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Record W2086369832 · doi:10.2118/67204-ms

In-Depth Investigation of the Validity of the Archie Equation in Carbonate Rocks

2001· article· en· W2086369832 on OpenAlexaff
Talia Shamsi Ara, Soran Talabani, Hans Vaziri, M. R. Islam

Bibliographic record

VenueSPE Production and Operations Symposium · 2001
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCarbonateCarbonate rockGeologyPorosityMineralogyTortuositySaturation (graph theory)Equation of stateElectrical resistivity and conductivityThermodynamicsGeotechnical engineeringMaterials scienceMathematics

Abstract

fetched live from OpenAlex

Abstract Archie found an empirical equation for consolidated sandstones relating several formation parameters, such as, porosity and water saturation. Despite its common use by petroleum engineers, Archie equation is not easy to apply to carbonate rocks because formation parameters (a, m, n) are functions of changes in the pore geometry, clay content, tortuosity of the pores, as well as formation pressure. The other important issue that Archie equation fails to address is the fluid critical point for the multi-component state in which different phases co-exist. This being the case for light oil and condensate reservoirs, the straightforward application of the Archie equation in carbonate rocks has severe limitations. The Archie equation is valid only when the rock is strongly water wet and clay free, which is not the case in carbonate rocks. There is no linear or direct correlation between resistivity index (IR) and formation water saturation in the carbonate rocks. Therefore, the Archie equation cannot be generalized over the entire carbonate reservoir. In this paper, a series of experiments is performed in order to derive the correct form of the Archie Equation that can be applied to carbonate rocks. The parameter a is further split to account for the composition, pore geometry and formation pressure. By separating these parameters, it is possible to find more precise correlation with formation resistivity and formation water saturation for carbonate reservoirs. Also derived are the correlations between resistivity and the composition of the carbonate rock as well as formation pressure. Finally, an equation is proposed for taking into account changes due to the presence of critical fluids. The generalized equation can then be applied to any fluid in a carbonate formation with varied geometry and clay content.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.228
Teacher spread0.204 · 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 designBench or experimental
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

Citations35
Published2001
Admission routes1
Has abstractyes

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