This study focuses on the assessment of drought severity, employing a comparative analysis between the normalized multi-band drought index (NMDI; calculated using Sentinel-2 imagery) and the combined drought indicator (CDI). The research aims to pinpoint the most accurate and reliable remote sensing techniques, which reflect ground-based measurements, thereby enhancing the precision of drought monitoring systems. By investigating the specific area of Małopolska, the study not only contributes to the global knowledge base on drought assessment methodologies but also addresses the regional needs for improved drought management practices. Through an exhaustive analysis correlating satellite-derived indices with in situ meteorological data, this research elucidates the potential of integrating NMDI and CDI for a comprehensive understanding of drought dynamics in Małopolska. In particular, the indices depict different dynamics of drought levels, as well as the location of regions more prone to its occurrence. The findings are poised to advance drought monitoring capabilities, offering significant insights for agricultural sustainability and water resource management in the region.

An open-source Python package is presented, ReMo3D, which allows the generation of synthetic normal and lateral resistivity logs for 2D and 3D models. The package is built around a finite element mesh generator Gmsh and a high-performance multiphysics finite element software Netgen/NGSolve and supports distributed-memory parallel computation. The examples included in the paper show that the developed software can accurately simulate the measurement process and produce detailed synthetic normal and lateral resistivity logs. In addition, basic information about normal and lateral tools such as tool configurations, measurement principles, nomenclature and a brief history of utilization is included in the paper.

This study investigates the challenges and opportunities associated with improving the vertical resolution of normal and lateral resistivity logs in thin-bedded rock formations. The proposed iterative inversion procedure combines a finite element method forward modeling procedure with a particle swarm optimization algorithm to generate high-resolution models of the rock formation. The performance of the inversion approach was evaluated using synthetic datasets, and the results of the inversion of field data from thin-bedded formations of the Polish Carpathians are presented. This research highlights the potential of modern computational techniques to enhance the utility of historical resistivity logging data in current studies.

In the past decades, boreholes were drilled all over the world for the purpose of hydrocarbon prospection. Data from these boreholes are a very valuable resource, that can be used in current geological, geothermal and hydrogeological studies. Since the process of drilling is both expensive and disturbing to the environment the possibility of incorporating data that already exists in the current studies is always worth consideration. However, in the case of older boreholes quality of data is not on par with modern standards which limits its usefulness, especially in the case of data from boreholes drilled in thin-bedded rock formations.Resistivity logs are one of the main logs used both in hydrocarbon prospection and other applications such as geological, geothermal and hydrogeological studies. Resistivity logs measured by older generations of logging tools are characterized by significantly lower vertical resolution in comparison to logs measured by newer logging tools which affect the quality of the interpretation. However, the information averaged in the process of logging can be partially restored in the process of iterative inversion.The focus of the presentation is on the utilization of open-source global optimization software in the process of inversion of resistivity well logs. Since inverse problems encountered in geophysics tend to be on the difficult side, relatively simple optimization schemas that often can be found in open-source software are not always giving good results. Therefore, in the presentation, a few methods that allow adapting those algorithms to the problem of inversion of well logs are discussed. The performance of the inversion procedure is validated on synthetic data and real data from the borehole where resistivity logs were measured by different generations of logging tools in the same depth intervals, which allows for comparison of the inversion results to logs measured by modern equipment. The research was funded by the National Science Centre, Poland, grant number 2020/37/N/ ST10/03230.