Controlling Hazards through Risk Management - A Structured Approach
Bibliographic record
Abstract
Controlling Hazards through Risk Management - A Structured Approach R. Theriau; R. Theriau Halliburton Search for other works by this author on: This Site Google Scholar K. Rispler; K. Rispler Halliburton Search for other works by this author on: This Site Google Scholar S. Redpath S. Redpath Halliburton Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. Paper Number: SPE-86838-MS https://doi.org/10.2118/86838-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Theriau, R., Rispler, K., and S. Redpath. "Controlling Hazards through Risk Management - A Structured Approach." Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. doi: https://doi.org/10.2118/86838-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search ProposalAn effective health, safety, and environment (HSE) program has many requirements. One of the key components to a comprehensive HSE program is an effective system for hazard identification, assessment, and control. It is critical to not only have a systematic approach to hazard assessment and control, but to ensure that the system is accessible, understood, and accepted by front-line employees.This paper presents a description of a hazard and risk assessment system, starting with documentation in a quality system through to implementation at the front line. The paper includes a description of tools employed, such as (1) hazard and risk identification imbedded in an operational quality system, (2) job safety analysis (JSA), (3) decision-making tools, (4) hazard observation, and (5) communication tools. Additionally, methods to make these tools available and used by the front line are discussed. Improved safety performance is in part a result of the reduction of hazards and risks through a systematic approach to hazard and risk identification.To realize the greatest reduction in risk, correct application of all of the tools and the knowledge of when to use each of the tools are critical. Specific examples are used to help ensure that the readers gain a basic understanding of which tools they will likely require.IntroductionWithin every organization, the level of success (measured by the actual numbers of total incidents) with the HSE program is directly proportional to the ability of the organization to control the risks associated with applicable hazards. In other words, the more the company reduces the level of risk, the greater reduction in overall incidents the company will see.There are four basic steps to successful risk control:Identification of the hazard(s).Assessment of the overall risk necessary to determine the type of control to be implemented.Control of the risk.Communication of the risk and its controls to those affected.This approach to hazard control is considered a structured approach. Because many people in and out of the HSE circle interchange these terms, and to understand this structured approach, it is necessary to define several terms:HazardHazard effectRiskResidual riskLikelihood or probabilityFollowing a detailed discussion of these terms and how they interact with each other to manage the risk associated with a particular task or activity, the paper will discuss effective controls aimed at reducing a particular risk or group of risks. Several controls will be examined and will be prioritized in order of long-term success and effectiveness. However, regardless of the control method used, the hazard and its control(s) must then be communicated to those exposed to the risk. Without this communication, the overall effectiveness of the risk management program will be in jeopardy.Structured vs. Unstructured Approach to Risk ManagementTo be effective at risk management, a structured approach must be taken. This four-step approach described above is a vital necessity in any risk-management program. Despite this fact, many organizations, and in some cases "safety professionals," decide to reduce the risk of their business and start implementing a safety program in a random or unstructured nature. This method can often be observed in a company that decides to implement a formal safety program by first copying the safety manual of another company or developing an emergency response plan without truly understanding the potential risks inherent in their business. This approach can also be observed by reviewing an inspection program of a particular company that has failed to examine their worksite for specific hazards. The inspection would appear to randomly address various site concerns. This approach to risk management is shown by the abstract nature of the "Unstructured Approach" in Fig. 1. Keywords: spe 86838, upstream oil & gas, hazard effect, information, hazard identification, identification, risk assessment, society of petroleum engineers, work activity, effectiveness Subjects: Safety, Risk Management and Decision-Making, Operational safety, Risk, uncertainty, and risk assessment This content is only available via PDF. 2004. Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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 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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".