3D Geomechanical Modeling in the Complex Fracture Network of the Horn River Shale Using a Fully-Coupled Hybrid Hydraulic Fracture HHF Model: Permeability Evolution and Depletion
Bibliographic record
Abstract
Abstract The objective of this paper is to improve the evaluation and characterization of the fracture network as well as the production matching in the Horn River Shale of Canada. The task is carried out by extending the hybrid hydraulic fracture (HHF) model introduced by Urban et al. (2017) to a fully coupled fluid flow-geomechanical model that considers the far field stress stemming from the overburden, sideburden and underburden of the shale reservoir in an optimized simulation grid. The model evaluates the effects of depletion, of fracture closure and of permeability change using a discretized complex fracture network. In this paper, the fracture network is discretized using microseismic observations, when available. However, microseismic data may be limited in some of the fractured stages, or like in the case of most hydraulically fractured wells it might be non-existent. The fully coupled HHF model is developed to (1) improve the shale characterization and the simulation history matching, (2) study the fracture closure and permeability change in the fracture network due to gas production, and (3) alleviate microseismic data scarcity by generating a representative fracture network of those stages where microseismic data are unavailable. The stress change from the initial hydraulic fracturing is evaluated in nine paths multi-level horizontal wells that penetrated the Horn River Shale. The stress shadow is corroborated with microseismic observations and exhibited areas with high fracture density and productivity. The HHF model further evaluates the reservoir response to pore pressure depletion stemming from production, which leads to stress and permeability changes, fracture closure, and fracture reorientation. The procedure improves the simulation history matching by improving reservoir characterization, especially in stages closer to the toe where an understanding of fracture network geometry is problematic due to the cloud dispersion and scarcity of the microseismicity. The model also evaluates interference between well-paths and helps to determinate the optimum well, fracture and stage spacing. The HHF model was used to observe changes in volume, permeability and fracture connectivity in undepleted areas close to the fracture network. These areas reveal possible candidates for refracturing. A refracturing scenario that restores fracture conductivity and increases the drainage area of the fracture network is analyzed economically for evaluating the viability of that type of operation in the Horn River Shale. The HHF simulation model improves the shale reservoir understanding and simplifies the use of a highly complex fracture network for evaluating history matching, fracture closure and permeability changes during gas production. Furthermore, it provides a viable methodology to optimize well and stage spacing, and to evaluate potential refracturing candidates, where microseismic data is unavailable and a fracture network needs to be developed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".