Software Development for Petrophysical Analysis of Shale and Tight Formations
Bibliographic record
Abstract
Abstract Shale and tight formations have long been a challenge for petrophysical interpretation. In the case of shales, the presence of clays and organic matter, complex mineralogy and pore structure make the log responses complicated. In tight reservoirs, the presence of connected and non-connected dissolution pores, microfractures and slot porosity also complicates the interpretations. This work seeks to integrate and digitize new petrophysical techniques and procedures that address these problems into a software system to assist with shale and tight reservoirs characterization. A petrophysics software system that includes dual and triple porosity models as well as elastic geomechanical properties has been developed to assist with the evaluation of shale and tight formations. Some critical petrophysical parameters can be quantified, such as matrix, fracture, non-connected and effective porosities, water saturation, total organic carbon, level of organic metamorphism, flow regimes (continuous vs. diffusion-like) at any pressure of interest, as well as Young modulus, Poisson’s ratio and minimum horizontal stress. Based on these estimates, detailed shale and tight reservoirs characteristics can be analyzed and the original hydrocarbons in place can be determined with good accuracy. Practical workflows for calculating each parameter are also organized and integrated. Object-oriented programming techniques are utilized for the development of this software considering its development life cycle for large-scale software development. Optimization capacity adopted in the current development for the reuse of the software components for future development is also explained. Two case studies using data from the Nikanassin formation in the Deep Basin of the Western Canada Sedimentary Basin (WCSB) and the Haynesville shale formation in Texas are presented to illustrate the software development and the application of the software. Conventional well log data, such as gamma ray, density, neutron, acoustic, resistivity, and cores and drill cuttings are utilized in the examples, which is further validated with other sources of information. It is concluded that the methodology developed in this software will prove valuable and facilitate the petrophysical evaluation of shale and tight formations.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".