Hazards to water resources and life safety from exploitation of onshore wells by hydraulic fracturing
Bibliographic record
Abstract
This article addresses risks of damage to surface and ground water, and safety of operating personnel and the general public. It includes the experience from the exploitation of shale hydrocarbons in USA, Canada and China, as applicable to the conditions in the United Kingdom and elsewhere. The accident and pollution rates in drilling, fugitive methane and water pollution in these countries are significant and widely reported and need consideration in relation to proposed activities in UK and other countries. The article gives detailed explanation of the failure mechanisms that have led to accidents and pollution incidents overseas and may apply to UK and other countries. Much reference is to authors in USA and China and it is shown that the hydraulic fracturing operation itself is a major cause of well integrity failures that are not normally present in conventional onshore oil and gas exploitation sites. Methods used for the conventional sites can be applied selectively, but differences are not well covered in existing UK guidance or elsewhere. Significant amendments are proposed in the article. Hydraulic fracturing inter-acts with geology faults, which cannot be predicted, prevented, detected nor mitigated, and must be prohibited as such. The US experience cannot be applied in this aspect as the density of faults in UK is four-times higher than in US, and also the density of population, infrastructure and facilities are much higher in UK than in US. The hydraulic fracturing activity also increases the risk of loss of life of operation personnel and general public, whereas the three highest risk types are associated with transportation, contacts with equipment and fire and explosions. The objective of the article is to take a whole picture view as it is the interaction of factors that is key to the overall hazard. It explains the problem, describes the method of solution of the problem, the verification of the solution method, the solution itself with results, conclusions, recommendations and references. It presents the simulations of multi-physics, non-linear thermodynamics and strength behaviour of key process equipment. The article also briefly outlines the methods of holistic semi-quantitative risk assessment and the design of Safety and Environment Critical Elements and Barriers. It is pointed out that the findings in relation to risk of well leakage can apply also for carbon dioxide sequestration. This is due to the currently favoured practice of injecting cold liquid carbon dioxide into reservoirs that may have high temperature rocks. On the subject of computational intelligence, it is recommended that the thread of computational intelligence be interrupted by audit points, at each of which, the parallel safety management system (SMS) can control and amend the parameters of the thread. This is to cover for inherent risk uncertainties identified in the SMS process.
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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 | 0.000 | 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) | 0.000 | 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".