Uniaxial compressive strength (UCS) is one of the most significant factors on the stability of underground excavation projects. Most of the time, this factor can be obtained by exploratory boreholes evaluation. Due to the large distance between exploratory boreholes in the majority of geotechnical projects, the application of geostatistical methods has increased as an estimator of rock mass pro...

[1] This study presents monthly CO2 fluxes from 1997 to 2001 at a 3.75 latitude 5 longitude resolution, inferred using a geostatistical inverse modeling approach. The approach focuses on quantifying the information content of measurements from the NOAA-ESRL cooperative air sampling network with regard to the global CO2 budget at different spatial and temporal scales. The geostatistical approach...

Genome-wide selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. The success of GS approaches will depend crucially on the availability of efficient and easy-to-use computational tools. Therefore, approaches that can be implemented using mixed models hold particular promise and deserve detailed study. A particular class of mixed models suitable ...

Areal interpolation is the procedure of using known attribute values at a set of (source) areal units to predict unknown attribute values at another set of (target) units. Geostatistical areal interpolation employs spatial prediction algorithms, that is, variants of Kriging, which explicitly incorporate spatial autocorrelation and scale differences between source and target units in the interpo...

The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 tonper-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena ob...

Modern geostatistical mapping methods are being applied to various types of data to produce more realistic and flexible characterizations of a natural random process. The Bayesian Maximum Entropy (BME) is a well-known geostatistical estimation method, especially for the use of soft knowledge as well as exact measurement data. Although development in geostatistical methods helps us to solve limi...