MétaCan
Menu
Back to cohort
Record W2039688407 · doi:10.2118/04-06-01

A Fully Implicit Single Phase T-H-M Fracture Model for Modelling Hydraulic Fracturing in Oil Sands

2004· article· en· W2039688407 on OpenAlexafffund
Ali Pak, Dave Chan

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaShell Canada
KeywordsHydraulic fracturingFracture (geology)MechanicsGeologyPetroleum engineeringGeotechnical engineeringPlane stressFlow (mathematics)Finite element methodStress (linguistics)Fluid dynamicsGeomechanicsEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Abstract Enhancing oil extraction from oil sands with a hydraulic fracturing technique has been widely used in practice. Due to the complexity of the actual process, modelling of hydraulic fracturing is far behind its application. Reproducing the effects of high pore pressure and high temperature, combined with complex stress changes in the oil sand reservoir, requires a comprehensive numerical model which is capable of simulating the fracturing phenomenon. To capture all of these aspects in the problem, three partial differential equations, i.e., equilibrium, flow, and heat transfer, should be solved simultaneously in a fully implicit (coupled) manner. A fully coupled thermo-hydro-mechanical fracture finite element model is developed to incorporate all of the above features. The model is capable of analyzing hydraulic fracture problems in axisymmetric or plane strain conditions with any desired boundary conditions, e.g., constant rate of fluid injection, pressure, temperature, and fluid flow/thermal flux. Fractures can be initiated either by excessive tensile stress or shear stress. The fracture process is simulated using a node-splitting technique. Once a fracture is formed, special fracture elements are introduced to provide in-plane transmissivity of fluid. Effectiveness of the model is evaluated by solving several examples and comparing the numerical results with analytical solutions. The model is also used to simulate large-scale laboratory hydraulic fracturing experiments. Introduction Hydraulic fracturing technique has been a fast growing technology since its first application in 1947. By 1988, more than one million hydraulic fracturing treatments had been performed(1), and today this technique is one of the most important methods in enhancing oil extraction from wells. Hydraulic fracturing in oil sand reservoirs plays an even more important role. Due to low temperature and low permeability of oil sand deposits and high viscosity of bitumen, oil is virtually immobile(2). Hence, any attempt for in situ oil extraction should employ one of the following techniques: cyclic steam stimulation, in situ combustion, or hydraulic fracturing. Despite the fact that hydraulic fracturing technology has advanced significantly over the past fifty years, our ability to model the process has not changed as rapidly. As a matter of fact, this technique has been so successful that in the past, designingthe treatment with a high degree of precision was not of any interest. But as the industry moved towards applications of very high volume/rate, and highly engineered and sophisticated hydraulic fracturing treatments, the demand for more rigorous designs in order to optimize the procedure have become more important. On the other hand, without a thorough understanding of the physical process and the factors that are involved, our ability for an optimal design is limited. Modelling fluid flow combined with heat transfer in the reservoir has been used by the industry for a long time, and the fracturing process was often designed based on twodimensional closed-form solutions, such as Geertsma-de Klerk(3), or GdK in brief, and Perkins-Kern(4) and Nordgren(5), or PKN. Most of the flow and heat transfer models are based on the finite difference method, and effects of stresses and deformations in the ground, if not totally ignored, are solved in a decoupled or partially coupled manner with other elements.

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 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 score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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.

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

Citations16
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Canadian Petroleum TechnologySame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207