Upscaling of Kinetic Parameters for Simulation of Reactive In Situ Bitumen Recovery
Bibliographic record
Abstract
Abstract Successful simulation of bitumen recovery processes such as in situ combustion or reactive gravity drainage at the Alberta Ingenuity Centre for In Situ Energy (AICISE) would require detailed knowledge of the kinetic parameters for the chemical reactions involved. It is known that the direct use of laboratory-obtained kinetic data for modeling of reactive systems in petroleum reservoirs often introduces error. It is therefore necessary to establish the scale dependency of reaction constants for field-scale simulation of reactive recovery processes. Although case-specific techniques for definition of reaction parameters in reservoir simulation applications have been proposed, a general framework for upscaling of reaction kinetics is not well established. We applied volume averaging technique to establish the relationship between upscaled reaction parameters and the grid block length scale and other system parameters. A case study involving simulation of in situ combustion with different grid block sizes is discussed where the upscaled kinetic parameters are determined through direct matching of fine grid and course grid solutions, followed by a proper extrapolation to field-scale gird block sizes. Introduction Modeling of transport phenomena and chemical reaction in porous media often requires scaling up the process from the micro (pore) scale to the macro (continuum) scale. This "upscaling" would make it possible to develop workable and effective models which would not require detailed knowledge of complex pore space and geometry within the porous medium. Volume averaging and homogenization are the main upscaling techniques used. The concept of upscaling discussed in this paper is related to that implemented by the volume averaging technique, although the goal is not to develop macroscale transport equations. Rather, the objective is to modify the reaction kinetics measured in the laboratory so a field-scale reservoir simulation could be performed. This upscaling is necessary because the direct use of laboratory-obtained knowledge in modeling of reactive systems in natural environments often introduces errors. For example, chemical reaction rates are usually measured in well-mixed lab systems designed to eliminate mass transfer limitations. However, in natural porous media such as petroleum reservoirs, reactions occur in individual pores with various physical and chemical properties. Heterogeneities of such systems can produce mass transport limitations and result in spatial variations in concentration, affecting the overall reaction rates. Equally important is the question of how to select a grid block size that provides reliable results when simulating chemical reactions in petroleum reservoirs. As an example, consider a grid block of 100 m which includes a 10-meter long reaction zone. The concentration changes in the reaction zone will be much larger than that happening in the rest of grid block where only diffusion or convection is active. For numerical solution with a finite difference scheme, the entire grid block will be assigned an averaged value of species' concentration. This average concentration, based on which the reaction rate is calculated, depends on the size of grid block which makes the simulation results highly dependant on the length scale. It is therefore necessary to establish the scale dependency of reaction rates for field-scale simulation of relevant processes in petroleum reservoirs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".