Bibliographic record
Abstract
Abstract Selecting an appropriate method for disposal of hydrocarbon contaminated drilling waste involves a number of fundamental issues; regulatory compliance, environmental risk and liability, cost effectiveness, environmental impact, and timeliness of disposal. The objective of this presentation is to review the field and lab data associated with the compost bioremediation of hydrocarbon contaminated drilling wastes. Based on the technical data compiled since 1996, compost treatment of hydrocarbon contaminated wastes effectively addresses the disposal issues outlined above. The results of our studies indicate that composting is not only an effective method of hydrocarbon contaminated waste treatment, but the resulting media is a nutrient rich, organic value added product, useful in reclamation of the well site or associated activity areas. Newpark's compost media has been exposed to a multitude of leachability, toxicity, and physical characterization studies; and is found to meet with compost maturity criteria as set our by the CCME, BNQ, and AAFC! Newpark has developed the program to a cost effective, environmentally sound treatment technology which we provide to our clients on over 300 projects throughout western Canada; as well as at our bioremediation facilities in Nova Scotia and Wyoming. Application of this method of bioremediation is not only effective for the treatment of drilling wastes but is also effective for the remediation of other types of hydrocarbon contaminated media. (e.g. Soil contamination from oil spills). Introduction The year 2001 drilling season will generate in excess of 500,000 cubic metres of oily drilling waste in Western Canada alone. The petroleum hydrocarbon contamination issue is further illustrated by several hundred thousand tonnes of contaminated soils seen annually throughout our region. Management options for these contaminated materials include the following:Landfill DisposalLandfarming / landtreatment systemsEncapsulation / stabilizationThermal Destruction or recyclingWashing and recovery systems Landfill disposal is, by far, the most common disposal option for these wastes in Alberta. Many operators choose to manage these wastes on their own property, thereby maintaining liability control 'on-site and infield'. Outside of Alberta there are increased restrictions on burial of such materials, and treatment is required to address future liability issues. Soil conservation, waste recovery, recycling, conversion, and resource management concepts have been a major driving force for effective bioremediation techniques. Typically, a bioremediation treatment system will falter in it's ability to meet financial goals or closure requirements. In addition, many bioremedial methods perform poorly in our generally difficult Canadian climate. In the past land treatments were the mainstay of Newpark's 'in-field' bioremediation systems throughout Western Canada. Land treatments had demonstrated successful treatment of oily drilling wastes and had provided operators with 'cradle to grave' management. However, due to our climate and land restrictions, it was clear that land treatments were not the best answer and were becoming less attractive to our clients. Operators were looking for solutions to the restrictions imposed by land treatment systems; timely management, large land disturbances, aggravation of native soils, and potential reclamation difficulties. Newpark Environmental Services has been actively involved with the development of innovative, yet practical, bioremediation programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".