Bibliographic record
Abstract
Technology Focus The baton has been passed, and so, during the next 3 years, I will provide here a brief editorial about and drawing your attention to recent publications or events pertaining to unconventional resources. I have been around the industry since the late 1970s and have seen many changes since. I started my petroleum career working in the unconventional oil sands of Alberta, Canada, which are similar to but colder than those of Venezuela. Although unconventional-oil exploitation is still a dynamic topic, activity in unconventional gas (e.g., tight gas, shale gas, and coalbed methane) is picking up as environmental awareness surrounding the exploitation of unconventional resources grows. So, my editorial is about "unconventionals," a very trendy word indeed. What are unconventional resources and what characterizes them? I will broach this topic in a general way without offering a definition—this has been debated for a long time! There are unconventional locations (e.g., deep water or beneath national parklands, a lake, or a city), which require unconventional methods. There are unconventional formations (e.g., oil sands and coalbed methane) containing hydrocarbons that cannot be produced in a conventional (primary or secondary) way with available equipment, or are not being exploited because of unavailable methods and/or high costs. Unconventional technologies are being developed to recover these unconventional and difficult-to-recover hydrocarbons, from drilling and completions to logging to production. There are unconventional "energies," with a shift toward renewable ones such as wind, solar, geothermal, and deep ocean energies, and biofuels. Obviously, the environment is a priority, and large efforts are expended nowadays in this direction. For example, greenhouse gases are being captured and disposed of in deep rocks or in the water in pilot projects; these gases are also used for enhanced oil recovery. The more-than-century-old "oil and gas" industry has changed into an "energy" industry. As this industry is redefined, many of the technologies that traditionally have been used for oil and gas exploration and development are needed to expand unconventional resources and advance the development of other sources of energy, whether they are nonrenewable or renewable ones. It is natural for this growth of the industry to happen. Along the way, we will find/discover new technologies that will also help the development or redevelopment of the old established sources. Bright is the future! Unconventional Resources additional reading available at OnePetro: www.onepetro.org SPE 119891 • "Workflow for Stratigraphic Characterization of Unconventional Gas Shales" by Roger M. Slatt, SPE, University of Oklahoma, et al. IPTC 12743 • "Importance of Unconventional Oil Resources in Shaping the Far East Energy Future" by Philip Stark, IHS, et al. SPE 113852 • "Oil and Gas Expertise for Geothermal Exploitation: The Need for Technology Transfer" by Gioia Falcone, SPE, Texas A&M University, et al.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.096 | 0.053 |
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".