Coal exploration and mining in extensively drilled and sampled coal seams can benefit from 3D statistical facies interpolation. Starting from closely spaced core descriptions, and using interpolation methods, a 3D optimum and robust facies distribution model was obtained for a thick, heterogeneous coal seam zone deposited in the non-marine As Pontes basin (Oligocene-Early Miocene, NW Spain). Se...

Instead of using indicator kriging to estimate discrete versions of cumulative distribution functions, with its order-relation problems, we suggest a compositional approach to the estimation of probability functions. A preliminary Bayesian treatment is needed to obtain estimates of the pdf (without zeroes) at sampled locations, and afterwards an isometric log-ratio transform provides unbounded ...

Probability maps are used to define areas with high and low certainty of exceeding a threshold value. The most popular methods for creating these maps are variants of indicator kriging. However, such methods are questionable when the data exhibit a trend or contain measurement errors, the latter of which is common in most data sets. This paper presents an alternative approach that maps the risk...

Image segmentation is a crucial step in understanding the structure of porous materials, subsequent analyses being profoundly dependent upon segmentation accuracy. Computed tomography images of naturally occurring heterogeneous materials such as soils are particularly challenging to segment reliably, due to the prevalence of partial volume effects, noise, and other artefacts induced during the ...

Area-class maps are conventionally delineated by human hands based on limited observed (or high-quality) data and expert knowledge. It is recognized that areaclass maps contain spatial uncertainty because the classification of unobserved locations is not completely certain. Spatial uncertainty associated with an area-class map may be quantified by spatial statistical approaches through estimati...

Real-time assessment of the ambient air quality has gained an increased interest in recent years. To give support to this evolution, the statistical air pollution interpolation model RIO is developed. Due to the very low computational cost this interpolation model is an efficient tool for an environment agency when performing real-time air quality assessments. Beside this, a reliable interpolat...

[1] During the last decade one has witnessed an increasing interest in assessing health risks caused by exposure to contaminants present in the soil, air, and water. A key component of any exposure study is a reliable model for the space-time distribution of pollutants. This paper compares the performances of multi-Gaussian and indicator kriging for modeling probabilistically the spatial distri...