A Simulation Study of Effects of Operational Procedures in CO2 Flooding Projects for EOR and Sequestration
Bibliographic record
Abstract
Abstract This work focuses on production data integration into reservoir models to be used for numerical reservoir flow simulation of enhanced oil recovery (EOR) through application of Carbon dioxide (CO2) injection processes. CO2 flooding has been recognized widely as one of the most effective EOR technology for reducing greenhouse emissions while increasing the ultimate recovery of oil reservoirs. Production data integration into reservoir models is an inverse problem. A proper methodology to its solution requires a prior complete understanding of the analogous forward problem. The study of this forward problem is the target of this research work. Throughout its duration, reservoir simulations will be performed with a compositional simulator focusing on the investigation of the macroscopic mechanisms of CO2 injection processes. Operational parameters such as the injector pressure and perforation locations, as well as different production schemes will be investigated to determine the relationship of observed recovery against the amount of CO2 sequestered. Introduction The use of CO2 injection in enhanced oil recovery is by no means a new technology; it has been utilized and reinvestigated for decades. Beginning in the 60s and 70s, the use of CO2 injection in place of methane was studied and found to be preferable in recovery results, obtaining miscibility, as well as simpler factors such as cost. Initially, the injection of CO2 was considered only for the oil recovery potential. In recent years, with growing environmental concern over CO2 emissions, the suggestion that CO2 injection into subsurface formations as a method of sequestration has become widely regarded as a feasible solution to slow the progression of global warming. This sequestration has been suggested in three main areas: injection into aquifers and other non-hydrocarbon porous formations, injection into depleted gas reservoirs or other depleted pools, and injection into oil reservoirs for the dual purposes of gas storage and oil recovery. While CO2 injection for enhanced recovery is regarded as having the lowest potential for storage1, it will likely be the most accepted due to its potential to off-set the costs of injection through increased oil production. A great deal of study has been done in various topics surrounding the consideration of CO2 injection, and a literature review done prior to this work followed the progression of research and testing to better the understanding and use of this EOR technology. Early study focused on the contrast between miscible and immiscible displacement, and through laboratory tests the recovery potential of miscible flooding was explored. The results of such experimentation have been largely successful, and this optimism has perpetuated study in CO2 miscible flooding. This work focused on the operational parameters of a miscible flooding scheme, specifically investigating variations in injection pressure and use of alternating injected fluids. The intention was to improve tertiary recovery while maximizing the CO2 sequestration potential. Literature Review For many decades, a method of gas injection for displacement has been used in improving oil recovery. Initial methods often involved methane, however over time, other alternatives such as CO2 were considered. In 1971, Rathmell, Stalkup, and Hassinger2 investigated CO2 miscible displacement in the laboratory setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".