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Record W3083120047 · doi:10.2118/193893-pa

A Sand-Arch Stability Constrained Dynamic Fractal Wormhole Growth Model for Simulating Cold Heavy-Oil Production with Sand

2020· article· en· W3083120047 on OpenAlexaffabout
Haisheng Yu, Juliana Y. Leung

Bibliographic record

VenueSPE Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWormholeArchFractalStability (learning theory)Computer scienceGeotechnical engineeringGeologyPetroleum engineeringEngineeringMathematicsStructural engineeringPhysics

Abstract

fetched live from OpenAlex

Summary Cold heavy-oil production with sand (CHOPS) is a nonthermal primary process that is widely adopted in many weakly consolidated heavy-oil deposits around the world. However, only 5 to 15% of the initial oil in place is typically recovered. Several solvent-assisted schemes are proposed as follow-up strategies to increase the recovery factor in post-CHOPS operations. The development of complex, heterogeneous, high-permeability channels or wormholes during CHOPS renders the analysis and scalability of these processes challenging. One of the key issues is how to properly estimate the dynamic growth of wormholes during CHOPS. Existing growth models generally offer a simplified representation of the wormhole network, which, in many cases, is denoted as an extended wellbore. Despite it being commonly acknowledged that wormhole growth due to sand-arch failure is likely to follow fractal statistics, there are no established workflows to incorporate sand-arch stability constraints into the construction of these fractal wormhole patterns. A novel dynamic wormhole growth model is developed to generate a set of realistic fractal wormhole networks during the CHOPS operations. It offers an improvement to the diffusion limited aggregation (DLA) algorithm with a sand-arch stability criterion. The outcome is a fractal pattern that mimics a realistic wormhole growth path, with sand-arch failure and fluidization being controlled by sand-arch stability constraints. The fractal pattern is updated dynamically by coupling compositional flow simulation on a locally refined grid and a stability criterion for the sand arch: the wormhole would continue expanding following the fractal pattern, provided that the pressure gradient at the tip exceeds the limit corresponding to a sand-arch stability criterion. Important transport mechanisms including foamy oil (nonequilibrium exsolution of gas) and sand-arch failure are integrated. Public field data for several CHOPS fields in Canada are used to examine the results of the dynamic wormhole growth model and flow simulations. For example, the sand production history is used to estimate a practical range for the critical pressure gradient representative of the sand-arch stability criterion. The oil and sand production histories show good agreement with the modeling results. In many CHOPS or post-CHOPS modeling studies, constant wormhole intensity is commonly assigned uniformly throughout the entire domain; as a result, the ensuing models are unlikely to capture the complex heterogeneous distribution of wormholes encountered in realistic reservoir settings. This work, however, proposes a novel model to integrate a set of statistical fractal patterns. The entire workflow has been readily integrated with commercial reservoir simulators, enabling it to be incorporated in practical field-scale operations design.

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 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: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.578

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 integrity0.0000.001
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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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 teacher head, 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

Citations13
Published2020
Admission routes2
Has abstractyes

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