Polymer Flood Application to Improve Heavy Oil Recovery at East Bodo
Bibliographic record
Abstract
Abstract The East Bodo, Lloydminster SS heavy oil pool has been exploited using primary recovery and waterflood. IOR screening showed that a polymer flood would be a preferred IOR technique. Subsequent coreflood tests indicated that the polymer flood could recover 20% OOIP incremental oil, after waterflooding, to a 95% water cut. Data gathered from the coreflood was used to fine tune the reservoir simulation model to help design the pilot and predict potential economic reserve capture for a commercial field-wide polymer flood. Subsequently, a pilot was initiated. During the pilot operation, achieving the target polymer viscosity, dependant on water quality, proved to be a significant challenge. Early field response is being observed through an increase in injection pressure, reduced water cut and polymer breakthrough. Further positive response of this polymer pilot allows for the expansion of the polymer flood technology to other parts of this reservoir; some with bottomwater and gas cap. This paper reviews the progress of the East Bodo polymer flood, from laboratory concept to working field application, in four major steps:IOR screening using simulations and coreflooding,field pilot design/implementation,pilot performance, andnext steps. Introduction Pengrowth has targeted East Bodo (Alberta side) and Cosine (Saskatchewan side) for waterflood optimization and subsequent enhanced oil recovery applications. Currently, the most practical EOR technology for this heavy oil reservoir seems to be the polymer flood technology in combination with horizontal wells. Several investigators(1–4) have demonstrated the potential of the polymer flood technology for improved oil recovery in heavy oil reservoirs. The East Bodo/Cosine Reservoir produces from the Lloydminster Formation, which is part of the Lower Cretaceous Mannville Group. Pengrowth provided some of the reservoir characteristics, as summarized in Table 1. This particular reservoir is separated into two parallel lobes trending North/West to South/East. To complicate matters, local gas caps are found primarily on the Saskatchewan side of the reservoir. Thus, the current waterflood patterns are located on the Alberta side. In the future, optimized waterflood and EOR schemes need to include those parts of the reservoir which are overlain by gas caps or influenced by bottomwater. A plan of progression aligned with the priorities of Pengrowth was laid out as follows:Optimize existing waterflood;Step out waterflood into limited gas cap areas;Then, target areas with a more extensive gas cap;Determine enhanced waterflood potential, for instance polymer flood; andArrange well patterns to benefit both waterflood and subsequent EOR process. IOR Screening Several IOR technologies were considered for application in the East Bodo Field. What follows is a list of IOR processes that were initially considered, but screened out after technical or economical issues could not be overcome.Thermal Recovery: Pay is too thin - heat loss to overburden is too large; oil not viscous enough to form a stable steam chamber; fireflood has potential, but a previous pilot on a neighbouring McLaren pool yielded poor results.
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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 | 0.000 |
| 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) | 0.002 | 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".