Resource Optimization at Remote Facilities by Leveraging Advance Maintenance Practices TPM (Total Productive Maintenance), ODR (Operator Driven Reliability) and Industry 4.0 Technologies

Abstract

Abstract ADNOC Onshore X Field is in the southwest of Abu Dhabi city. This field has currently 01 Centralized Processing Facility, 3 Remote Degassing Stations, 15 oil gathering stations and two satellite pumping stations and more than 1000 oil producing wells. The current sustainable oil production from this Field is around 570,000 STBOPD. Most of the remote gathering stations are manned during daytime and operator is present at site to support operational and maintenance activities. The objective of this case study was to adopt lean maintenance practices and take advantage of the digitalization projects completed in ADNOC Onshore and optimization the resources in both operations and maintenance Disciplines. In oil field, the assets are remotely located which possess a great challenge related to logistics and resource mobilization and lot of time is consumed in front end troubleshooting during any operational disturbance or equipment downtime. The objective of this paper is to share the outcome of a pilot project executed at one of the giant oil fields in ADNOC Onshore for the de-manning/resource optimization at one of remote facility by applying advance maintenance approaches and Industry 4.0 solutions. The methods and solutions utilized to achieve this objective are TPM (Total Productive Maintenance), Autonomous Maintenance, Operator Driven Reliability, Connected Worker, Deployment of IIoT (Industrial Internet of Things) for remote monitoring and AI based predictive maintenance model for operator support and training. These satellite facilities are located at 45 minutes of driving distance from parent facility and are designed to be manned during day times. The objective was to lead this operation to unmanned and minimize the mobilization towards this facility by optimizing the operation and maintenance activities being conducted for this site. Following methodologies were adopted to during the formulation of execution strategy. All operational and low critical activities performed maintenance team was analyzed and a solution was developed to adopt Autonomous Maintenance / TPM (Total Productive Maintenance) Philosophy. ORS was achieved with Connected Worker Solution. Cost Effective IIoT solution were deployed for remote monitoring at parent facility. AI based decision model based on FMEA and RCM outcomes was deployed over the existing Process Information Solution to facilitate the predictive maintenance and ease in operator and maintenance technician decision process. After conducting the analysis and assessing the initial functionality of ODR and IIoT solution, following are the benefits from this approach. 10% of total annualized manhours were optimized by shifting low critical activities from maintenance to operations. 30% reduction in movement by operations and maintenance staff towards that remote facility leading to 8000KG/Month reduction of CO2 emission. Low critical maintenance and operations activities plan designed in a way that justifies the requirement of an operator during the daytime performing operational and maintenance activities. Operator takes greater ownership of the equipment and enhancement equipment functionality, failure modes and corrective actions. Maintenance Team only responsible for low frequency and high critical activities. This paper will describe the optimized operation of remote facilities with the application of advance maintenance strategies e.g., TPM, ODR and industrial solutions offered by advancement in digitalization such as IIoT, connected worker, remote data monitoring and AI techniques based on plant data. Lesson learnt and challenges faced in adopting this change will also be showcased.