Project Challenge
At Shell Albian Sands, maintenance on slurry conditioning lines reduced redundancy and exposed the operation to production losses. The consequences extended beyond the equipment undergoing maintenance: mine feed, crushing conditions, available inventories, upgrading, blending and pipeline movement all influenced the overall production response.
The initial objective was to understand this maintenance exposure and compare alternatives. A focused bottleneck study therefore developed into an integrated operating model, allowing maintenance, operating and capital decisions to be assessed across the broader oil sands production system.
Modelling Approach
The discrete-event simulation began with the conditioning-line bottleneck and expanded to represent upstream and downstream interactions. Its scope connected mining and feed, crushing, conditioning, storage, upgrading, product blending and pipeline movement.
The model represented mine rates, feed consistency and crushing conditions alongside conditioning-line availability, maintenance, routing and redundancy. It also included feed buffers, surge capacity, upgrading and tank inventories. Product recipes, pipeline batches and transfer rules linked production with downstream movement.
Calibration against benchmark operating data provided a basis for comparing operating scenarios. The resulting configurable model supported investigation of how equipment availability, inventories and operating rules influenced system performance, including situations in which the controlling constraint shifted between parts of the operation.
Decisions Supported
The analysis compared maintenance schedules and outage timing, including the implications of reduced redundancy for production exposure and recovery. Equipment arrangements and expansion options could be evaluated alongside tank capacity, storage constraints and operating rules.
Product blending and pipeline batching were also examined so that alternatives could be compared by their effect on total production. This connected local equipment decisions with the performance of the wider operating system.
The integrated model supported maintenance planning, capital configuration studies, production forecasting and scenario testing. These applications used a common representation of the operation to examine interactions between proposed changes and existing constraints.
Outcomes and Applications
The work developed from a local maintenance study into a configurable tool for integrated operating decision support. It demonstrated how constraints could shift as equipment availability, inventory levels and operating rules changed.
The central finding was that maintenance at a critical asset is a system-level decision. Upstream feed, available storage and downstream operating rules can absorb or amplify the effects of downtime. Evaluating the complete production response helps inform maintenance plans and capacity alternatives.
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