Fully Coupled Numerical Modelling of Ground Surface Uplift in Steam Injection
Bibliographic record
Abstract
Abstract In enhanced oil recovery, steam injection involves high stresses, pressures, temperatures and volume changes. Traditional reservoir simulation fails to predict associated transient ground surface movements because it does not consider coupled geomechanical effects. We present a fully-coupled, thermal half-space model using a hybrid DDFEM method, in which a simultaneous finite element method (FEM) solution is adopted for the reservoir and the surrounding thermally affected zone, and a displacement discontinuity (DD) method used for the elastic, non-thermal zone. This approach provides transient ground surface movements in a natural manner. Introduction Enhanced oil recovery (EOR) methods involving high pressures and steam injection (steamflooding, cyclic steam stimulation, steam-assisted gravity drainage) are accompanied by large volume changes in the reservoir horizon. Ground movements in excess of 300 mm heave or subsidence are registered during injection and production cycles. Reservoir simulation cannot address this phenomena without due consideration of geomechanical effects. The earliest theory to account for coupled pore fluid behaviour and soil deformation was the Terzaghi one-dimensional consolidation theory, still used in soil mechanics. Since Biot's theory of consolidation(1) was introduced to petroleum engineering by Geertsma(2) with the coined term "poroelasticity,?? coupled analysis of petroleum geomechanics effects has been widely advocated(3-5). Coupled reservoir simulation can be carried out in a loosely coupled fashion(6, 7) or with a tightly coupled scheme(8-10), and comparisons of different coupling techniques can be found (11, 12). In reservoir simulation, a coupled analysis demands simultaneous solution of changes in (p,T) and fluid flow as well as stress and strain. Computing challenges persist in large-scale 3D applications to real cases where there are a huge number of equations to solve iteratively; e.g. thermo-poro-elasto-plastic analyses involving several simultaneous diffusion processes (Darcy, Fourier, Fick). In regions of large pressure, temperature, concentration or stress gradients, accurate solution requires small-scale discretization. If the problem has strong non-linearity, such as changes in permeability, compressibility, or other properties arising from changes in pressure and effective stress, the computational effort increases by several orders of magnitude because multiple iteration loops are needed. These issues mean that accurate analysis of realistic complex 3D problems is challenging, and will so remain as we seek to solve larger and larger coupled problems involving non-linear responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".