Modelling the Spread of Covid-19 in a Typical Oil and Gas Facility Setting

Abstract

The spread of infectious diseases such as COVID-19 in a typical oil and gas facility setting, the health of employees, their families and their communities, is of real concern to the industry. In this work, a suitable predictive, agent-based model is used to predict the spread of COVID-19 in different settings as well as to evaluate strategies to block the spread. The agent-based modelling work is based on the simulation platform, Complex Organization and Bifurcation Within Environmental Bounds, or COBWEB. COBWEB simulates how a system of autonomous agents adapts to variation and sudden changes in the resource base or other features of their environment. Previous COBWEB simulation results illustrate that the tool is useful for predicting the evolution of COVID-19 spread and the effectiveness of various preventive actions including self-isolation of symptomatic people, social/physical distancing, effective PPE use, and ‘shielding’ (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in such a setting, in particular by shifting the distribution of risk severity towards ineffective PPE use, self-isolation and poor social distancing, which expectedly shows upward trend of the spread of the COVID-19. Ultimately, governments and industry can apply the predicted trends, as well as apply the model to specific settings, to make more informed decisions on the additional measures and preventative strategies to curb the spread of COVID-19.