Exprodat releases white paper entitled "Exploratory Spatial Data Analysis—Optimizing Interpolation of E&P Datasets" for use by Petroleum exploration and production (E&P) sector geoscience and GIS professionals. The paper explains techniques for selecting suitable interpolation methods for creating accurate surface models using Geographical Information System (GIS) technology.

Exploratory Spatial Data Analysis (ESDA) is a group of techniques used to describe and visualize spatial distributions, to highlight patterns affecting the distribution of observations and to identify outlier values. Each interpolation technique has its own advantages and disadvantages, depending on the characteristics of the input dataset. ESDA techniques provide the GIS user with guidance on how to decide which interpolation method to use when gridding and contouring data.

The techniques in Exprodat’s white paper were first presented at ESRI’s 2009 Petroleum User Group (PUG) Conference in Houston, Texas. By publishing the white paper Exprodat are now able to share the full results of their research with the wider oil and gas GIS community.

Exprodat’s Managing Director, Gareth Smith, says, “Geoscientists are commonly faced with the problem of selecting the most appropriate gridding algorithm when generating grids. Often, they’ll just select the defaults provided in their E&P mapping tools without understanding the implications of their choices. Our research in this area shows that GIS, when used alongside traditional mapping packages, provides powerful tools for evaluating data in order to make these key decisions correctly.” cvv shop in magazine

“Choosing an interpolation method for the type of phenomenon the geoscientist is trying to model, and one that fits the distribution of the data in hand, should not just be a matter of luck - they need to understand the spatial behavior of the phenomenon they are investigating, and need to answer to some critical questions before attempting to apply any interpolation technique. This can help produce defendable results that reflect a deep understanding of the way the phenomenon of interest varies spatially. It also helps us to quantify the uncertainty in the modeling.”

In this paper Exprodat focuses on the use of ESDA techniques available in ESRI’s ArcGIS platform and on guiding the user in choosing a suitable interpolation method among the many available in ArcGIS Spatial Analyst and ArcGIS Geostatistical Analyst.

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