The First Integrated Approach for CO2 Capture and Enhanced Oil Recovery in China
Bibliographic record
Abstract
Abstract As the only company which owns the right for coal mines and oil and gas production in China, Yanchang Petroleum Group has the unique advantages to implement integrated CO2 capture and enhanced oil recovery (EOR) in Ordos Basin. This area is also one of the largest CO2 emission areas in China. The coal to chemicals plant was built to efficiently co-utilize coal, oil and natural gas. The energy efficiency is about 8.9% higher than the world average level. Two corresponding CO2 capture plants were built with the capacity of 50,000 and 360,000 tonnes per year. The cost for CO2 capture is as low as $17.5/tonne, much cheaper than most of the other CO2 capture project in the world. By optimizing the distance between CO2 capture plants and EOR sites, the shortest distance, the shortest distance for CO2 transportation is only 10 kilometers. It is estimated that the cost for CO2 transportation is $2.58/tonne. Meanwhile, the CO2 is used for enhanced oil recovery in Yanchang oil fields. Extensive research has been done to investigate the suitable geological conditions for CO2-EOR. Experiments have also been conducted to study the behaviors of CO2-crude oil mixture. Two pilot tests including Qiaojiawa 203 block and Wuqi Yougou are now in operation with well production being doubled or tripled. In addition, more than 87% of reservoirs in Yanchang oil field in Ordos Basin are suitable for CO2-EOR with estimated billions of CO2 storage capacity. Introduction Greenhouse gas emissions are regarded as one of the most important factors resulting in global warming and climate change. In all the greenhouse gases, the proportion of carbon dioxide (CO2) emitted is the greatest and around 76%, according to the statistics from the Intergovernmental Panel on Climate Change (IPCC) in 2013. The CO2 emissions are mainly from the consumption of fossil fuels such as coal, oil and natural gas which provide 85% of worldwide energy needs for human activities (BP, 2017). While in these CO2 sources from energy consumptions, the burning of coal produces more CO2 than oil or natural gas at the same equivalent electricity generated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".