Will Carbon Dioxide Injection in Shale Reservoirs Produce from the Shale Matrix, Natural Fractures, or Hydraulic Fractures?
Bibliographic record
Abstract
Abstract Enhanced oil recovery (EOR) in shale reservoirs has been recently shown to increase oil recovery significantly from this unconventional oil and gas source. One of the most studied EOR methods in shale reservoirs is gas injection, with a focus on carbon Dioxide (CO2) mainly due to the ability to both enhance oil recovery and store the CO2 in the formation. Even though several shale plays have reported an increase in oil recovery using CO2 injection, in some cases this method failed severely. This research attempts to investigate the ability of the CO2 to mobilize crude oil from the three most prominent features in the shale reservoirs, including shale matrix, natural fractures, and hydraulically induced fracture. Shale cores with dimensions of 1 inch in diameter and approximately 1.5 inch in length were used in all experiments. The impact of CO2 soaking time and soaking pressure on the oil recovery were studied. The cores were analyzed to understand how and where the CO2 flowed inside the cores and which prominent feature resulted in the increase in oil recovery. Also, a pre-fractured core was used to run an experiment in order to understand the oil recovery potential from fractured reservoirs. Results showed that oil recovery occurred from the shale matrix, stimulation of natural fractures by the CO2, and from the hydraulic fractures with a large volume coming from the stimulated natural fractures. By understanding where the CO2 will most likely be most productive, proper design of the CO2 EOR in shale can be done in order to maximize recovery and avoid complications during injection and production which may lead to severe operational problems.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".