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Record W2092038069 · doi:10.2118/80997-pa

Coupled Geomechanical and Reservoir Modeling Investigating Poroelastic Effects of Cyclic Steam Stimulation in the Cold Lake Reservoir

2002· article· en· W2092038069 on OpenAlexafffund
D. A. Walters, A. Settari, P. R. Kry

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsImperial Oil (Canada)
FundersCanadian Natural Resources Limited
KeywordsPoromechanicsAquiferSteam injectionGeologyInjection wellPermeability (electromagnetism)Petroleum engineeringPore water pressureGeotechnical engineeringOil fieldBoreholePorosityPetrologySoil sciencePorous mediumGroundwater

Abstract

fetched live from OpenAlex

Summary The heating of bitumen reservoirs by cyclic steam stimulation (CSS) requires high pressures and temperatures that disturb the soil matrix. This disturbance results in a dilation of the soil matrix, creating regions of enhanced permeability and porosity, which impact both the injection and production cycles of steam stimulation and the porous zones not hydraulically connected to the reservoir. The volumetric strain changes reach far beyond the region of injection and include areas of both expansion and compression. The magnitude of the volumetric strains may result in significant displacements and strains being transferred to porous zones outside the reservoir. This can result in observable pressure changes in an otherwise hydraulically static system. Pressure data at an observation well drilled to monitor aquifer pressures showed a significant response to the CSS process occurring in the reservoir approximately 300 m below the aquifer. Coupled geomechanical and reservoir modeling and an analytical calculation both show that this pressure behavior is attributed to the poroelastic response of the aquifer caused by the CSS process occurring in the reservoir. This paper describes the field data, the methodology of the coupled reservoir and geomechanical modeling, and the result of the analysis of the field data with the coupled model. The analysis shows clearly that the aquifer response is not caused by a hydraulic communication with the reservoir. It also shows the capabilities of coupled modeling, as this type of a problem could not be analyzed with conventional reservoir simulation tools.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.253
Teacher spread0.226 · 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 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

Citations21
Published2002
Admission routes2
Has abstractyes

Explore more

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