Numerical and Experimental Modelling of the Steam Assisted Gravity Drainage (SAGD)
Bibliographic record
Abstract
Abstract For complex petroleum recovery processes, an experimental investigation isusually performed with a numerical simulation to study the recoverymechanism(s). In this paper, both physical and numerical simulations of thesteam assisted gravity drainage (SAGD) process were performed. One of theobjectives of the numerical investigation was to determine the match betweenumerical results with data generated from scaled model experiments. The Computer Modelling Group's (CMG) STARS? thermal simulator was used. Resultsfrom the numerical simulation were found to be in reasonable agreement withthose obtained from the experiments for oil production rates, and cumulativeoil production. In addition, the steam chamber volume and temperaturedistribution were also examined. ffects of different parameters, such as steaminjection pressure, vertical separation between injection and production wells, nd reservoir thickness, on the performance of the SAGD process ereinvestigated. They were observed to have the same effects on both experimentaland numerical results. The numerical simulator was also used to study theinfluence of rock and fluid properties, such as oil viscosity, permeability, porosity, and the mount of heat loss from the reservoir to thesurroundings. Introduction The steam assisted gravity drainage (SAGD) process was developed by Butler(1), and is illustrated in Figure 1. It has been applied inseveral projects, including the Underground Test Facility (UTF) and has shownpromise of achieving high recovery (more than 50 % of OOIP in some cases). Many experimental and numerical studies of the SAGD process have been carriedout over the last ten years, on different aspects of the process. One of therecent numerical studies was presented by Chow and Butler(2). Theyfocused on history matching the oil recovery and the steam temperatureinterface position with those observed in the SAGD experiments by Chung and Butler(3). In the present study, numerical history matching of the experimental data, suchas the oil production and the steam chamber temperature contours [Sasaki etal.(4)] is the main focus. Furthermore, time to establish initialcommunication between the two steam injection and production wells (steambreakthrough time) was investigated. The physical and operational conditions inthe experimental study were different, compared to those used in Chung and Butler's experiments(3). They included a pressure drop of?Pi = 20 kPa, permeability of k =142 D; no pre-heating was employed.The experiments were configured to examine phenomena associated with the risingchamber. More details are provided in the following, for both experimentalinvestigation and numerical simulation. Description of the Experimental Model Several 2D visual, scaled physical models were used in the experiments. Theywere designed to represent a vertical section of a heavy oil reservoir. Themodels had sidewalls of acrylic resin (of 20 mm in thickness).
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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 | 0.001 | 0.001 |
| 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".