Remal Project: Utilizing AI & Data Analytics to Predict Sand Movement on Gas Plant in the UAE

Abstract Shah Gas field (SGF) is located within the Empty Quarter desert premises, where the sand dunes are prominent with varying heights up to 40 m. If the sand blows are severe, the sand would cover the access road and block the access and disrupt plant activities. SGF team regularly patrol to check several facilities including Main Asphalt roads, Gatch Roads, Gas Gathering Pipelines Corridors, Well Pads boundary, Main Plants boundary and the major product pipelines corridor to inspect and report of any sand accumulations that require to be cleared. Accurate detection and forecasting of sand accumulation is crucial for scheduling sand cleanup activity and successful oil transport. As it requires huge manual effort and is not cost-effective to measure the true value of sand accumulation at different geographical areas. This paper will present a successful solution to effectively predict and clear sand in a timely manner and at a lower cost in across the Shah Gas Plant and Access Roads area. The invention has been developed as a part of ADNOC Sand Accumulation (Phase 2) for ASG organization in collaboration with Siemens.