by Martin M. Franklin, Kevin R. Hanson
As presented at the 2019 Winter Simulation Conference
Modeling and simulation was key in solving a prominent problem in the oil and gas industry; how to mitigate disruption from stoppages in a single pipeline and keeping customers supplied with minimal interruptions required for sustaining high service levels. The client commenced various expansion projects to add storage capacity to an existing pumping station. Concern was raised about future demand exceeding capacity. The client was interested in identifying the optimal number, size, and arrangement of the tankage at the new terminal in order to obtain the most cost efficient use of capital towards operational gains for their end customer. Benefits of the new terminal were expected to include improvements in the ability to receive mainline inputs to the terminal despite variability in sending batches to end customers, and conversely in the event of upstream upsets, providing consistency and predictability of batch deliveries to their end customers.
Introduction
The client owned and operated an oil pipeline system in Canada and the United States and as part of a pipeline capacity expansion business case was evaluating inline storage requirements. A series of different configurations and sizes of storage tanks needed to be considered and analyzed, and by employing advanced modeling and simulation, informed decision making was made possible and recognized as best practice. More specifically, a model that considered various mainline batch sequenced inputs and outputs in a first in – first out manner (FIFO), scheduled maintenance, and random service slowdowns or failure events either upstream or downstream of the terminal was desired.
This paper and accompanying presentation provides an overview of the system being modeled, demonstration of the model as developed, and shares some of the best practices and approaches applied in representing the digital twin of the terminal.
Problem Statement
The objective of this simulation study was to evaluate the performance of a proposed future state in-line terminal. A buffering capacity analysis was required to determine if the proposed tankage equipment would meet the future production delivery demands. Identification of capacity constraints, as well as financially feasible solutions for mitigating the impact of upstream and downstream upsets, were of interest. The simulation model also served as a digital twin, with which the client could test different batch scheduling loads and tank usage operating rules and methods.