Steam Alternating Solvent Process: Lab Test and Simulation
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Bibliographic record
Abstract
Abstract A new heavy oil recovery process, the Steam Alternating Solvent (SAS) process, is studied by lab experiments and corresponding numerical simulation. The SAS process involves injecting steam and solvent alternately, using well configurations similar to those in the SAGD process. This process is designed to combine the advantages of the SAGD and VAPEX processes to minimize the energy input in heavy oil and bitumen recovery. Lab experiments were conducted using a 2D high-pressure/ high-temperature model. One baseline SAGD test and one SAS test were performed using an oil sample from Burnt Lake. A mixture of propane and methane was used as the solvent in the SAS test. The results showed that the energy input in the SAS process was 47% lower than that of the SAGD process for recovering the same amount of oil. The post-run analysis revealed that asphaltene precipitation occurred in the porous medium. Numerical history matching of the test data using Computer Modelling Group's STARS reservoir simulator captured the main features of the process. Introduction The main obstacle to producing oil from the large deposits of heavy oil and bitumen resources in northern Alberta is the high viscosity of these oils, usually over 10,000 mPa's at reservoir conditions. There are generally two types of methods for the reduction of oil viscosity. The first is to increase oil temperature by injecting a hot fluid, such as steam, into the reservoir, or by in situ combustion through the injection of oxygen-containing gas. The second method is to dilute the viscous oil by injecting low viscosity hydrocarbons (solvent). As the solvent dissolves and mixes with the viscous oil, the lower viscosity solvent-diluted oil can then be recovered. Two processes, Steam Assisted Gravity Drainage (SAGD) and Vapour Extraction (VAPEX), have been developed for the recovery of heavy oil and bitumen resources(1–3) based on the combination of the above viscosity reduction methods and horizontal well technology. The first has been successfully tested in the field and is moving to commercial scale application(4, 5). The second is presently in the initial field-testing stage(6). The advantage of the SAGD process is its relatively higher oil production rate. However, the higher production rate is associated with significant energy requirements, CO2 generation, and costly water treatment. The VAPEX process has the advantage of lower energy consumption, therefore, less CO2 generation. The major predicted drawback of the VAPEX process, however, is its relatively lower oil production rate. In the past several years, modifications, such as ES-SAGD(7) and SAGP(8), have been proposed to improve SAGD's energy efficiency. In the ES-SAGD process, a small amount of solvent with a boiling temperature matching the steam temperature is coinjected with steam to increase the oil production rate. In the SAGP process, non-condensable gas is co-injected with steam for the purpose of reducing heat loss to the overburden. Recent studies(9, 10) have indicated that the economics of a SAGD project are more sensitive to the energy consumption per unit of oil production than to the oil production rate.
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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 | 0.002 | 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 it