Performance Overview and Current Status of Heavy-Oil Polymer Floods in Saskatchewan Canada: Opportunities
Bibliographic record
Abstract
Abstract As the global upstream petroleum industry mulls over the ramifications of social license as it relates to the energy transition, there are concerns on future oil supply; at least, in the short- and medium-term. The province of Saskatchewan, in Canada, is noted for fostering innovation and testing of technologies for optimizing oil recovery; thus, can play a key role in meeting future petroleum demands. In the Plan for Growth released by the Government of Saskatchewan in 2019, three of the 30 provincial goals are streamlined to support the upstream oil and gas industry; including, but not limited to, increasing oil production by 25 percent to 600, 000 barrels of oil per day, enhance oil recovery, and position Saskatchewan as the best place in North America to test, commercialize and scale new oil and gas technologies. Due to significant remaining oil-in-place (OIP) in thin-pay heavy-oil pools and miscellaneous pools in Saskatchewan that are not amenable to thermal enhanced oil recovery (EOR) processes such as steam-assisted gravity drainage (SAGD), ease of modification of existing waterfloods and, given the high costs associated with replenishing dwindling petroleum reserves through new exploration efforts, polymer flooding presents an opportunity for reserves production in marginally-producing mature thin-pay heavy-oil plays. Heavy oil in Saskatchewan is produced mainly from the Lower-Cretaceous Mannville and Devonian-Mississippian formations of the Lloydminster and Kindersley Districts. As of year-end 2022, estimated heavy oil in place is about 6 billion cubic meters (6 × 109 m3). Primary recovery factors are generally less than 10 percent (%) of oil originally-in-place (OOIP), leaving more than 90 % of OIP available for secondary recovery or EOR. Secondary recovery, mainly waterfloods, have been widely implemented in some of these reservoirs to increase recovery but with incidental high watercut(s). Most of the heavy-oil reserve is exploited using thermal EOR methods, particularly cyclic steam stimulation (CSS) and SAGD. But thermal methods are not always applicable in thin-pay reservoirs. So, polymer flooding has been applied with the aim of increasing oil recovery while reducing watercut in waterflood pools where adverse mobility ratios result in poor waterflood performance or in thin-pay reservoirs wherein heat loss will make thermal recovery uneconomic. A summary of the performance of all heavy-oil polymer flood projects (16 in total) in Saskatchewan is presented. Information on all commercial-scale polymer flood projects (including pilot projects) in Saskatchewan was retrieved from publicly available applications, reports and other non-confidential data submitted to Saskatchewan's Ministry of Energy and Resources (ER). To analyze their individual performance, plots of instantaneous- and cumulative- produced water/oil ratio (WOR) versus cumulative oil produced (Np) are generated based on reported field injection and production data. The inventory was compiled into a Microsoft® Excel® spreadsheet and organized by pertinent characteristics such as geology, pool, formation, reservoir rock and fluid properties, injection (water and and/or polymer) start date(s), estimated OIP prior to commencement of the polymer flood, cumulative oil production, total recovery factor (RF) prior to- and following- implementation of the polymer flood project. The target formations (and lithology for each pool were included because of the importance of geology on oil recovery, and to help in future screening of applicable candidate pools for polymer flooding. Performance metrics such as WOR, incremental fluid production and RF can serve as useful guides in planning similar future projects in analogous reservoirs, benchmarking simulation studies, and in the selection of surface facilities and fluid handling equipment. Reservoir engineering and operational factors leading to observed trends are highlighted. Opportunities to extend the useful economic life of mature oilfields, marginally producing pools and suspended assets that may otherwise become liabilities are highlighted. Remaining oil-in-place in selected stratigraphic units is highlighted with a focus on future potential in terms of opportunities for reservoir re-characterization, conformance control and integration of hybrid recovery technologies for improved project economics. Expansion of polymer flooding to suitable analog reservoirs can contribute to reserves addition and provide shared economic benefits for both industry and the public.
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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 | 0.001 |
| 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".