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Record W1995112540 · doi:10.2118/97848-pa

Mapping Reservoir Volume Changes During Cyclic Steam Stimulation Using Tiltmeter-Based Surface-Deformation Measurements

2008· article· en· W1995112540 on OpenAlexafffund
Jing Du, S. J. Brissenden, P. McGillivray, Stephen Bourne, Paul Hofstra, Eric Davis, William H. Roadarmel, Stephen Wolhart, Scott Marsic, R. Gusek, Christopher Amyas Wright

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsShell (Canada)
FundersShell Canada
KeywordsTiltmeterDeformation (meteorology)Steam injectionGeologyPetroleum engineeringWellheadCasingVolume (thermodynamics)Geotechnical engineeringOil fieldGroundwater-related subsidenceSubsidenceGeomorphology

Abstract

fetched live from OpenAlex

Surface-deformation measurements have been used for years in oil fields to monitor production, waterflooding, waste injection, steam flooding, and cyclic steam stimulation (CSS). They have been proved to be a very effective way to monitor field operations and save money for operators wishing to avoid unwanted surface breaches, casing failures, and excessive subsidence because of production. This paper demonstrates that more information can be extracted from surface-deformation measurements by inverting the surface deformation for the volumetric deformation at the reservoir level using the inversion techniques from the literature, so that the areal distribution of volumetric deformation can be identified. This leads to a better understanding of reservoir behavior and also provides additional data for integration into coupled reservoir simulation modeling. This paper shows the results of mapped reservoir volume changes from two cyclic steam injection projects using tiltmeter-based surface deformation measurements.

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)0.000
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 score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.110
GPT teacher head0.274
Teacher spread0.164 · 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

Citations36
Published2008
Admission routes2
Has abstractyes

Explore more

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