In plays with multiple prospects, decision makers put themselves at a significant disadvantage by using economics on a stand-alone basis to justify development for each prospect. Offshore developments do not require a stand-alone discovery to exceed a minimum economic threshold for the development to be sanctioned. Technology developments such as, extended reach drilling and long distance subsea tie-backs support the development of an asset area using a "clustered" development model. The presence of geologic dependence and development synergies between prospects, requires that business development decisions be made holistically using a "clustered" development approach.
In the clustered development approach, the geologic dependence between prospects is combined with the aggregation of prospects to determine the economic viability of a grass roots development offshore. Historically our industry has applied a rather straightforward conservative approach whereby a grass roots development required a single prospect to meet or exceed the minimum economic threshold. A better approach would base the initial sanctioning and capacity design decisions on one or more discoveries that exceed the minimum economic threshold in aggregate, even though no individual discovery may be large enough to support a stand-alone development. Although easily visualized, economic evaluations of clustered developments do not typically consider the geological dependencies and development synergies that exist. As we will demonstrate, modeling these synergies has a significant impact on the economic evaluation of grass roots developments.
Play analysis concepts, where we develop an understanding of the dependency between prospects, must be assessed to properly evaluate new offshore developments. In "greenfield developments", there are geologic chance dependencies (shared chance elements) between many of the prospects. Probabilistic analysis is the preferred method to evaluate the range of possible resource outcomes at each prospect and the dependency between the shared chance parameters of the clustered prospects. These geologic dependencies, integrated with development dependencies, will be linked to modify the probabilistic geologic resources distribution into an economic resources distribution and economic chance of project success. Examples will be shown in this paper of a clustered development economic evaluation that quantifies the increased chance-weighted resources, improved chance of economic success for project sanctioning and the increased expected monetary value of the venture.
Where we have often failed as an industry is in getting the understanding of these geological concepts into our commercial models. To make this happen, our geoscientists, engineers and business analysts need to better understand the commercial impact of conducting fairway analyses and how a clustered development can take a series of smaller prospects and potentially make them commercially viable.
Included in the paper, we have built a three-prospect evaluation template using three different evaluation models.
The historic industry approach where we evaluate a new region based on having one discovery which is large enough to support the infrastructure development.
An analysis whereby the development decision is made based on a clustered development with no consideration for the impact of geologic dependence.
In the third approach, advocated by the authors, we combine a clustered development with geologic dependence between the prospects. The development decisions are then based on what might be found when all three prospects are considered.
These approaches are the type of evaluations that are best conducted before the prospects in a new region are drilled. Clustered developments are common today, but only after the individual prospects have been drilled and delineated.