--> Abstract: Does Scenario Modelling Really Lead to from Explosion in the Work We Have to Do?, by Alan D. Gibbs, Clare Bond, Roderick J. Muir, and Zoe K. Shipton; #90078 (2008)

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Does Scenario Modelling Really Lead to from Explosion in the Work We Have to Do?

Alan D. Gibbs1, Clare Bond1, Roderick J. Muir1, and Zoe K. Shipton2
1Midland Valley Exploration, Glasgow, United Kingdom
2Geographical and Earth Sciences, University of Glasgow, Glasgow, United Kingdom

Traditional best practice leads us to make detailed syntheses of data to build a geological model. The model produced, we believe, is the best solution given the constraints of data and time. These models are often vigorously defended representing months of work that embody the distillation of our knowledge and experience.

Even with the best data and our best endeavours we find that on drilling or the acquisition of additional data that the model is inadequate or even wrong. The model needs to be either modified or the modelling process must begin again. Many industry projects go through a cyclical workflow of data acquisition, model building and drilling, with projects evolving through several very different model paradigms in their life time. The authors have carried out some controlled studies to assess the level of uncertainty inherent in interpretation. This work has indicated that even when the best interpretational practices are deployed the creation of a single deterministic model will still lead to a significant level of uncertainty.

Recognition that geological datasets are massively unconstrained means that we need to adopt new workflows to define the range of "possible" models. Once the full range of models is acknowledged, they can be ranked for their impact on outcome and hence decision. Using current interpretation and software methodologies multiple complete models would need to be built prior to making decisions, a multiplier on the time taken to prepare a drilling model. This paper outlines revised workflows necessary to test model sensitivity to change, outlining the characteristics of software toolsets that enable interpreters to create a large number of scenario and sensitivity cartoons to support the decision process.

 

AAPG Search and Discover Article #90078©2008 AAPG Annual Convention, San Antonio, Texas