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Record W2102619736 · doi:10.2118/07-03-01

Effects of Criterion Values on Estimation of the Radius of Drainage and Stabilization Time

2007· article· en· W2102619736 on OpenAlexaff
M. Enamul Hossain, M. Tamim, N. M. Anisur Rahman

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRADIUSProduction (economics)Function (biology)MathematicsDrainageMechanicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

Abstract After a well starts flowing, a larger portion of the reservoir contributes to production. At any given time, the radius of the portion of the reservoir that demonstrates a pressure gradient and contributes to production of fluid is the radius of drainage (ROD). The time required for the entire reservoir just to be able to contribute to production is the stabilization time. Estimating the ROD and stabilization time is very important in well test design and production optimization. It has been a great challenge to estimate the ROD and stabilization time accurately because of inherent uncertainties with respect to the rock and fluid properties. This study examines the effects of criterion values on the estimated values of the ROD and stabilization time. As expected, estimated values of the ROD and stabilization time vary considerably, depending on the suggested criteria. The primary objective of this study is to recognize and appreciate the importance of criterion values for defining the ROD and stabilization time. Generalized correlations have been proposed that allow one to determine the ROD and stabilization time as a function of the criterion values. The relationship between a pressure criterion and the corresponding rate criterion has been examined also. Introduction The concepts of ROD and stabilization time are commonly used in reservoir engineering and in well test analysis. Estimating the ROD is very important on many counts. A well test analysis provides important reservoir information based on the area sampled within the ROD. It is important to know the extent of the reservoir that is being sampled when determining the parameters like permeability and storage capacity from the analysis. In other words, the well test analysis provides the global values of the reservoir parameters that are valid over the radius of investigation(1). Thus, the obtained reservoir information is good for the region within the ROD. In addition, knowing the ROD helps optimize the locations of new wells to be drilled in a field. It is very difficult to identify the well test run time without an estimate of the ROD and stabilization time. The ROD concept has both quantitative and qualitative importance in well test design and analysis. This distance is dependent on the way the pressure response propagates through the reservoir. It is also related to rock, fluid properties and elapsed time. Thus, the ROD concept presents a guide for well test design. This concept can be used also to estimate the time required to test the desired depth into the formation. However, estimating any ROD has been dependent on the assumed level of the criterion for pressure or flow rate. As a result, there can be substantial variations in the estimated magnitude of the ROD. Depending on the criterion parameters and their values, a number of definitions have been proposed for the ROD and stabilization time equations. Daungkaew et al.(2) have provided a comprehensive account of these efforts(3–16). Muskat(3), Jones(7) and Van Poolen(8) postulated ROD equations based on pressure criteria. Tek et al.(6) postulated the same based on a rate criterion.

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)0.010
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.002
GPT teacher head0.180
Teacher spread0.179 · 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 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

Citations9
Published2007
Admission routes1
Has abstractyes

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