Elastic Anisotropy in Bakken Formation
Bibliographic record
Abstract
ABSTRACT: The first laboratory study describing elastic anisotropy of Bakken shale reservoir was reported almost three decades ago. Since then, several efforts have been made in this direction, with the most recent being in 2022 to characterize hydraulic fracture-driven interaction. Separately, a study reported the relationship between various anisotropic stiffness tensor components using published data. However, none of these studies address the variability observed between different formations, nor did they highlight static-dynamic inversion, crucial to 1D geomechanics modeling. This paper utilizes the data presented in the 2022 publication to advance current understanding of anisotropy for Bakken reservoir. First, we try to understand static mechanical property anisotropy observed in various formations. We also study stress-dependency of the observed anisotropy. We examine relationships between various anisotropic stiffness tensor components and reconcile with published data. Finally, we estimate Thomsen parameter for the formations studies and subsequently utilize that to build 1D geomechanics model for Bakken. Separately, we built another iteration of 1D geomechanics model using a different workflow. The results presented here improve our understanding of anisotropy in Bakken, as well as demonstrating two different ways to build 1D geomechanics model. 1. INTRODUCTION The Bakken and Three Forks formations cover a significant portion of North Dakota, South Dakota, and Montana in the United States; and Saskatchewan and Manitoba in Canada. Drilling activity since 2000 has been primarily focused on these two formations because of new advances in horizontal drilling technology. With these advances, the need for additional cores and data has enabled investigations into previous undrilled portions of the basin. Organic shales present in the Bakken and Three Forks formation, and other formations all over the world, are characterized by velocity anisotropy with lower velocity in the direction perpendicular to the lamination. Characterizing anisotropy is critical not only from the seismic attribute standpoint, but also for geomechanics modeling with application to frac design. While the seminal paper by Thomsen (1986) first mathematically described the observed anisotropy almost 40 years back, past decades have seen a number of publications aimed at characterizing anisotropy in Bakken formations via core-based measurement (Vernik and Nur, 1992; Guedez et al., 2018, and very recently, Merzoug et al., 2022). Guedez et al. (2018), for example, reviewed extensive literature data to establish relationship between different components of the anisotropic stiffness tensor. They were then applied to sonic data from a vertical well in the Bakken formation, in an effort to circumvent the uncertainty involved in using Stonely wave data (for C66 estimation). They then compared the predicted insitu horizontal stress using the relationship developed by them with that obtained using ANNIE and MANNIE models. Merzoug et al., 2022 (and Chellal et al., 2022), on the other hand, used core-based measurements targeted on Bakken and Three Forks formation to model insitu horizontal stress aimed at understanding fracture driven interaction.
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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".