CO2 Enhanced Oil Recovery And Geologic Storage: An Overview with Technology Assessment Based on Patents and Articles
Bibliographic record
Abstract
Abstract Contextualized overview of the CO2 EOR and its geologic storage, with critical evaluation of state-of-art and technological development through patents and scientific articles, focusing on annual evolution, technology owners (countries, companies, R&D institutions), inventors, annual evolution of the patents portifolia, field projects, company shared technology, IPC codes, technologic trends and fields, miscible and immiscible processes, capture technologies, relationships between the annual evolution of crude oil production, price, patent deposits and articles published, and technologic maturity of geologic storage. With the high impact on climatic changes, the energy industry is aiming to recover the planet climatic conditions by developing feasible processes. There are a reasonable number of field projects and are several technologic challenges are identified. The annual evolution of patents for CO2 EOR has the same trend as the other EOR methods, the deposits increase significantly near the petrol crises. The main technology owners are Texaco, Mobil, Chevron and Shell. In indexed articles, BP, Chevron and Shell are the companies that published more and University of Regina (Canada), is the academic leader. Most of the CO2 EOR field projects are in the US, being US, Canada and Norway pioneers in carbon sequestration. In the Latin America, Petrobras intends to act on all Carbon Capture and Storage chain. The inventors usually act in several technologic fields. Texaco, Mobil, Chevron, ConocoPhillips and Shell invested in alternated injection and surfactants addition. Shell made numeric simulation for miscible and immiscible fluids dislocation. ConocoPhillips studied CO2 correlations for miscibility pressures. University of Regina studied interfacial tension CO2-oil. University of Texas studies foams to change the injection profile. Over 90% of the patents are miscible processes. Patented capture technologies are adsorption, absorption, ionic liquids, and membranes, MOFs, among others. CO 2 − baixar o 2
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.029 | 0.021 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".