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Record W2930009718 · doi:10.2118/193893-ms

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

2019· article· en· W2930009718 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Reservoir Simulation Conference · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWormholeFractalComputer scienceEnhanced oil recoveryFractal dimensionPetroleum engineeringGeologyMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract Cold heavy oil production with sand (CHOPS) is a non-thermal 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 is commonly acknowledged that wormhole growth due to sand failure is likely to follow fractal statistics, there are no established workflows to incorporate geomechanical 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 failure and fluidization being controlled by geomechanical 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 (non-equilibrium dissolution of gas) and sand failure are integrated. Public field data for several CHOPS fields in Canada is used to examine the results of the dynamic wormhole growth model and flow simulations. For example, 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 with realistic geomechanical constraints. 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.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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