Use of a Variable Shape Distribution (VSD) Model to Populate Reservoir Properties in Tight Fractured Reservoirs for Numerical 3D Modeling
Bibliographic record
Abstract
Abstract The importance of unconventional resources is increasing every day. In Canada, unconventional gas accounts for an estimated 34% of the total gas production. In the United States the estimate is 54%. And we anticipate that the contribution of unconventional resources throughout the world will become significant in decades to come. Most unconventional reservoirs are naturally fractured and also need to be hydraulically fractured to attain commercial production. Different authors have concluded that both, natural and hydraulically induced fractures make these reservoirs stress-sensitive causing various problems for modeling, such as poor history match and inaccurate forecasting. The solution to this problem is coupling the reservoir model with a geomechanical model, to take into account the changes in porosity and permeability due to changes in stresses during the life of the reservoir. But inputting natural fracture data accurately in the simulator at different scales is challenging. Thus the objective of this study is the use of a variable shape distribution (VSD) model, which has never been utilized in the past in reservoir simulation, to build a more rigorous static model with a view to improve history matching, production forecasting, and modeling of tight fractured reservoirs. While other statistical models are not capable of fitting the whole scale spectrum of fracture properties without truncating the data, the VSD fits the complete set of non-truncated fracture data with a coefficient of determination (R2) of at least 0.97. This improves reservoir characterization and geostatistical modeling. Although application of the method concentrates only on a tight gas formation of the Western Canada Sedimentary Basin (WCSB) the workflow is presented in detail so that it can be reproduced in other tight naturally fractured reservoirs around the world. It is concluded that the proposed methodology represents an improvement over previous approaches as the complete distribution of matrix and fracture properties, from very small to very large scales, is taken into account without any truncations. Results lead to proposals for drilling horizontal wells in areas of more intense natural fracturing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".