Integration of Microseismic Data, Fracture and Reservoir Simulation into the Development of Fractured Horizontal Wells in the Cardium Formation - A Tight Oil Case Study
Bibliographic record
Abstract
Abstract Multi-fractured horizontal wells have been used successfully to exploit tight gas and shale gas reservoirs in North America over the last decade. This technology has also been successfully implemented in tight oil reservoirs in recent years. Some of the prominent tight oil plays in Canada are the Cardium, Bakken and Viking formations. Higher oil prices and depleting conventional resources have challenged operators to exploit these tight oil resources. Some of the primary reservoir engineering challenges are the optimization of the fracture spacing along the length of a horizontal wellbore, and the spacing between the horizontal wells in a resource play. Three-dimensional reservoir simulation is the most reliable technique for reservoir modeling from these complex completions in permeability-challenged reservoirs. For an accurate representation, reservoir simulation requires data input from different sources to be incorporated into the model. In this study, microseismic data was integrated with a fracture-pumping operation to create a calibrated fracture model in a pseudo-3D fracture simulator. This fracture simulation model was subsequently imported into a multi-layer numerical reservoir model developed for the Cardium formation. The reservoir model was production matched using the fracture conductivities from the calibrated fracture model. The history-matched reservoir model was then used to understand production depletion in this tight oil reservoir. Sensitivity studies were conducted on the history-matched model for fracture and wellbore spacing optimization. An improvement in the recovery factor was shown when fracture spacing was reduced, and when wellbores were more closely spaced. The time to production interference between fractures and wellbores helps optimize the play. This paper presents the workflow (integrating microseismic and fracturing studies) and results of a 3D reservoir simulation study conducted on a fractured horizontal well in the Cardium tight oil formation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".