SAND
SAND
Statistical Analysis of Natural Resource Data - SAND
The SAND department was established in 1984. It is a significant international contributor to research and services within reservoir description, stochastic modeling and geostatistics for the oil industry. Our primary goal is to use statistical methods to reduce and quantify risk and uncertainty. The main area is stochastic modeling of the geology in petroleum reservoirs including upscaling and history matching. There is also a significant activity on all kinds of risk quantification, primarily within the energy sector.
The staff has a background in statistics, mathematics, physics, numerical analysis and computer science. To ensure that we work with interesting and relevant problems for the petroleum industry, we encourage close cooperation with professionals within the geo-science whenever this is relevant for the project. Oil companies, software vendors within the oil industry and research project sponsored by the European Commission and The Research Council of Norway, finance most projects.
Research areas
Efficient depletion of oil and gas reservoirs require an accurate description of geometric shapes and the petrophysical properties of the sedimentary rocks. We use statistical methods to integrate all available data and stochastic models to describe the remaining uncertainty.
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NR has long experience in stochastic modeling faults and surfaces. This is done to integrate seismic and well data with geological knowledge, and to study the uncertainty both in reservoir volume and in flow within the reservoir.
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We use Bayesian approach for inversion of geophysical data. This provides a common framework when integrating rock physics and structural geology with geophysical data. We do work on seismic and electromagnetic data.
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The oil and gas industry has lot of data from different sources. These data can give valuable information to decision-makers about uncertainty. Statistical methods are valuable tools to estimate uncertainty and thereby give important decision support.
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The use of statistical methods for using historical production data to improver petroleum reservoir models.
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Storage of CO2 in saline acquifers is one important way mitigating climate change due to green house gases. We work on techniques for optimizing the storage process and new and better ways of monitoring the flow of CO2 within the saline acquifers.
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This is a center for Research-based-innovation funded by the Research Council of Norway. The center has a close cooperation with industry and academia developing new methods that improve innovation within finance, petroleum, health and marine resources.
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