A new methodology using borehole data to measure

A new methodology using borehole data to measure angular distances between geological interfaces
The study presents a new triangulation-based workflow to assess the degree of parallelism between geological surfaces. This workflow consists of producing and analyzing angular distance distributions as well as conducting spatial analysis using grid maps applicable for subsurface environments with sparse data. We tested our approach using a set of interfaces from Kraków-Silesian Homocline, a geological unit with preferred subhorizontal dip to NE. The pairs of interfaces for angular distance measurements can be divided into two groups: i) separating only Jurassic homocline-related units and ii) separating Jurassic homocline-related units from homocline-unrelated units. To observe potential differences for these two groups, we used bootstrap methods and estimated confidence intervals for summary statistics. In our case, the mean of angular distances turned out to be in general smaller for the pair separating only homocline-related Jurassic sediments. The results also show that the method can be more sensitive to the identification of small-scale structures which are developed only in some of the analyzed surfaces. We provided open-source and freely available computer code to allow reproducibility of the results.
Assumption of parallelism in geological modelling
Knowledge about angular relationships between geological interfaces plays a significant role in subsurface geological modelling. The assumption of geologic interfaces parallelism is used in many modelling environments and related geological software (Lajaunie et al. 1997; Calcagno et al. 2008; Caumon et al. 2013; de la Varga et al. 2018; Grose et al. 2021). For example, (Calcagno et al. 2008) assume in the GeoModeller software (http://www.geomodeller.com) that all geological interfaces belong to a series of sub-parallel surfaces. However, terms such as “sub-conformable” (Carmichael and Ailleres 2016; Carena et al. 2019), “sub-parallel” (Wellmann and Regenauer-Lieb 2012) or “layer-cake” (Thiele et al. 2016) are qualitative and do not have the capacity of answering the question, to which extent two geologic interfaces are parallel?
We acknowledge that the modelling assumption of parallelism may be of great practical utility (Caumon et al. 2013; Grose et al. 2021) allowing geological models comprising conformable interfaces to be constructed using a reasonable geometric constraint. Although several interpolation constraints can be applied to alleviate the rigidity of the parallelism assumption, the limitation of using them is that they can sometimes be subjective which affects uncertainty of the resulting geological model (Grose et al. 2021). Moreover, the number of genetically related strata comprising a conformable succession may not always be known in advance. A next problem is that an angular unconformity with a low angle of discordance may appear conformable at a local scale (Groshong 2006) and in such a case this assumption may be a source of the cognitive bias (see Liang et al. 2021 for exaplanation). In geological mapping, distinguishing conformable contacts from low-angle unconformities is difficult but extremely important to the correct map interpretation (Groshong 2006).
Angular unconformities
Deviations from the assumed parallelism between contacts of layers may be attributed to angular unconformities. For example, angular unconformities develop where tectonically tilted older strata have been eroded and have subsequently been overlain by younger strata (Shanmugam 1988). Thus, knowledge about angular unconformities is important for determining the timing of tectonic activity (Shanmugam 1988).
Comparison between different spatial interpolation methods for the development of sediment distribution maps in coastal areas
Sediment grain size and its spatial distribution is a very important aspect for many applications and processes that occur in the coastal zone. One of these is coastal erosion which is strongly dependent on sediment distribution and transportation. To highlight this fact, surficial coastal sediments were collected from a densely populated coastal zone in Western Greece, which suffers extensive erosion, and grain size distribution was thoroughly analysed, to predict the spatial distribution of the median grain size diameter (D50) and produce sediment distribution maps. Four different geostatistical interpolation techniques (Ordinary Kriging, Simple Kriging, Empirical Bayesian Kriging and Universal Kriging) and three deterministic (Radial Basis Function, Local Polynomial Interpolation, and Inverse Distance Weighting) were employed for the construction of the respective surficial sediment distribution maps with the use of GIS. Moreover, a comparative study between the deterministic and geostatistical approaches was applied and the performance of each interpolation method was evaluated using cross-validation and estimating the Pearson Corellation and the coefficient of determination (R2). The best interpolation technique for this research proved to be the Ordinary Kriging for the shoreline materials and the Empirical Bayesian Kriging (EBK) for the seabed materials since both had the lowest prediction errors and the highest R2.
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Coastal zones are one of the most complex and dynamic systems since their landform changes rapidly (timeframe of days and weeks) due to the combined action of tidal flows, currents and waves on coastal sediments (Raper et al. 2005). Moreover, grain size analysis and textural characteristics of surficial coastal sediments provide useful information to define and reveal the hydrodynamic condition as well as the deposition process. The modelling of many environmental and engineering applications in the coastal zone as well as for risk assessment against coastal hazards requires the knowledge of the grain size and the distribution of the surficial coastal sediments. As a result, measurements of grain size parameters are important for the understanding and calculation of sediment transport and critical parameters for modelling coastal erosion and vulnerability (Boumboulis et al. 2021), offshore and geotechnical engineering (Zananiri and Vakalas 2019), coastal zone management and coastal protection works such as beach nourishment. Hence, maps of surficial sediment spatial distribution in coastal and nearshore zone are important to provide information about the processes and mechanisms of the environment for sustainable management and protection.