Bibliographic record
Abstract
Abstract Approximately 80% of the Canadian Oilsands are too deep to be economically mined. SAGD - an in situ recovery technology has come of age and is emerging as the technology of choice in exploitation of these resources. The current major challenge that SAGD faces is the use of expensive heat to generate steam. The authors have previously described an improvement to SAGD - Solvent Aided Process (SAP) that aims to combine the benefits of using steam with solvents. In SAP, a small amount of hydrocarbon solvent is introduced as an additive to the injected steam during SAGD. SAP holds the promise to significantly improve the energy efficiency of SAGD thus reducing the heat requirement. This paper describes field testing of SAP at Encana's Christina Lake SAGD Project. In addition to dwelling on some of the important parameters of a SAP test, it outlines the design considerations for the pilot and associated facility modifications. The design duration of the experiment calls for an assessment of reservoir performance on a long-term basis. However, some preliminary observation and indications are discussed. Additionally impact of (a) timing of solvent initiation and (b) the well pair spacing on process performance is also explored based on modeling exercises. Introduction In SAGD, oil viscosity is reduced by heating with steam1,2. In SAP3,4,5, solvent dilution is also taken advantage of to aid this viscosity reduction. The result is enhanced rate of oil production and recovery leading to superior economics with lower energy intensity and impact on environment. In the context of doing away with the heating requirement, VAPEX - a process similar to SAGD but employing only hydrocarbon vapor instead of steam has been described in literature6,7,8,9, however, its development is awaiting a successful field trial. Use of solvent with steam for oil recovery is also discussed in literature10,11,12,13 with a focus on enhancement of steam displacement or steam stimulation. Using solvent with steam in SAGD context offers some practical advantages. The pressure in the vapor chamber does not need to be supported by a non-condensable as required in some versions of VAPEX. This means that the progression of the vapor chamber in SAP does not get overwhelmed by the heat/mass transfer resistance at the vapor/oil interface. Recently others14,15 have also discussed benefits of using solvents with SAGD in a process similar to SAP. Reference 14,15, advocate use of those solvents that match the condensation characteristics of steam at the operating conditions. Previous description3,4,5 and data, does not suggest such requirements for SAP. Encana has been developing SAP since 1996 and piloted the process first at its Senlac Thermal Project in 2002 and encouraged by the results is presently testing SAP for in situ bitumen extraction at its Christina Lake Thermal Project. In Senlac SAP Pilot, some description of which has been given previously5, solvent (butane) was co-injected in a well pair which was already in SAGD operation. Judging by the production rates at the time of SAP start, the steam chamber had risen to the top of the reservoir already for a few months.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".