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Record W3002669646 · doi:10.2118/199728-ms

Developing Methodology for DFIT Design and Pressure Interpretation by Coupled Reservoir Geomechanics Flow Simulation

2020· article· en· W3002669646 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 Hydraulic Fracturing Technology Conference and Exhibition · 2020
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsApache (Canada)
Fundersnot available
KeywordsGeomechanicsClosure (psychology)GeologyFlow (mathematics)Fracture (geology)Geotechnical engineeringPetroleum engineeringHydraulic fracturingReservoir simulationMechanics

Abstract

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Abstract A numerical, coupled reservoir flow and geomechanics model has been built using a black-oil simulator and evaluated for diagnostic fracture injection test (DFITs) in unconventional reservoirs. DFITs have evolved into a commonly used technique to generate direct estimates of some key unconventional reservoir characteristics. Challenges, however, arise due to the complexity of the unconventional reservoir characteristics, long shut-in times to reach the closure pressure, and the long test durations to obtain realistic reservoir parameters from pseudoradial flow. One way to improve the analysis of minifrac tests in unconventional reservoirs is to use a coupled geomechanics and flow simulator, which is capable of representing the interactions between the reservoir fractures and minifrac developed during minifrac tests. The numerical model used in this work is based on coupling the geomechanical rock properties with the reservoir flow model. The geomechanical model simulates the growth and subsequent closure of the hydraulic and secondary fractures by modeling the change in the reservoir stresses. Furthermore, the model simulates the minifrac pressure response before fracture-closure as well as during the after-closure falloff period. The pressure response during the falloff period is then analyzed to evaluate the reservoir properties using Nolte pre-closure and after-closure analysis techniques. The coupled geomechanics and flow simulation of minifrac provides the capability of modeling the fracture breakdown and fracture closure and estimating the fracture dimensions. The traditional fracture design tools provide similar information focusing only on the geomechanics of the rock and ignoring the effect of the reservoir flow. An additional advantage of the simulator used in this work is to provide estimates of fracture stiffness, fracture closure permeability, residual permeability, and permeability of the matrix. The simulator allows pressure matching and successfully simulates the reservoir flow for extended shut-in periods. The simulator allows designing DFITs with different injection volumes, rates, and shut-in periods and thus helps provide the optimum parameters for the test. The after-shut-in flow regimes generated by the simulation model agree with the DFIT theory.

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score1.000

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 head0.045
GPT teacher head0.273
Teacher spread0.228 · 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