Soil gas measurements of radon (²²²Rn), CO₂, and hydrocarbon concentrations, as well as gamma-ray spectrometry, were conducted at two separate locations to estimate the measurement results for known locations of hydrocarbon accumulations in the subsurface and oil seepage on the surface. The aim of the study was to confirm the applicability of the method for identifying migration pathways (e.g., faults) and to detect possible seepages of hydrocarbons to the surface as well as to investigate possible health issue potential about the soil gas analysis results. Site A investigations were performed with a large number of sampling points to provide sufficient spatial coverage to capture the influence of subsurface lithologic variability as well as the influence of the migration pathway on the measured parameters. For the investigation of site B, sampling points were positioned to reflect the situation between the area above producing hydrocarbon fields and areas with no confirmed accumulation. The results presented show that it is possible to distinguish the near-surface lithology (gamma-ray spectrometry), characterize the migration pathway, and indicate the area of oil seepage at the surface. Areas above the known hydrocarbon accumulations generally have elevated radon concentrations and detectable heavier hydrocarbons with sporadic methane in soil gas, which contrasts with the lower radon levels and lack of detectable heavier hydrocarbons in soil gas in the area with no confirmed hydrocarbon accumulation in the subsurface.

The Aiza research area covers over 650 km² of the northern Adriatic offshore, a common Adriatic foreland of the older Dinarides on the NE, and the younger Apennines on the SW. High-quality 3D reflection seismic data were used to investigate the area’s Mesozoic to Cenozoic tectono-stratigraphic evolution. Four main seismo-stratigraphical horizons were recognized: Base of Carbonate Platform (BCP), Top of Carbonate Platform (TCP), Messinian Erosional Surface (MES), and a Plio-Quaternary horizon (PlQh), as well as the dominant faults. The results depict the geological setting and tectonic evolution of the area. A long-lasting (Jurassic to Cretaceous) stable NW-SE striking platform margin evolved probably along the inherited Triassic normal fault. The marginal belt of the platform was affected during the Late Cretaceous to Palaeogene by extension and opening of the intra-platform basin, probably on the southern limb of the then developing Dinaric forebulge. The transverse fault system (Kvarner fault) was probably reactivated as a strike-slip zone during the late Miocene tectonic reorganization. The area was tilted to the SW during the Pliocene, in the distal foreland of the progressively northward propagating Northern Apennines. Sub-horizontal late Quaternary cover of Dinaric and Apenninic structures could imply active subsidence of the foreland in between nowadays sub-vertically exhuming neighboring orogenic belts.

Magnetism in Croatian caves has been significantly underexplored, despite the well-documented preservation of cave sediments. This study investigates whether magnetic susceptibility can be effectively recorded in Croatian caves and, if so, whether there are differences between in situ and laboratory measurements, as well as the extent of these differences. The focus is on two prominent sites within the Velebit Mountain range of the Dinaric Karst: the deep Slovačka Cave and the extensive Crnopac Cave System (ex. Kita Gaćešina Cave). Magnetic susceptibility was measured in soft sediments using the Kappameter KM-7 for in situ assessments and the Bartington MS2B System for laboratory analyses. The comparison of the two devices aimed to evaluate the feasibility of detecting magnetic susceptibility variations within carbonate sediments. Sampling locations were selected based on preliminary assessments of magnetic susceptibility variations and accessibility for sampling. Characteristic samples from each profile underwent X-ray powder diffraction analysis. Results revealed significant variations in magnetic susceptibility across each profile under both in situ and laboratory conditions. In situ measurements ranged from −45 × 10⁻⁵ SI to 120 × 10⁻⁵ SI, while laboratory measurements ranged from 4.00 × 10⁻⁵ SI to 99.40 × 10⁻⁵ SI. The portable Kappameter KM-7 provided satisfactory results for preliminary investigations, while the Bartington MS2B System demonstrated high precision in analyzing these variations in detail. These findings support the potential for further investigations into magnetic susceptibility in karst cave environments, with an emphasis on understanding depositional history and the timeline of climate and tectonic changes.

The scarcity of well data and the inherent subjectivity of geological interpretations often leads to imprecise or oversimplified subsurface models. Traditional interpretation methods struggle with sparse datasets, necessitating the application of advanced machine learning techniques to enhance subsurface characterization. This study leverages artificial neural networks to predict lithology distribution using seismic attributes in the northern Croatian part of the Pannonian Basin System, an area with numerous exploratory wells. Seismic data, long employed as a supplementary interpretation tool, was used to generate a predictive lithological model, overcoming data limitations inherent to well-based methods. A key focus was the volume of shale, a lithological indicator, which was estimated using an extensive set of seismic attributes and processed through innovative data preparation techniques for artificial neural network analysis. A comprehensive artificial neural network based modelling approach was implemented over a 4365 km² 3D seismic dataset, targeting Pannonian (Late Miocene–Early Pliocene) sediments deposited in deltaic, turbiditic, and lacustrine environments. Results show that standardization of input data significantly improved model accuracy, particularly in capturing key geological features such as meandering sandstone-filled channels. In contrast, normalization led to unreliable predictions, while raw data substantially underestimated sandstone volumes. Despite its advantages, the method’s limitations stem from the inherent uncertainty in the volume of shale estimation and interpreter subjectivity. The approach is well-suited for geological settings with two or three dominant lithologies distinguishable on geophysical well logs. While applicable to coalbearing strata and shale-rich carbonates, its effectiveness in more complex geological settings requires further refinement. The findings highlight the untapped potential of legacy seismic data for geo-energy applications, including hydrocarbon exploration, geothermal studies, and carbon storage.

Deep saline aquifers in the eastern part of Drava Basin were screened for potential storage sites. The input dataset included three seismic volumes, a rather extensive set of old seismic sections and 71 wells. Out of all identified potential storage objects, only two sites were found to be situated in the favorable geological settings, meaning that the inspected wells drilled through structural traps had a seal at least 20 m thick which was intersected by only a few faults with rather limited displacement. Many more closed structures in the area were tested by exploration wells, but in all other wells, various problems were encountered, including inadequate reservoir properties, inadequate seal or inadequate depth of the identified trap. Analysis was highly affected by the insufficient quality and spatial distribution of the seismic input data, as well as in places with insufficient quality of input well datasets. An initial characterization of identified storage sites was performed, and their attributes were compared, with potential storage object B recognized as the one that should be further developed. However, given the depth and increased geothermal gradient of the potential storage object B, it is possible that it will be developed as a geothermal reservoir, and this brings forward the problem of concurrent subsurface use.