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Record W1982150862 · doi:10.2118/00-03-05

Analysis of Transient Pressure Response Near a Horizontal Well-A Coupled Diffusion-deformation Approach

2000· article· en· W1982150862 on OpenAlexafffund
Y. Li, R.C.K. Wong, K.C. Yeung

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsSuncor Energy (Canada)University of Calgary
FundersSouthwest UniversitySouthwest Jiaotong UniversitySuncor Energy IncorporatedMcMaster UniversityU.S. Department of Energy
KeywordsThermal diffusivityMechanicsDiffusion equationPressure gradientCompressibilityMass diffusivityPermeability (electromagnetism)Porous mediumPorosityPore water pressureGeotechnical engineeringThermodynamicsGeologyChemistryPhysicsEngineering

Abstract

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Abstract Analysis of transient pressure response near a horizontal well has been based largely upon the analysis of mathematical solutions for the diffusivity equation. The diffusivity equation satisfies the principle of mass conservation, but does not consider the principle of equilibrium. No deformation properties of reservoir are included in the diffusivity equation. However, in some deformable reservoirs, the stress and deformation caused by injection or production could be so significant that it might affect the pressure response. This paper presents analyses of transient pressure response near a horizontal well using a coupled diffusion-deformation method. The results are compared with those obtained from the single diffusivity equation. Implications on practical applications such as well testing are addressed. Introduction Reliable information about in situ reservoir conditions is important in many phases of petroleum engineering. Much of the information can be obtained from well testing by measuring the variations in wellbore pressure that result from changes in the operating condition of the well. For example, pressure transients measured at an injecting well (under constant injecting rate) after it is shut in can be used to estimate the permeability of the reservoir. Well testing theory is based largely upon the solutions for the diffusivity equation, the differential equation for fluid flow in porous medium. Traditionally, it is assumed that the permeability, porosity and compressibility of fluid are constant, and pressure gradient is small(1,2). In fact, the change in fluid pressure is related to the change in the volume of fluid and reservoir rock. In order to obtain a better insight into the reservoir properties, two mechanisms should be considered in the interaction between the interstitial fluid and the porous rock:an increase of pore pressure induces a dilation of the rock; andcompression of the rock causes a rise of pore pressure, if the fluid is prevented from escaping the pore network. On the other hand, if pore pressure induced by compression of the rock is allowed to dissipate through diffusive fluid mass transport, further deformation of the rock progressively takes place. The earliest theory to account for this coupled diffusion-deformation mechanism was developed by Biot(3) who proposed a theory for three-dimensional consolidation of soils. Terazghi(4) developed a model for one-dimensional consolidation of soils. Rice and Cleary(5) linked the theory of poroelasticity to the concepts in rock mechanics with the full account of fluid and solid grain compressibility's. The objective of this paper is to study the effects of coupled diffusion-deformation mechanisms and compressibility's of fluid and grain on the pressure response near a horizontal well. Numerical cases in oil sand and sandstone reservoirs are generated to investigate the above effects, using a coupled numerical simulator. Then, the results are compared with those from the well testing method. Analysis Methods Single Diffusion Equation (Well Testing Analysis Technique) In 1967, Matthews and Russell(2) published their monograph dealing with well testing and analysis, which became a standard reference for many petroleum engineers. The basic fluid diffusion equation is a combination of the law of conservation of mass, Darcy's law, and state equation.

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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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.176
Teacher spread0.173 · 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".

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Citations1
Published2000
Admission routes2
Has abstractyes

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