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Record W2296735629 · doi:10.2118/175929-pa

History Matching and Forecasting Tight Gas Condensate and Oil Wells by Use of an Approximate Semianalytical Model Derived From the Dynamic-Drainage-Area Concept

2016· article· en· W2296735629 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 Reservoir Evaluation & Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMultiphase flowPetroleum engineeringSaturation (graph theory)MechanicsFlow (mathematics)Tight gasWork (physics)GeologyPermeability (electromagnetism)Fluid dynamicsReservoir simulationMathematicsEngineeringHydraulic fracturingPhysicsChemistryMechanical engineering

Abstract

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Summary Recently, low-permeability (tight) gas condensate and oil reservoirs have been the focus of exploitation by operators in North America. Multifractured horizontal wells (MFHWs) producing from these reservoirs commonly exhibit long periods of transient flow, during which two-phase flow of oil and gas begins because of well flowing pressures dropping to less than saturation pressure. History matching and forecasting of such wells can be rigorously performed by use of numerical simulation, but this approach requires significant data and time to set up. Analytical methods, although requiring fewer data and less time to apply, have historically been developed only for single-phase-flow scenarios. In this work, a novel and rigorous analytical method is developed for history matching and forecasting MFHWs experiencing multiphase flow during the transient and boundary-dominated flow periods. The distance-of-investigation (DOI) concept has been used for many years in pressure-transient analysis to estimate distances of reservoir boundaries to wells, among other applications. In the current work, the DOI concept is used to estimate dynamic drainage area (DDA) to forecast tight gas condensate and oil wells; a linear flow geometry is assumed. During transient flow, the DDA is calculated at each timestep by use of the linear-flow DOI formulation; a multiphase version of the linear-flow productivity-index (PI) equation and material-balance equations for gas, condensate, and oil are solved iteratively for pressure, saturation, and fluid-production rate. The PI equations for gas and oil use pseudopressure, which is evaluated with saturation/pressure relationships derived from pressure/volume/temperature data. For boundary-dominated flow, when the drainage area is static, the inflow equations are again coupled with material balance for both phases. The new method is validated against numerical simulation, covering a wide range of fluid properties and operating conditions. The new method matches the simulation acceptably for all cases studied. Field examples of MFHWs are also analyzed to demonstrate the practical applicability of the approach. The three liquid-rich shale examples analyzed were also chosen to represent a wide range of fluid properties. In all cases, acceptable history matches are achieved. The new analytical forecasting/history-matching procedure developed in this work provides a practical alternative to numerical simulation for tight gas condensate and oil experiencing two-phase flow during the transient-flow period. The method, which does not rely on Laplace-space solutions, is conceptually simple to understand, easy to implement, and avoids the inconvenience of Laplace-space inversion.

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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)0.001
metaresearch head score (Gemma)0.001
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 score0.240
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.061
GPT teacher head0.272
Teacher spread0.211 · 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