Best Practices in DFIT Interpretation - Comparative Analysis of 83 DFITs in the Canadian Duvernay Shale Play
Bibliographic record
Abstract
Abstract In September 2021, the Alberta Energy Regulator (AER) through a new pressure and deliverability testing directive issued new guidance for minifrac tests, also known as diagnostic fracture injection tests, to align with the current practice for conducting these tests. This paper statistically summarizes results from 83 of these DFITs, submitted by many operators from the Canadian Duvernay shale play. The main parameters analyzed were closure, reservoir pressure and permeability. This newly updated directive sets out requirements for pressure and deliverability tests. In the development of tight or unconventional reservoirs, industry moved towards horizontal wells with multistage fracture treatments using a minifrac (also referred to as DFIT or diagnostic fracture injection test), which became the more common well test in determining closure, initial reservoir pressure and permeability. In this paper, a comparison of holistic vs compliance methods descriptions for closure pressure are provided. Complete governing equations for after closure analysis methods are described in detail to permit readers to replicate all results on reservoir pressure and permeability. For closure pressure, the compliance model is compared to the holistic model that is published or commercially available. Comparisons are also provided for After Closure Analysis (ACA) models including the Soliman and Nolte methods as far as reservoir pressure and permeability are concerned. 83 field case studies are presented for horizontal wells in an unconventional shale play. The most significant findings are 1) a compliance closure pressure signature is not apparent in the analyzed DFITs, 2) closure pressure estimates, and outcomes are similar for the compliance and holistic methods 3) reservoir pressure determination differentiation using either linear or radial flow 4) PVT impact on interpretation and 5) order of magnitude difference for permeability determination on After Closure Analysis methods. The findings have direct practical implications for operators in the Canadian Duvernay shale play and analogous shale plays in USA and elsewhere. Accurate permeability estimates are needed for calculating effective fracture length and for optimizing well spacing and fracture design. Accurate closure pressure is fundamental to hydraulic fracture design and other geomechanics applications. Accurate initial reservoir pressure is important because it could be used for input for Rate Transient Analysis (RTA) for resources / reserves assessments in similar unconventional plays. The novelty of the comparative analysis is in the ability to show in unconventional shale plays how closure pressure methods compared, and the implications of using different after closure analysis methods which could be of significant benefit to a practicing engineer or well testing interpreter
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".