Offshore (Subsea) Power Delivery Management Model
Authors: Noel Cornelia Deann 
Published: April 2012

Offshore (subsea) power delivery systems have traditionally been viewed as asecond order decision for upstream energy projects. The primary focus has beenthe hydrocarbon value chain, or the physical path of bringing oil or gas tomarket: reservoir fluid flow through the well completions and subsea facilitiesto the offshore process host, and finally to export pipelines. Moreover, although proven and in wide use for the hydrocarbon value chain, thetraditional decision-making modeling process is yet to be applied for theoffshore (subsea) power delivery because of its perceived insignificance. However, the pending difficulty in developing long-offset and/or marginal leaseareas (oil or gas), the volatile commodity market, and climate changeregulations uncertainty dictate that an alternative view where power is nolonger a second-order decision will be needed.

This paper describes an IT-enabled power delivery management (PDM) model toaddress the many challenges inherent in decision-making for offshore (subsea)power delivery. These challenges include the diversity in functionaldisciplines required for effective decision-making, many dimensions ofpotential value and system design trade-offs (e.g. local power vs.power-from-shore), varying perceptions of value by stakeholders, the need toaccommodate uncertainty, and the need to align actions of individuals tohigher-level corporate objectives.

The PDM model is supported by an integrated decision environment where thestakeholders, operators, systems integrators, and suppliers, can interactseamlessly. This novel approach will aid in the increased uptake of newtechnologies for offshore (subsea) power delivery. In addition, it caneliminate knowledge islands and re-work errors (i.e. data is entered once andused many times); it simplifies complex decisions making cross-disciplineimpacts explicit; it standardizes the system decision model and reportingformat; and automates the decision models so it can be re-used and tailored inrepeatable ways by the team or other stakeholders.

Introduction

To support investment in a particular power system technology, some evaluationhas to be done that would likely incorporate multiple "what-if" scenarios forthe numerous power provisioning approaches under consideration, whether byusing formal decision analysis or discrete evaluations. Moreover, projectuncertainty can increase the power system alternatives to be examined. Addingto the complexity is the emergence of the Renewables Energy market as aconsequence of the spotlight placed on CO2 emissions. The number of RenewableEnergy concepts (solar, wind, ocean) recorded to date is easily +100;" down-selection" of the most promising Renewable Energy technology relative toproject need is warranted.

Now, without an integrated workflow and supporting IT toolkit, power systemtechnology evaluations can be onerous. The norm is to use multiple IT tools(Excel, Word, PowerPoint, custom-built models) to assemble the dataset uponwhich decision are made. In most cases, the tools are not linked necessitatingmanual data transfer. Of additional concern is the duplication of effortinvolved as the same core knowledge dataset would have been assembled prior toaddress a similar problem. Moreover, each time a team member makes neededchanges to even one of the variables, those change has to be manuallyreplicated across the multiple tools in use.