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Record W2604120466 · doi:10.3997/1365-2397.34.9.86740

Constraining a 3D anisotropic tomography inversion with 800 wells – A Canadian oil sands case history

2016· article· en· W2604120466 on OpenAlexaboutno aff
Sylvestre Charles, Jiwu Lin, Lijuan Du, Ahmed Mouaki Benani Chebihat

Bibliographic record

VenueFirst Break · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyOil sandsInversion (geology)AsphaltGemologyBoreholeEnvironmental geologyEconomic geologyGeophysical imagingAnisotropyReservoir modelingPetrologyPetroleum engineeringMineralogyEngineering geologyGeomorphologyStructural basinHydrogeologyGeotechnical engineeringGeophysicsSeismologyTectonicsVolcanism

Abstract

fetched live from OpenAlex

This Canadian oil-sands case history is a very shallow play with a complex geology that includes Quaternary thrusting at surface, sinkholes, and highly karsted Devonian carbonates at the base of the notoriously complex McMurray reservoir. Despite this challenging environment, we were able to demonstrate that Depth Imaging brought significant improvements as compared to the routinely used time imaging. Recent developments in Anisotropic Pre-Stack Depth Imaging technologies provided a better focused and better positioned 3D subsurface image that accurately tied several hundreds of wells. These results were achieved using steering filters, solver bounds and simultaneous multi-parameter tomography inversion while constraining the tomography updates with the well top picks from over 800 wells. Surveys of different vintages, geometries, orientations and shooting directions were regularized using 5D interpolation and merged together. Besides a better imaging of the subsurface, one of main objective of the project was the characterization of the McMurray reservoir. To that aim, the Anisotropic Pre-Stack Depth Migration (APSDM) generated better conditioned Offset Vector Tile gathers for subsequent pre-stack inversion work. The Alberta oil sands are one of the largest bituminous hydrocarbon reserves in the world (Alberta Energy Regulator, 2015). At reservoir temperature, the bitumen is so viscous that it can almost be considered as a solid. In situ thermal recovery processes such as steam-assisted gravity drainage (SAGD) that lower viscosity and increase mobility are required to extract the bitumen from the reservoir. SAGD operations consist of horizontal well pairs that are drilled into the base of the reservoir. In each pair, one well is drilled about 5 m directly above the other well. The top well is injected with steam to melt the bitumen. The bitumen seeps down towards the bottom producing well, which pumps the bitumen to the surface. The well pairs are generally configured to about ten parallel horizontal well pairs that are around 100 m apart horizontally and are 1000 m long, which constitute a 1-km2 pad.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.165
Teacher spread0.154 · 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 designObservational
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

Citations1
Published2016
Admission routes1
Has abstractyes

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