China’s Unconventional Challenge Spurs New Thinking on Shale and Tight Reservoirs
Bibliographic record
Abstract
Despite possessing some of the world’s largest shale-gas resources, China is likely in 2020 to have produced less than half of the 30 Bcm per year in shale gas that the government set as a goal in its latest Five-Year Plan. While such a small volume may make shale production seem inconsequential to China’s overall energy balance, it is clear that when it comes to developing unconventional hydrocarbons, China is playing a long game. With regard to shale alone, a 2013 US Energy Information Administration study noted that China has the world’s second-largest technically recoverable shale-gas resources at an estimated 1,115 Tcf; the US is first with 1,161 Tcf. Even more to the point, China is one of only four countries (including the US, Canada, and Argentina) that produce commercial volumes of both shale gas and of tight oil. But it is the lack of efficient technologies and infrastructure that stand in the way of China besting the US and creating its own “shale revolution.” China’s most attractive reserves occur in remote, mountainous areas where, in some cases, shale resources can lie as deep as 3500 m. In separate papers presented in October during the 2020 SPE Russian Petroleum Technology Conference, the China National Petroleum Company (CNPC) detailed new technologies it is applying to meet some of these challenges. Paper SPE 202066, coauthored by subsidiaries of CNPC, Downhole Service Company and CCDC Petroleum Drilling & Technology Company Ltd., details the application of enhanced-hydraulic- fracturing technology (EHFT) to raise the effective stimulated reservoir volume (SRV) in the Sichuan shale basin. A second paper (SPE 202062), coauthored by CNPC and Halliburton, offers a case study in tight-oil production in Daqing employing an intensive fracture-cluster-completion strategy using a microemulsion flowback technology. The Spice in Sichuan Shale China boasts three shale basins (Sichuan, Tarim, and Yantze), but its principal development focus is in the southwestern province of Sichuan, which holds half of the country’s shale reserves. In developing fields such as Weiyuan, Changning, and Jiaoshiba, producers target the Ordovician Wufeng-Silurian Longmaxi formation. The total proved geological reserves of these three gas fields exceeds 500 Bcm, the authors noted in their paper. To develop infrastructure supporting industrial-scale operations and to introduce and test new technologies to raise shale output, China has established several national pilot demonstration areas. One of those is the Weiyuan national shale demonstration area in south Sichuan, where the authors quote an annual production of 2.5 Bcm. Staged horizontal fracturing is the main technology used at Weiyuan and other Chinese shale fields as producers strive to expand the fracture extension area, increase the reconstruction volume, and improve the productivity of single wells. An analysis of production data from Weiyuan showed, however, that the long-term conductivity of fractures is limited because the length and height of supporting fractures are short. Thus, because of the limited volume of reconstruction, production decreases rapidly and efficiency suffers as pressure declines.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".