Bibliographic record
Abstract
Technology Focus As throngs of people crowd the car dealerships eager to buy hybrid or electric vehicles to stop using fossil fuels to drive their cars, I reminisce about the good old days when hydrocarbons ruled the world of energy. Oh, wait, that is the start of my upcoming novel! Renewable energy and nuclear power are the world’s fastest-growing energy sources, each increasing 2.5% per year. However, it is estimated that fossil fuels will continue to supply nearly 80% of world energy use through 2040. Natural gas is the fastest-growing fossil fuel, as global supplies of tight gas, shale gas, and coalbed methane increase. Rising prosperity in China and India is a major factor in the outlook for global energy demand. This is great news for our industry because it forces us to continue finding new resources to meet the world’s demands. The massive deepwater reservoirs seem to have been discovered and are, for the most part, in the field-development and production phases. The unconventional reservoirs open new possibilities. Although the term is used indiscriminately for rocks that exhibit permeability values in the nano- to microdarcy range, these unconventional reservoirs fall into various categories that must be exploited differently. Common practice is that massive fractures are required to stimulate hydrocarbon production. But, in many developed countries, the mere mention of the word “fracturing,” or “fracking,” sends shivers down the collective spine of the general population to the point that governing bodies have simply prohibited such practice. Thus, the reservoirs remain unproduced. And they will remain so unless new technologies are developed or the public is eventually educated on the benefits and safety of this procedure. In the meantime, shale gas and coalbed methane, or coal-seam gas, continue to gain acceptance in countries other than the US, where most of the initial techniques have been tested with reasonable success. Interest in exploiting these types of reservoirs has gained momentum in places such as Australia, Argentina, China, Canada, Russia, and even the Middle East. Allow me to say that this is not a comprehensive list; other countries are also opening the doors for companies to find, develop, and produce hydrocarbons from these reservoirs. During the last year, a large number of publications have dealt with testing unconventional reservoirs. Although it was difficult to select three articles from the many manuscripts, I hope that the three chosen convey the interest in these reservoirs and the clever use of well-test data to add knowledge into understanding the producibility of these reservoirs. Finally, let me remind the interested reader that many other articles on this subject are available in the OnePetro library. JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 164349 Innovative Single-Phase Tank Technology for In-Situ Sample Validation Enhances Fluid-Sampling Technology by Francisco Galvan Sanchez, Baker Hughes SPE 164482 Inferring Interwell Connectivity in a Reservoir From Bottomhole-Pressure Fluctuations in Hydraulically Fractured Vertical Wells, Horizontal Wells, and Mixed Wellbore Conditions by Anh V. Dinh, Schlumberger, et al. SPE 166074 In-Situ Poisson’s-Ratio Determination From Interference Transient Well Tests by Mojtaba P. Shahri, The University of Tulsa, et al. IPTC 16711 Deepwater Reservoir Characterization Using Tidal Signal Extracted From Permanent Downhole Pressure Gauge by Xingru Wu, University of Oklahoma, et al.
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.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".