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Record W2117519266 · doi:10.1190/1.2369835

Heavy oil reservoir characterization using Vp/Vs ratios and spectral decomposition

2006· article· en· W2117519266 on OpenAlexaffabout
Carmen C. Dumitrescu, Larry Lines

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCharacterization (materials science)DecompositionPetroleum engineeringEnvironmental scienceReservoir modelingEnvironmental chemistryMaterials scienceChemical engineeringChemistryGeologyNanotechnologyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

It is well known, especially for heavy oil projects, that Vp/Vs is a very good lithology discriminator. In this paper we provide a Vp/Vs ratio volume based on AVO analysis and simultaneous inversion using only the PP component. The new results are compared with the previous results based on the traveltime measurements on the vertical and radial components of the multicomponent records (Lines et al., 2005). The area for this project is a heavy oil field (oil sands of the Devonian‐Mississippian Bakken Formations) near Plover Lake, Saskatchewan. In this study we analysed Nexen's 3D‐3C seismic survey, acquired by Veritas DGC and processed by Sensor Geophysical. We performed AVO analysis followed by simultaneous inversion on pre‐stack time migrated gathers in order to derive P‐impedance, S‐impedance, density and Vp/Vs volumes. The inversion approach accounts for the petrophysical relationship that exists in the logarithmic domain between: (1) P‐impedance and S‐impedance and (2) P‐impedance and density. It provides a significant improvement over separate inversions of the two AVO attributes P‐ and S‐wave impedance reflectivity, particularly for Vp/Vs ratio estimates. Additional rock properties, such as rigidity and incompressibility were derived from P‐impedance and S‐impedance (Goodway et al., 1997). The Vp/Vs volume from simultaneous inversion compared very well with the similar volume obtained from a previous study. The Vp/Vs results for the Sparky/Waseca‐Torquay interval show similar general features. The new volume, based on simultaneous inversion produces Vp/Vs ratio values with a vertical resolution of 2ms (sampling rate) whereas the previous results from travel times are just averaged over 60 ms (Sparky — Torquay interval). The new results are sharper and offer more details in identification of the sand and shale. In this project we applied spectral decomposition (discrete Fourier transform) to the AVO attributes P‐ and S‐wave impedance reflectivities to better predict changes in lithology and flow barrier. The spectral decomposition amplitude and phase spectra volumes show structural geologic features and the limits of the reservoir.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.252
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2006
Admission routes2
Has abstractyes

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