Back to the Future: Shale 2.0 - Returning Back to Engineering and Modelling Hydraulic Fractures in Unconventionals With New Seismic to Stimulation Workflows
Bibliographic record
Abstract
Abstract Stimulating Shale Gas Wells has become a mundane activity with very little or no engineering. The industry has focused heavily on reducing costs and increasing efficiencies of operations that there is seldom any time for engineering. The lack of any horizontal logging information, assumptions that rock quality does not change have led to excel driven spreadsheets doing glorified mass balances which are considered as the fracture designs of today. In addition to this the same fracture treatment is pumped stage after stage well after well. Needless to say the industry's lack of ability to model these complex fractures has also contributed to the exercise of moving away from fundamental fracture design. This trend has resulted in productivities of wells being all over the place that mostly are unexplained. The industry is beginning to realize that a significant % of the wells drilled in unconventionals are not profitable. Refracturing is also gaining prominence because of a single important factor that primary initial completions are ineffective. Shale 2.0 is all about integrating seismic to stimulation information to provide better answers and ultimately better productivity via simple measurements in the lateral. These measurements are ultimately used to engineer the completion, design and understand the science behind fracturing than just merely pumping the job. This paper details the planning, design and evaluation processes in the application of a new workflow called the Unconventional Reservoir Optimized Completion workflow. This revolutionary Seismic to Stimulation workflow demonstrates with examples how we have migrated, a dominant well centric process to a reservoir centric process. A significant step change in fracture modelling has been applied using unconventional fracture models which have the ability to model complex fractures using discrete fracture networks. These models can be validated using microseismic and when calibrated with production can become a powerful prediction tool. Experiences and lessons learned in the Canadian Montney will be presented.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".