Well Integrity Risk Assessment - Software Model for the Future

Abstract

AbstractRisk is a topic reaching over many layers in an organization and its structure. From operator and asset level to individual wells and operations. The oil and gas industry's joint consensus of primary focus is safe and effective production. This is reflected in the growing efforts in the area of Well Integrity. The essence of Well Integrity is "containment" and the essence of a Well Integrity Risk Assessment (WIRA) is to demonstrate containment capacity in a scenario where barrier elements fail to meet industry standards and requirements. Risk assessments often adhere to guidelines in ISO 16530 part 1 "Life cycle governance" and part 2 "Well integrity for the operational phase". Following the practice outlined in these standards, understanding the risk starts with a procedure for identifying the risk level of the individual wells and then goes on to evaluate the impact to – and the total asset risk level.When a parameter indicates a weakness in a barrier, the general procedure is to investigate until the source is identified and the associated risk is understood. In many cases, the error indicator, trouble shooting procedure, and final risk assessment is triggered by a failure known and familiar to the many experienced Well Integrity organizations operating wells. These organizations are processing vast amounts of data to understand the Well Integrity, the risk at single well level and asset level associated by producing one or more wells with deviating behavior. Software exists to support the daily efforts in Well Integrity, but a digitalization process can make a step change. The basis of a new Life Cycle Well Integrity Model (LCWIM) has been developed. Risk assessment support as function of the integrity indicators is one of the features planned for the LCWIM. The scope of this paper is to outline how risk assessment processes often are performed in Well Integrity, and establish the key components in a plan for an autonomous process, where the LCWIM generates the risk assessment based on the signals transmitted from the well.