risk management

In today’s era of asset management, digital twins are changing risk management, optimizing operations, and benefitting the bottom line.

Real-time location systems have emerged as invaluable tools for enhancing safety and efficiency in the operations of oil and gas organizations. This paper investigates the various applications of the technology within the industry, highlighting its transformative effect on safety protocols and operational efficiency.

This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.

The new look at the plan involves considerations for national security.

From optimizing drilling performance to enhancing worker safety, computer vision can change how the industry works.

This paper discusses and demonstrates the limitations of quantitative risk assessments (QRA) with respect to the usefulness of the concept in managing day-to-day and emerging risks as well as the effect of change. The paper goes on to discuss improved solution sets compared with pure reliance on QRA.

“Riskwashing” refers to a situation where an organization engages in superficial or insincere actions to create the appearance of addressing a particular risk or issue without actually taking substantive action to address the underlying problem. This paper presents methods to identify and minimize riskwashing as an organizational response to incidents.

This paper presents a method of geomechanical-risk screening and gives examples of its positive effect on the company’s safety standards through implementation of integrated solutions to prevent or mitigate the risks.

This paper presents an integrated view of three key areas of knowledge that typically are addressed individually—cybersecurity, process safety, and human factors—from the perspective of cybersecurity.

This paper outlines how one company uses digital technologies to manage HSE risks in project delivery, developing an artificial intelligence (AI) predictive model to predict HSE risks and incidents based on historical incident data.