Calculating and determining a range of Gas Initially In Place (GIIP) is one of the major challenges faced when optimizing a field development plan. Desired outcomes can be further complicated by geological characteristics which are uncertain and difficult to quantify; to the point where a physical solution is unattainable without the use of inappropriate and complicated software applications. Plackett-Burman Experimental Design (P-B ED) is a published and an innovative process which is simple, logical and efficient in managing uncertainty and appropriately defining the range of possible outcomes by utilizing simple, every day and user friendly software. PB ED allows for effective planning and mitigation for the most likely outcome and the least. The geological uncertainties incorporated in the analysis are described in Part 1 of the Greater Dolphin Area Case Studies; SPE 158545.

The P-B ED workflow was applied to determine the range of GIIP for the Starfish field. Starfish is currently not on production and is located off the East Coast of Trinidad and is being considered for development. It is owned as a joint venture between Chevron and BG Trinidad and Tobago (operator). One of the main objectives of this process was to identify the P10, P50 and P90 geo-models which are then used for dynamic modeling and field development planning.

The Unconstrained Development Study (UDS) process was utilized for the field development planning of Starfish. A UDS is a process used to determine the optimum number of wells and their locations to develop a field. The P50 dynamic model was populated with hundreds of wells which were subsequently eliminated based on well performance and water breakthrough. This is an iterative process which has been recognized as an effective workflow for field development planning. Once the P50 reservoir outcome was optimized, both P10 and P90 geo-models were tested to ensure that the proposed development plan was also valid for the geological range. After applying the UDS process; it was determined that four wells were required to optimally develop the field. This paper discusses the Experimental Design and UDS workflows, summarizes the lessons learned and recommends best practice for field development optimal recovery efficiency.

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