An Adaptive Inverse-Distance Weighting Interpolation Method Considering Spatial Differentiation in 3D Geological Modeling

Estimating the Precipitation Amount at Regional Scale Using a New Tool, Climate Analyzer

Different methods are known for interpolating spatial data. Introduced a few years ago, the initial version of the Most Probable Precipitation Method (MPPM) proved to be a valuable competitor against the Thiessen Polygons Method, Inverse Distance Weighting and kriging for estimating the regional trend of precipitation series. Climate Analyzer, introduced here, is a user-friendly toolkit written in Matlab, which implements the initial and modified version of MPPM and new selection criteria of the series that participate in estimating the regional precipitation series. The software provides the graphical output of the estimated regional series, the modeling errors and the comparisons of the results for different segmentations of the time interval used in modeling. This article contains the description of Climate Analyzer, accompanied by a case study to exemplify its capabilities.

Unique Path Method of the Pinch-Out Profile Based on Unified Stratigraphic Sequence

Pinch-outs refers to the gradual thinning of the thickness of the sedimentary layer laterally until there is no deposition and are a major topic of modern research on the automated drawing of geological profiles. The rapid development of smart geological systems imposed an urgent need for high-speed, accurate methods to plot pinch-outs. However, because of their complexity, excessive number of branch paths, low rendering speed, and poor reliability in the case of large-scale data, the existing pinch-out drawing methods are inadequate and cannot satisfy the modeling needs of large-scale geological projects. To resolve these problems, based on unified stratigraphic sequences, this paper proposes a unique path method for drawing pinch-out profiles by converting the principle of plotting of pinch-outs into controlling the appearance of stratigraphic boundaries, and a high-speed and reliable method for drawing pinch-out in digital profiles is also proposed. The proposed method is successfully applied to drawing geological profiles for an urban geological project in East China, and greatly reduces the complexity of the method without reducing the drawing accuracy. Compared with those of other methods, the speed and reliability are significantly improved. Therefore, the unique path method for drawing pinch-out profiles based on a unified stratigraphic sequence proposed in the writers’ previous paper effectively avoids the excessive branch paths, slow speed, and insufficient reliability of the existing methods and provides effective and reliable support for the rapid drawing of profiles in smart geological systems.

An enhanced dual IDW method for high-quality geospatial interpolation

Many geoscience problems involve predicting attributes of interest at un-sampled locations. Inverse distance weighting (IDW) is a standard solution to such problems. However, IDW is generally not able to produce favorable results in the presence of clustered data, which is commonly used in the geospatial data process. To address this concern, this paper presents a novel interpolation approach (DIDW) that integrates data-to-data correlation with the conventional IDW and reformulates it within the geostatistical framework considering locally varying exponents. Traditional IDW, DIDW, and ordinary kriging are employed to evaluate the interpolation performance of the proposed method. This evaluation is based on a case study using the public Walker Lake dataset, and the associated interpolations are performed in various contexts, such as different sample data sizes and variogram parameters. The results demonstrate that DIDW with locally varying exponents stably produces more accurate and reliable estimates than the conventional IDW and DIDW. Besides, it yields more robust estimates than ordinary kriging in the face of varying variogram parameters. Thus, the proposed method can be applied as a preferred spatial interpolation method for most applications regarding its stability and accuracy.