Effects of fracture geometries on well production in hydraulic fractured tight oil reservoirs
Bibliographic record
Abstract
Tight oil production is emerging as an important new source of energy supply and has reversed a decline in US crude-oil production and western Canadian light-oil production. At present, the combination of the multistage hydraulic fracturing and horizontal wells has become a widely used technology in stimulating tight oil reservoirs. However, the ideal planar fractures used in the reservoir simulation are simplified excessively. Effects of some key fracture properties (e.g., fracture-geometry distributions and the permeability variations) are not usually taken into consideration during the simulation. Oversimplified fractures in the reservoir model may fail to represent the complex fractures in reality, leading to significant errors in forecasting the reservoir performance. In this paper, we examined the different fracture-geometry distributions and discussed the effects of geometry distribution on well production further. All fracture-geometry scenarios were confined by microseismic-mapping data. To make the result more reliable and relevant, a geomodel was first constructed for a tight oil block in Willesden Green oil field in Alberta, Canada. The simulation model was then generated on the basis of the geomodel and history matched to the production history of vertical production wells. A horizontal well was drilled in the simulation model, and different fracture-geometry scenarios were analyzed. Results indicated that the simulation results of simple planar fractures overestimated the oil rate and led to higher oil recoveries. In addition, if the secondary fracture can achieve the same permeability as the main fracture, a hydraulic fracture with branches can increase the well production (e.g., Scenario 2 under the conductivity ratio of 1:2) because of a larger effective contact area between matrix and fracture. Secondary fractures with low permeability can decrease the well productivity compared with wells with biwing planar fractures. Furthermore, the effect of hydraulic-fracture geometries on the cumulative production of the wells with higher main-fracture conductivity was more significant compared with those with lower main-fracture conductivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".