_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 221994, “Effective Risk Management Through Data-Driven HSE-Assurance Program for Safe Execution of Project Delivery, ” by Wan C. Sia, Zulamryn A. Ahmad, and Sharudin Muhamad, SPE, Petronas, et al. The paper has not been peer reviewed. _ Since 2019, the operator’s project-delivery arm has invested in establishing its Artificial Intelligence Incident and Risk Analysis (AIIRA) platform, an artificial-intelligence model designed to predict future health, safety, and environment (HSE) risks and incidents based on historical HSE-incident data, coupled with a prescription of control measures. Assurance is identified as one of the essential elements in the prescription of control measures of the enhanced module of AIIRA. This paper, therefore, advocates for an HSE Assurance Prescription Tool that complements predictive analytics by evaluating top HSE risks and recommending risk-based assurance intervention wherever appropriate. Introduction Conventional risk-management methodologies, characterized by rigid HSE assurance plans typically developed at the onset of a project, have become inadequate and inaccurate in the face of the dynamic and evolving landscape of project execution. Typical HSE plans often rely on a reactive approach and an annual review cycle of HSE assurance plans. The enhanced AIIRA predictive model is complemented by an HSE Assurance Prescription Tool that improves upon simple identification of top HSE risks by rationalizing holistic risk-based assurance interventions. Frontline workers often are the first to encounter hazards and can provide valuable insights in managing operational risks. By providing workers with the authority, resources, and training to actively participate in risk mitigation and intervention, a project-management team can enhance its ability to identify and address hazards onsite while adapting real-time risk-management strategies. Conceptualization of HSE Assurance Prescription Tool The International Association of Oil and Gas Producers (IOGP) standards for critical HSE activity are set as a main reference and foundational input for the development of the HSE Assurance Prescription Tool by providing insight into the most-critical hazards and vulnerabilities faced by the project delivery. Subsequently, the operator’s existing relevant HSE functional assessment checklists are mapped against IOGP’s critical HSE activities and coupled with the development of a simplified decision-tree algorithm to define the minimum frequency of functional assessment checklists conducted with the following criteria: - Historical records of fines or compounds leading to operational performance deficiency - Risk level defined based on incident findings - Risk level defined based on previous audit findings or compliance assessments This algorithm provides a systematic approach that enables tailored frequency of assurance activities to specific risk profiles and situational needs while preventing assurance fatigue and maintaining a robust assurance and verification process. Development and Implementation of the HSE Assurance Prescription Tool IOGP’s Critical HSE Activity and Functional Assessment Checklist Mapping Assessment. While IOGP’s critical HSE activities provided a foundational input, the developed mapping exercise was customized and crafted in consideration of specific needs of the project-delivery phase, namely fabrication, construction, installation, precommissioning, hookup, commissioning, and decommissioning. The AIIRA predictive model was designed to automate risk that is relevant for each project phase in predicting the unique HSE risks based on historical incident data.
Chris Carpenter (Fri,) studied this question.