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Record W2986502429 · doi:10.2118/195359-pa

A Correlation for Estimating the Biot Coefficient

2019· article· en· W2986502429 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Drilling & Completion · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiot numberCorrelation coefficientPorosityGeologyPermeability (electromagnetism)PoromechanicsGeotechnical engineeringPetroleum engineeringMathematicsPorous mediumMechanicsStatisticsPhysics

Abstract

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Summary The objective of this paper is to develop an easy-to-use correlation for estimating the Biot coefficient. This is important because the Biot coefficient plays an important role in solving many practical petroleum-engineering problems, including, for example, the design of hydraulic-fracturing jobs and the estimation of in-situ closure stress on proppant. The procedure for developing the proposed empirical correlation uses data from various lithologies including limestone, sandstone, shale, marble, and granite. Thus, the correlation has application in conventional and unconventional petroleum reservoirs. The use of the correlation requires knowledge of permeability and porosity, the data commonly available in petroleum engineering (on the other hand, the Biot coefficient data are almost never available). The ratios of permeability to porosity (commonly known as process or delivery speed) and pore-throat radii (rp35) are entered for estimating the Biot coefficient from the correlation proposed in this paper. The correlation is useful in those cases where sophisticated experimental work needed for estimating the Biot poroelastic coefficient is not available. Testing against various data sets indicates that the proposed correlation provides reasonable results. In the past, methods with different complexity levels have been used for estimating the Biot coefficient. These have included, for example, (1) a method that requires the knowledge of bulk modulus of the rock mineral and bulk modulus of the skeleton with no fluids in it, parameters that are not usually available for petroleum reservoirs; (2) a method that is based on knowledge of only porosity; (3) a method that is based on the knowledge of only permeability; and (4) an approach that simply assumes that the Biot coefficient is equal to 1.0 or some other number. The proposed correlation falls somewhere in the middle. It is not as simple as saying that the Biot coefficient is equal to unity or saying that it depends only on porosity, or only on permeability. On the other hand, it is not as complex as requiring sophisticated laboratory work of the type mentioned in (1) above. The novelty of this work is the development of an original easy-to-use correlation for estimating the Biot coefficient in conventional and unconventional (tight and shale) reservoirs on the basis of knowledge of the ratio of permeability to porosity (k/ϕ) and the pore-throat radius (rp35). The correlation is developed in such a way that it also has application for estimating the Biot coefficient in the case of unconsolidated petroleum reservoirs and oil sands. The overall approach allows the integration of geomechanics with flow units, geology, petrophysics, and reservoir engineering (RE).

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.

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: none
Teacher disagreement score0.811
Threshold uncertainty score0.271

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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