Abstract

Oil and gas production systems are getting deeper, more complex, and far away offshore where energy companies are targeting further resources. These complexities are transforming the problem of field layout design optimization into a much more pressing need. Considering the various pipeline design and layout constraints and associated investment costs, planning and development of production gathering and transmission pipeline networks for oil and gas fields is gaining further importance in field development planning. The optimization of transmission and gathering pipeline networks is conducted to accommodate the encountered topological complexities and significantly reduce total investment cost for the corresponding fields. Although many optimization schemes are developed and widely available in literature, these methods are either prohibitively slow with exhaustive search required, or they don't account for the various topological complexities typically encountered in real scenarios. Thus, the deficiency associated to these optimization schemes becomes drastically more limiting in the case of a concept-select phase of field development planning where many scenarios need to be assessed in a relatively short timeframe.In this study, the optimal shortest path A* algorithm is introduced to the field of pipeline placement optimization. A* is successfully used in other applications such as unmanned aerial vehicle (UAV) and robots motion planning. A benchmark comparison is presented with the Dijkstra algorithm; another algorithm that assures optimal shortest path solution that was recently introduced into this field. This comparison is performed on a varied set of pipeline layout scenarios accounting for different topological complexities and dynamic conditions. The conducted tests show the superiority of the A* algorithm in terms of accounting for the application heuristics and assuring an optimal and efficient solution.

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