Comparison of PKN, KGD, Pseudo3D, and Diffusivity Models for Hydraulic Fracturing of the Horn River Basin Shale Gas Formations Using Microseismic Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We present a comparison of three different hydraulic fracture models as well as an anisotropic diffusivity model with the observed microseismic data from shale gas reservoirs in the Horn River Basin of Canada. We investigated the validity of these models in the prediction of hydraulic fracture geometries using tempo-spatial extension of microseismic data. In the study area, ten horizontal wells were drilled and hydraulically fractured in multiple stages in the Muskwa, Otter Park, and Evie shale gas formations in 2013. The treatments were monitored by downhole microseismic measurements. We integrated microseismic analyses, geomechanical information extracted from well logs, and fracturing treatment parameters performed in the area. We compared fracture geometry predicted by Perkins-Kern-Nordgren (PKN), Khristianovic-Geertsma-de Klerk (KGD), and a Pseudo-3D (P3D) fracturing models as well as an anisotropic diffusivity model with actual fracture geometries derived from microseismic records in more than one hundred fracturing stages. For the study area, we find that there are no barriers to hydraulic fracture vertical growth between the Muskwa, Otter Park and Evie shales. Therefore, the fracture height to length ratio is higher than unity in many stages. Large fracturing heights suggest that the PKN model might be more suitable for fracture modeling than the KGD model. However, our analyses show that the fracture length predicted by the KGD model is closer to, but still far less than the fracture length illustrated by microseismic events. Pseudo 3D model also predicts fracture lengths which are slightly larger than the modeled fracture lengths by the KGD and PKN equations and still significantly smaller than the microseismic fracture lengths. These differences are observed throughout all stages suggesting that these methods are not able to perfectly predict the hydraulic fracturing behavior in the study wellpad. Vertical extension of microseismic data with linear patterns into the Keg River formation below the shale formations suggests the presence of natural fractures in the study area. This study presents a distinctive insight into the complex hydraulic fracture modeling of shales in the Horn River basin and suggests that diffusivity mapping is a simple, but powerful tool for hydraulic fracture modeling in these formations. Observed microseismic fracture lengths are significantly higher than lengths predicted by the geomechanical models and closer to diffusivity models, which suggests the possibility of increasing well-spacing in future development using diffusivity equation for improving treatment design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it