Oriol Oms

The Early Pliocene Warmth (EPW) was one of the most recent intervals of sustained global temperatures above present, but its expression in European terrestrial environments remains poorly constrained. Here we establish a continental chronological and paleoenvironmental framework for the Camp dels Ninots maar-lake succession (NE Spain) using integrated ⁴⁰Ar/³⁹Ar geochronology, magnetostratigraphy, and multiproxy analyses. Incremental-heating ⁴⁰Ar/³⁹Ar dating of welded spatter deposits yields an eruption age of 4.70 ± 0.07 Ma, anchoring the onset of subsequent lacustrine sedimentation. Correlation of the polarity record with the Geomagnetic Polarity Time Scale, combined with sedimentation-rate modelling, dates the fossil-bearing interval to ~ 4.42 Ma and constrains the terrestrial onset of EPW conditions at ~ 4.45 Ma. Palynological assemblages indicate increased arboreal pollen and reduced aridity indicators, while mineralogical data support enhanced effective precipitation. Vertebrate faunas, including ectotherms and large mammals associated with closed habitats, further indicate ecosystem restructuring under warm-humid conditions. The preservation and chronological control of Camp dels Ninots provide a rare terrestrial archive for assessing continental paleoenvironmental responses during the EPW in Europe.

This work presents a novel deep learning workflow for estimating porosity and permeability from combined data, where numerical variables such as high-resolution bulk density (RHOB) and photoelectric factor (PEF) data are integrated with X-ray computed tomography (X-CT) image data, using a dual-energy X-CT approach (DECT). Convolutional neural networks (CNNs) were calibrated with routine core analysis (RCAL) laboratory measurements from one well from Sinú-San Jacinto Basin (Colombia). The CNN architecture combines two main branches: An image branch, in which a CNN extracts spatial features from normalized X-CT sections using 3 × 3 convolution layers, ReLU activation, batch normalization, and maxPooling, and a numerical branch, which processes the input vectors corresponding to RHOB and PEF using fully connected dense layers and dropout regularization. Both branches are concatenated in a fusion layer, from which the model’s final predictions are made. Results indicate a strong correlation between porosity, permeability, RHOB and PEF logs, and CT images. The porosity model achieved excellent predictive performance, with an R² = 0.996, MAE = 3.96 × 10⁻³, MSE = 3.82 × 10⁻⁵, and 0.064 maximum error. The permeability model also performed well, with a linear R² = 0.983, though metrics reflected the wide dynamic range of permeability. Consequently, artificial neural networks (ANNs) can accurately predict porosity and permeability at various depths where no corresponding laboratory data exists, demonstrating excellent predictive capabilities over several rock intervals, in a high vertical resolution because of X-CT data scale (0.625 mm).

Reservoir petrophysical characterization is traditionally performed through the interpretation of well logs validated with routine core analysis (RCAL), often excluding the integration of other tools such as computed tomography (CT), which provides interpretation of higher resolution. In this study, artificial neural network (ANN) models were applied to estimate porosity and permeability by integrating conventional logs with CT-derived data (RHOB and PEF), thereby validating the petrophysical model of Ciénaga de Oro Formation. Neural networks were trained in MATLAB^® using a feed-forward regression network based on a multilayer perceptron (MLP) architecture, with RCAL measurements serving as a reference. Model performance was assessed by comparing predictions with laboratory data from two wells, yielding high accuracy (R² = 0.98 for permeability and R² = 0.90 for porosity) with mean absolute errors below 5%. Additional validation was performed using well logs and CT data from complete 3 ft sections, with the trained models successfully reproducing core heterogeneities at millimetric resolution. These results confirm the potential of integrating well logs and CT data with ANN to enhance petrophysical characterization and extend property estimation to wells lacking core or laboratory measurements. Furthermore, an interactive MATLAB^® tool was developed, enabling users to load well logs and CT files as flat inputs, generate high-resolution predictions, validate results, and export the estimated values.

This study develops a three-dimensional (3D) geostatistical model of the Ciénaga de Oro Formation in the southern Sinú–San Jacinto Basin (Colombia), integrating structural, sedimentological, and petrophysical data to identify new hydrocarbon storage-prone zones. The structural model was constructed from seismic interpretation, well log correlation, and velocity models derived from VSP and check shots. Sedimentological models were generated by means of facies definition through field—outcrops description, well-log analysis, integrating computed tomography and digital rock analysis (Digital SCAL), complemented by automatic facies classification through a multi-layer perceptron (MLP) neural network. In this framework, Petrophysical properties, including porosity, permeability, density and clay volume, were interpolated using geostatistical sequential Gaussian simulation (SGS) and kriging, accounting for directional anisotropy (N45W), using the previously defined structural model as a basis. Analysis of the ANH-SSJ-La Estrella-1X and ANH-SSJ-Nueva Esperanza-1X wells revealed reservoir variability: clean sandstones associated with distributary channels exhibited the highest quality (Φ > 20%, K > 1000 mD), while heterolithic sandstones linked to delta-front mouth bars were identified as new secondary reservoir-prone zones (Φ > 10%, K > 10 mD). The proposed methodology provides a robust, integrated and replicable workflow for reservoir characterization in complex sedimentary environments and reduces exploration uncertainty, supporting both prospect evaluation and development planning.

The combined sedimentological and palaeoecological analysis of charophyte-rich carbonate microfacies is proven to be a useful methodology for the palaeoenvironmental reconstruction of continental settings. However, the integration of these charophyte assemblages with geochemical proxies has not been explored, yet. In the present work, the charophyte-rich muddy carbonates of the Barremian La Pedrera de Meià Konservat-Lagerstätte (Southern Pyrenees, Spain) were studied from a taxonomic, taphonomic, and palaeoecological viewpoint, and the results were later integrated with previously published paleoenvironmental proxies (δ¹³C, δ¹⁸O, and elemental geochemistry). In the studied locality, monospecific Echinochara sp.–Charaxis spicatus meadows are only found in the temporary lakes recorded in the lower stages of lake infilling. The high Al, K, Fe and Ti concentrations and δ¹⁸O values previously described in these carbonates indicate meteoric infilling followed by evaporation periods. Freshwater and brackish communities are found in the upper stage of lake infilling. Freshwater settings had mixed meadows with Atopochara–Clavatoraxis, Clavatoroidae utricles–Clavatoraxis, and Ascidiella–Favargerella plants, while the brackish environments, that occurred laterally to freshwater, contain meadows dominated by porocharacean– Charaxis sp., and Echinochara sp.–Charaxis spicatus plants. Miliolids and broken dasycladaceans also occur in these facies. Sr/Ba ratios, REE + Y concentrations, and δ¹⁸O values previously reported in these lacustrine carbonates indicate prevalence of freshwater environments with occasional marine influence, which agrees with the occurrence of distinct brackish and freshwater charophyte assemblage and marine-affinity organisms, suggesting that during the last stage of lake evolution, the system was part of a coastal wetland. This work demonstrates that the integration of geochemical, palaeontological and palaeoecological datasets improves the understanding of the fossil continental carbonate settings and their evolution.

Noninvasive elemental XRF characterization of mudstone lagerstätten for provenance identification: Advantages and limitations

Deep-time (=pre-Quaternary) maar lakes and certain other, hydrologically deep volcanogenic lakes, are often excellent Konservat-Lagerstätten representing unique windows into past biota and ecosystems. Many deposits from such lakes contain animal and plant remains in extraordinary preservation, often with soft tissues or fine morphological and anatomical details preserved. Such Lagerstätten have the potential to provide in-depth information on a variety of organisms, which is important for understanding their biology and ecology, their evolution and palaeobiogeography, but also for elucidating entire ecosystems with their numerous biotic and abiotic interactions. The formation of such Lagerstätten is intimately linked to volcanic processes, amongst which phreatomagmatic explosions that formed maar-diatreme volcanoes are probably the most important, but also other volcanic processes can lead to the formation of deep volcanogenic lakes (e.g. in certain calderas). Maar lakes and other volcanogenic Konservat-Lagerstätten occur in a large number of volcanically active regions worldwide, although older deposits are often difficult to access as they are more likely to be eroded or covered by younger deposits. The accessibility of many of the better-known localities is often connected to the mining of natural resources, ranging from diamonds, to volcanic rocks such as basalts to the lacustrine sediments that may have filled volcanic craters, including diatomites and ‘oil-shales’. Most or even all of the maar and other volcanogenic lakes presented here in greater detail, can be considered as important geoheritage sites. Although currently some of these deposits have at least some kind of legal protection as monuments of natural heritage, others remain in danger of being exploited commercially for natural resources and hence, ultimately destroyed. Moreover, many scientific questions related to these ancient lakes and their biota covered here in more detail, as well as those related to lakes only briefly mentioned in passing, have not been posed, let alone answered. This makes maar lakes and other volcanogenic lakes important resources for present-day and future research. The present contribution should be seen as a global call to scientists to find further localities that represent similar volcanogenic lacustrine settings, as they may be the source of vital and surprising new information about the plants, animals, and environments of the past. Examples of pre-Quaternary maar and other volcanogenic lakes that are presented here in greater detail include the following localities: Paleocene: Menat (France); Eocene: Messel, Eckfeld (Germany), Mahenge (Tanzania); Oligocene: Enspel, Rott, Hammerunterwiesenthal, Baruth, Kleinsaubernitz (Germany); Miocene: Foulden Maar, Hindon Maar Complex (New Zealand), Randeck Maar, Hirnkopf-Maar, Höwenegg, Öhningen (Germany); Pliocene: Ruppach-Goldhausen (Germany), Camp dels Ninots (Spain).

The taphonomic study of two complete and anatomically connected individuals of Tapirus arvernensis from the Pliocene site of Camp dels Ninots (Caldes de Malavella, Spain) strengthens the attribution to a konservat-Lagerstätte deposit. The macroscopic analysis showed the absence of weathering, predation marks, and scarce superficial modification. Different surface colourations have been observed, highlighting white alteration. A selection of samples was analysed through ESEM-EDX, XRD and FTIR. Results suggest preservation of histological features and absence of microtunneling associated with biotic digestion of bioapatite. Specific white alteration of bone surfaces are attributed to a slightly different phase of the bone apatite, with higher crystallinity index and heavier loss in biogenic carbonates. Together with the presence of silicon-rich crusts and infillings that cover bone surfaces, it is now suspected that some interference of the volcanic activity that occurred in the past could have been responsible for an optimal preservation of the osteological material. A slow remineralisation could have been caused by hydrothermal activity still active in the area that caused the absence of bacterial activity in a lacustrine context and left the specimens undisturbed. These results could proportionate new data to understand fossil diagenetic mechanisms that could potentially allow exceptional preservation in maar contexts.

Despite the paleontological relevance of the terrestrial Early Pleistocene Venta Micena bonebed (Baza Basin, Spain), it lacks a comprehensive geochemical/sedimentological study. Here, we demonstrate that the 1.5-m-thick Venta Micena limestone formed in a relatively small freshwater wetland/pond located at the periphery of the large saline Baza paleolake. Two microfacies are observed, with high and low contents of invertebrate fossils, and which originated in the centre and margin of the wetland, respectively. X-ray diffraction (XRD) mineralogy and paleohydrological characterization based on ostracod and bulk-rock geochemistry (δ¹³C and δ¹⁸O) indicate that the limestone reflects a general lowstand of the Baza lake, permitting the differentiation of freshwater wetlands that were fed by adjacent sources. Conversely, during highstands, the Baza lake flooded the Venta Micena area and the freshwater fauna was replaced by a saline one. Bulk-rock isotopic data indicate that the lower interval C1 of the limestone (bone-rich in marginal settings) displays general negative values, while the upper interval C2 (bone free) displays less negative values. The bones of predated mammals accumulated in the marginal areas, which were flooded and buried by recurring water-table fluctuations. Lake dynamics played a critical role in bone accumulation, which was previously considered as representing a hyena den.