectivity under high-pressure operation can be explained. Injection fluids (steam and condensate) gain huge increases in mobility but resident fluids do not undergo significant changes in the region where the failure zone is developed. This is the basic premise behind the Sand Deformation concept.

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)0.008
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.049
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0050.005
Open science0.0040.005
Research integrity0.0290.025
Insufficient payload (model declined to judge)0.0330.019

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 head0.249
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2004
Admission routes1
Has abstractyes

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