Estimation of Oil Recovery and CO2 Storage Capacity in CO2 EOR Incorporating the Effect of Underlying Aquifers
Bibliographic record
Abstract
Abstract Atmospheric concentrations of CO2 have risen since the beginning of the industrial revolution, primarily as a consequence of fossil fuel combustion for energy production and other industrial activities. Recognizing the challenge imposed by the potential for climate change, recent initiatives by various governments and by energy producers target a significant reduction in the intensity of CO2 emissions into the atmosphere. A major mitigation strategy for reducing the intensity and amount of CO2 emissions into the atmosphere is CO2 capture and sequestration, of which geological sequestration is a major component. Although enhanced oil recovery operations have the lowest capacity of all options for geological CO2 sequestration, they are most likely to be implemented first because of the additional economic benefit that will help offset the cost of CO2 sequestration. Assuming that the pore space previously occupied by the produced oil can be backfilled with CO2, a methodology has been developed for the identification and screening of oil reservoirs that are suitable for CO2 flooding and for estimating their CO2 sequestration capacity at depletion, as well as under enhanced oil recovery. The methodology has been applied to close to 11,000 oil pools in the Western Canada Sedimentary Basin that are recorded in provincial reserves databases. Of these, 4,767 oil pools are technically suitable for CO2 flooding, with an estimated incremental oil production and total CO2 sequestration capacity of 350×106 m3 (2,200 MMbbl) and 988 Mt CO2, respectively. However, only 110 oil pools have individual CO2 sequestration capacity greater than 1 Mt CO2 each, but together they account for ~61% of the total. The incremental oil production from these 110 oil pools is estimated to be 150×106 m3 (930 MMbbl) oil, and these oil pools should be considered first in detailed studies of CO2 EOR and sequestration. To account for the effect of underlying aquifer influx that reduces CO2 storage capacity, analysis of the production history of these 110 oil pools shows that the water-oil and gasoil ratios are indicative of the strength of the underlying aquifers, but the recovery factor is not. The underlying aquifer is considered strong if cumulative net WOR>0.25, and weak if WOR<0.15. For WOR between 0.15 and 0.25, strong aquifer support is indicated by cumulative GOR<1,000 m3/m3 (5,600 scf/bbl), otherwise the aquifer support is weak. Material balance analysis on 19 of these oil pools with active aquifers indicated that, if the reservoir pressure is only allowed to increase back to the initial pressure, the CO2 sequestration capacity is reduced on average only by ~3%, if the underlying aquifer is weak, and by ~50% if the underlying aquifer is strong.
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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 | 0.001 |
| 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) | 0.001 | 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".