Abstract

In the near future, development of subsea oil and gas fields in ultra deepwater will likely use new subsea systems technology. The rapid pace required for developing and deploying new technology will further reduce the time available for identifying and correcting latent design flaws. In addition, the relative numbers of these systems deployed by individual operators may not be statistically significant. Hence the design of the next generation subsea systems would benefit from processes and tools that employ alternative methodologies. This paper proposes a new paradigm for improving subsea system designs that can be embedded in the front-end-loading (FEL) design process. The approach employs the evolution concept and visual pattern recognition (exploratory data analysis) along with commercial-off-theshelf (COTS) software tools. More specifically, this design tool enhances the ability of decision-makers to effectively control the three business drivers - life-cycle-cost (LCC), ystem availability (A) and time schedule (T). In the industrial sector, studies comparing traditional design processes to automated FEL indicate man-hour savings multiples ranging from 8:1 to as much as 40:11. Another source indicates greater than 6X cost savings could be accrued over traditional design processes.

Introduction2,3

The approach to improving subsea system designs must integrate a balanced improvement of not only the system's availability (A) but also its life-cycle-cost (LCC) and time schedule (T). These three factors, T, A and LCC, can be termed the "3-Axes of Continuous Improvement for a Subsea System Design" (see Fig. 1): the T-A-LCC factor. Using these three axes, one can establish a baseline for measuring improvements in subsea system designs. Figure 2 graphically depicts the approximate relationship of Availability (A) vs. Life-Cycle-Cost (LCC) and Availability (A) vs. Time Schedule (T).

Life-Cycle-Cost (LCC) Axis.

Some of the cost components associated with a subsea system design are immediate (CAPEX), but many are downstream (OPEX). The sum of the upstream and downstream costs, the total ownership cost (LCC), is the key variable in determining economic performance. However, downstream cost estimations are broad approximations. Consequently, there is a high degree of uncertainty in economic performance projections, thus reducing their value as discriminators in major decisions.

Key economic performance measures influenced by this component include net-present-value (NPV), discounted-cashflow-return-on-investment (DCFROI), return-on-capitalemployed (ROCE), CAPEX/BOE, OPEX/BOE, payout (PO).

Time Schedule (T) Axis.

Many terms can be used to describe today's business environment: dynamic, decentralized and global, among others. However, there is one constant in all this - the need for faster response to the demands of the capital markets. The latter was one of the drivers for the shift from the sequential-to an overlapped-process for oil and gas project development. The differences in time schedule: +/- 9 years for the sequential process as opposed to +/- 4 years for the overlapped process.

The project milestones that influence this factor include: exploration/appraisal, first production, full production, field abandonment. But one also needs to be cognizant of the risk elements that can lengthen or shorten the time schedule - namely market conditions, equipment and/or resource availability.

This content is only available via PDF.
You can access this article if you purchase or spend a download.