Reducing exploration and production risk by visualization and seismic classification: a case study from the North Sea

The seismic interpreter often has access to large amounts of data, in particular in mature and partially mature basins. Or- ganizing and interpreting the geological and geophysical data in a time and cost efficient fashion is a major challenge. Similarly, the unwritten requirement to be 'right' most of the time means that explorers are occupied in a constant search for means to reduce the risks in their prospects and developments.In addressing these challenges and objectives, a third issue arises, that is the large (and constantly expanding) array of commercial and proprietary technology-based 'interpretation tools' potentially available for use. The questions has thus become, 'What is the exploration problem/risk to be addressed?' and 'Which interpretation tool could be usefully applied to solve the problem?' The ultimate cost/benefit analysis of this process is the measurement of the impact of the technology on the overall understanding of the risk of the prospect or the development. These issues could be usefully addressed by an industry-wide survey of both successful and unsuccessful case histories of technology applications. It seems reasonable to surmise that unsuccessful applications of technology are only rarely published (possibly when the authors are approaching retirement?) Successes may be 'stored away' for reasons of competitive advantage. Most companies are unwilling to share 'cutting edge' technologies or processes which they perceive to give them a competitive advantage. Hence, the purpose of this article is twofold. Firstly, a brief review of some technology applications on a real, and as yet undrilled, North Sea prospect, and a qualitative assessment of their impact on the perceived risks. Secondly, the issue of value for money and the time-saving potential of new technologies is raised as a discussion point within the hydrocarbon exploration community, both within oil companies and the contractors who generate most of the technology. How do we measure the value of technology?