Successful Fracture Stimulation in the First Joint Appraisal Shale Gas Project in China
Bibliographic record
Abstract
Abstract This paper discusses fracture stimulation in the first joint venture shale gas project with foreign companies in China. Shell China Exploration and Production Company (SCEPCO) is jointly appraising the shale gas play with partner PetroChina. The block is in Sichuan, China. The target zone is Longmaxi hot shale, a Silurian formation. Its matrix permeability is extremely low, in the range of 100–300 nano-Darcy but rich in natural fractures. Hydraulic fracturing has been proven a key to enhance the production by effectively connecting natural fractures and providing a path for the gas to flow into the wellbore. "Every shale reservoir is different." The joint working team is facing specific challenges in this play:Understanding of reservoir based on the study of geology, petrophysic, geomechanics.High wellhead treating pressure due to high formation stress and pore pressure.Deep wells - some deeper than 3,500m TVD.Fluid system and proppant type and size selection.Fit for purpose treatment size and pump program.Connection between wellbore and formation through the fracture.Horizontal wells - Stimulation interval selection, stage spacing, perforating strategy.Unknown fracture geometry - only 1 microseismic was applied in a horizontal well. Two vertical wells and three horizontal wells have been fracture-stimulated to date. The team has gained valuable experience and made significant improvement step-by-step and well-by-well. This paper discusses how a collaborative approach was applied to the completion of the shale gas wells during appraisal. Initial production test results of the wells have been promising. This is a significant step to unlock the potential of shale gas resources in China and help meet the country's energy needs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".