Copyright 2003, Offshore Technology Conference

This paper was prepared for presentation at the 2003 Offshore Technology Conference held in Houston, Texas, U.S.A., 5–8 May 2003.

This paper reports on the results of a Reversionary Mode Analysis Level-1 (RMA-1) to assess the ‘do-ability’ of three novel, complex, smart well designs. These are the Spider Well TM , the Stacked Internal Gravel Packs (IGPs) and the Smart Wells options studied for a deepwater sub-sea field in the Gulf of Mexico.

Both the Spider Well TM and the Stacked IGPs designs are more complex than Smart Wells, which in turn are more complex than conventional wells. These complex smart wells contain more equipment, which complicates the installation of the wells, and which must function for the lifetime of the well. In addition, several equipment items to be incorporated in the wells require new designs, or pressure rating extensions of existing technology.

Whole life-cycle plans were defined for each of those three well design options. Quantitative failure mode analysis incorporating economic consequences were performed on all well construction processes and production subsystems. The RMA software calculated “Risk-Dollars” by multiplying the probability of failure by the consequential costs of well intervention, oil deferment and/or loss of reserves.

The resulting risks were broken down into production system and construction process elements, and into the economic categories of intervention, deferred production and lost reserves. The assessed risks, together with various other factors, were input to the selection process of the preferred field development concept, which is outside the scope of this paper. Key risk drivers were identified from the analysis, allowing cost-effective targeting of reliability improvement actions. The three designs studied, the analysis method and the results are presented in the paper.

The use of quantitative risk results, expressed in economic terms, has wide application in making systematic comparisons between complex systems, both inside and outside the energy industry. The results clarify the reliability risks present in smart wells, even before considering more advanced alternatives.

The results show that failures are inevitable in all three options, but the Spider Well TM carries the greatest overall risk, the highest total number of failure modes and more high-cost failures. The RMA method demonstrated its strength in being able to identify ritical risks and ‘drill-down’ to root causes, allowing specific mitigating measures to be identified and evaluated. These included specific fu ll-scale testing of prototype equipment, and specific quality management and reliability engineering measures. It was found that these mitigating measures, if implemented, would bring the risks to similar levels for all three well design options. Sand control failures present the largest remaining risk.