Using the SPE/WPC/AAPG/SPEE/SEG PRMS To Evaluate Unconventional Resources
Why this work is in the frame
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Bibliographic record
Abstract
Summary It is the intention of the SPE/World Petroleum Council (WPC)/ American Association of Petroleum Geologists (AAPG)/ Society of Petroleum Evaluation Engineers (SPEE)/ Society of Exploration Geophysicists (SEG) Petroleum Resources Management System (PRMS) to provide a consistent approach to estimating petroleum quantities, evaluating development projects, and presenting results within a comprehensive classification framework. The reserves and resources definitions and application guidelines are designed to be applicable to both conventional and unconventional petroleum accumulations, regardless of their in-place characteristics, the extraction method applied, or the degree of processing required to yield a marketable product. The fact that unconventional resources are usually pervasive throughout a large area and are not significantly affected by hydrodynamic influences may require different approaches in evaluation. Assessments may include an increased sampling density to define uncertainty of in-place volumes and the variations in quality of reservoir and of hydrocarbons and their detailed spatial distribution for the design of specialized extraction methods. This paper summarizes the special problems in the estimation and evaluation of shale gas. However, similar procedures can be used for other unconventional resources. The material is largely drawn from the recently published SPE Application Guidelines to the PRMS, supplemented with illustrations from actual field examples. The rapidly advancing exploitation of unconventional resources has opened up many development opportunities, especially in North America. Shale gas and bitumen have already caused major impact on energy supply. We anticipate these opportunities will expand rapidly throughout the world. Achieving a better understanding of the special problems in unconventional-resources evaluation will help us build on PRMS to develop a more consistent approach to classification and categorization, accounting for unique project risks and uncertainties.
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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 | 0.001 | 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) | 0.001 | 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 it