Bringing Uncertainty to the Forefront of Informed Decision Making in Oil and Gas Exploration and Development
- Paul Wanjau (Varigrid Explorations Inc.) | Rory Bloomfield (Varigrid Explorations Inc.) | Jennifer Bauer (National Energy Technology Lab) | Kelly Rose (National Energy Technology Lab)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Data, Visualization, Exploration, Uncertainty, Decision
- 3 in the last 30 days
- 239 since 2007
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As data computing and big data driven analytics become more prevalent in a number of spatial industries, there is increasing need to quantify and communicate uncertainty with those data and resulting spatial analytical products. This has direct implication in oil & gas exploration and development where big data and data analytics continue to expand uses and applications of spatial and spatio-temporal data in the industry without providing for effective communication of spatial uncertainty. The result is that communications and inferences made using spatial data visuals lack crucial information about uncertainty and thus present a barrier to accurate and efficient decision making. With increasing cost awareness in oil & gas exploration and development, there is urgent need for methods and tools that help to objectively define and integrate uncertainty into business decisions.
To address this need, the Variable Grid Method (VGM) has been developed for simultaneous communication of both spatial patterns and trends and the uncertainty associated with data or their analyses. The VGM utilizes varying grid cell sizes to visually communicate and constrain the uncertainty, creating an integrated layer that can be used to visualize uncertainty associated with spatial, spatio-temporal data or data-driven products.
In this paper, we detail the VGM approach and demonstrate the utility of the VGM to intuitively quantify and provide cost-effective information about the relationship between uncertainty and spatial data. This allows trends of interest to be objectively investigated and target uncertainty criteria defined to drive optimal investment in improved subsurface definition. Examples are presented to show how the VGM can thus be used for efficient decision making in multiple applications including geological risk evaluation, as well as to optimize data acquisition in exploration and development.
Today, uncertainty, if it is provided at all, is generally communicated using multiple independent visuals, aggregated in final displays, or omitted altogether. The VGM provides a robust method for quantifying and representing uncertainty in spatial data analyses, offering key information about the analysis, but also associated risks, both of which are vital for making prudent business decisions in oil & gas exploration and development.
|File Size||1 MB||Number of Pages||15|
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