Petrological Data Research Articles

Understanding Groundwater Resource Vulnerability at Bryce Canyon National Park, Utah, Using Applied Geophysics at the Rubys Inn Thrust Fault

Abstract Recent development near Bryce Canyon National Park, Utah, could affect local groundwater usage, availability, and dependent resources. The National Park Service and Utah Geological Survey conducted a geophysical study targeting the Rubys Inn thrust fault. This fault lies between commonly targeted aquifers in Emery Valley and groundwater flow systems of the Paunsaugunt Plateau, which support springs and dependent ecosystems. Fault zone geometry and internal structure are complex, resulting in a heterogeneous permeability distribution that affects groundwater flow. The influence of fault zones on groundwater flow parallel and perpendicular to their planes is difficult to predict. Geophysical imaging can yield important information about subsurface fault geometry. We utilized electrical resistivity tomography (ERT) surveys to investigate the influence of the Rubys Inn fault on groundwater occurrence and movement along the southeast boundary of Emery Valley. We collected ERT data along three transects orthogonal to the mapped fault strike in May and September 2022. Where available, we used water-level and lithologic data to constrain ERT inversion model interpretations. The inversion models illustrate the complexity and variability of the Rubys Inn fault within a short distance along strike. Where the fault is concealed, results indicate that the actual and mapped locations differ by 70–100 m along the transects. Groundwater is well constrained in the hanging wall, but poorly constrained in the footwall, and some seasonal variation is discernible. Variable stratigraphy and structure are apparent in all transects. This study enables strategic placement of test wells that will further establish the influence of the Rubys Inn fault on the occurrence and movement of groundwater in and adjacent to the fault zone. The study demonstrates that ERT is a cost-effective and noninvasive tool for detecting the precise surface location and delineating subsurface fault geometry in otherwise data-poor areas with sensitive ecological or archaeological resources.

Lithology Prediction Using K-Nearest Neighbors (KNN) Algorithm Study Case In Upper Cibulakan Formation

Abstract Knowledge in the characterization and evaluation of hydrocarbon formations by identifying the type of lithology is an important step in oil and gas exploration. However, this method is not efficient enough because it requires a lot of time and effort. This study focuses on lithology predictions using log data input by applying one of the machine learning algorithms, namely K-Nearest Neighbors (KNN). This KNN algorithm can classify data based on K values to predict lithology. The Hyperparameter K value is determined based on the number of nearest neighbors calculated using the Euclidean distance principle. The K value in KNN needs to be optimized in order to find out the best K value to get high accuracy. The accuracy value of the model is obtained by comparing the results of the actual qualitative interpretation of lithology with the prediction results of lithology with KNN resulting precision, recall and F1 as representative of model accuracy. In the data train wells KP-24, KP-54 and KP-57 as well as test data, namely the KP-34 well, the value of k = 5 has the highest accuracy value of 89.9%. With the dominance of lithology in the predicted results, namely limestone, according to the information on the well data area, namely the Cibulakan Formation above and into the well, it reaches the Baturaja Formation. These results indicate that the lithology predicted by the KNN algorithm from the train data is already representative of the actual lithology data. Comparison of the results of qualitative interpretation with the results of machine learning predictions on the KP-34 well can predict thin or small layers and data labels in a relatively short time.

Geochemical studies of potential acid-forming classification materials to reduce acid mine drainage formation

Abstract Acid mine drainage (AMD) is acidic wastewater produced in coal mining operations due to sulfide mineral oxidation. In compliance with the regulations of good mining practice procedures, each mining operation must conduct a geochemical study of the distribution of material classification categories to identify the potential acid-forming (PAF) or not acid-forming (NAF) materials to mitigate the AMD. This research conducted a field observation at one of the post-mining lakes of a coal mining operation in South Kalimantan. It determined materials or rocks that have the potential for acid formation using static tests with the Net Total Acid Producing Potential (NTAPP) method. The results of coring samples were processed to obtain rock lithology data for four drilling points, demonstrating one layer of low-capacity PAF material in borehole point A, one layer of low-capacity PAF material, and one layer of PAF material in borehole point B. Only one layer of PAF material was in borehole point C and borehole point D. These PAF/NAF data highlighted essential information about PAF/NAF, underscoring the significant role of our work in improving the strength and accuracy of mitigation plans and reducing acid mine drainage.

Determination of Organic Carbon Content of the Soils within the Greenhouses Built on Pyroclastic Deposits in Isparta Settlement Area

Soil organic carbon (SOC) is an important indication of soil health and helps to sustain soil fertility. As a result, determining its composition and the factors that influence it is critical for long-term soil nutrient management, especially in controlled conditions such as greenhouses. This study utilizes machine learning to classify SOC content in greenhouses built on pyroclastic deposits in the Isparta region. A dataset of 276 samples and eight variables—clay (%), silt (%), sand (%), soil electrical conductivity (EC), pH, elevation, slope, and aspect—were used to model SOC values. SOC content was classified into five classifications: very low (2.3%). In this study, five machine learning models—Logistic Regression (LR), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF)—were evaluated using cross-validation to determine their classification accuracy, precision, recall, F-score, and ROC area. Random Forest (RF) and Decision Tree (DT) outperformed the other models, with RF achieving the highest overall accuracy (76.4%), precision (77.3%), and AUC (0.904), followed by DT at 75.4% and AUC of 0.874. This study shows the practicality of machine learning models in categorizing SOC content, highlighting their importance for long-term soil health and fertility control in greenhouse conditions. To improve model efficacy, future studies should include more auxiliary variables, such as soil physical and chemical qualities and lithological data, as well as a wider range of soil types.

Enhancement of the geological mapping in weathered plutonic and metamorphic rocks areas using village water supply wells data (lithology and hydrochemistry)

In weathered plutonic and metamorphic rocks areas, because rock outcrops are rare due to the extensive regolith cover, geological mapping is largely based on the interpretation of airborne data and imagery (aerial photographs, satellite images, airborne geophysics when available, etc.). In the sub-Saharan Africa, numerous village water supply campaigns were performed during the last 40 years. Most hydrogeological and geological data from these campaigns are stored and safeguard in country scale databases. In this study, we develop a methodology to improve the existing geological maps in a such geological context with lithological data from the existing databases. These data were not used during past geological mapping; yet they provide a complementary access to the lithology, notably in areas where outcrops are very scarce. We propose a coherent methodology to use and validate such geological data, complementary to field observations on the scarce outcrops, to cope with their uncertainties. We also show that groundwater hydrochemistry, namely the silica content, can be of use to complete the geological mapping. Using data from 735 boreholes drilled in the Koudougou and Léo square study area of Burkina Faso, we validate this new methodological approach and locally propose a more accurate 1:200,000 geological map.

Structural and Reservoir Characteristics of Potential Carbon Dioxide Storage Sites in the Northern South Yellow Sea Basin, Offshore Eastern China

The geological storage of carbon dioxide (CO2) in offshore saline aquifers stands as a primary option for reducing CO2 emissions in coastal regions. China’s coastal regions, particularly Shandong and Jiangsu provinces, face significant challenges in CO2 reduction. Therefore, evaluating the feasibility of CO2 geological storage in the adjacent seas is critical. To assess the suitability of a CO2 storage site, understanding its structural and reservoir characteristics is essential to mitigate injection and storage risks. In this study, we analyzed the structural characteristics and potential traps of the Yantai Depression in the South Yellow Sea Basin based on seismic data interpretation. We further conducted well logging analysis and post-stack seismic inversion to obtain lithological data, including acoustic impedance and sandstone content percentages from the Cenozoic Funing Formation, Dainan–Sanduo Formation, and Yancheng Formation. Our findings highlight that the Yantai Depression in the South Yellow Sea Basin exhibits diverse structural traps and favorable reservoir–caprock combinations, suggesting promising geological conditions for CO2 storage. This area emerges as a suitable candidate for implementing CO2 geological storage initiatives.

Real-Time Lithology Prediction at the Bit Using Machine Learning

Real-time drilling analysis requires knowledge of lithology at the drill bit. However, logging-while-drilling (LWD) sensors in the bottom hole assembly (BHA) are usually positioned 2–50 m (7–164 ft) above the bit (called the sensor offset), leading to a delay in real-time drilling analysis. The current industry solution to overcome this delay involves stopping drilling to perform a bottoms-up circulation for cuttings evaluation—a process that is both time-consuming and costly. To address this issue, our study evaluates three methodologies for real-time lithology prediction at the bit using drilling and petrophysical parameters. The first method employs a petrophysical approach, which involves using bulk density and neutron porosity predicted at the bit. The second method combines unsupervised and supervised machine learning (ML) for prediction. The third method employs classification algorithms on manually labeled lithology data from mud log reports, a novel approach used in this work. Our results show varying degrees of success: the bulk density versus neutron porosity cross-plot method achieved an accuracy of 58% with blind-well test data; the ML approach improved accuracy to 66%; and the Random Forest (RF) classification with manual labeling significantly increased accuracy to 86%. This comparative analysis of three different methodologies for lithology prediction has not been previously explored in the literature. While clustering and classification methods have been regarded as the most effective, our study demonstrates that they do not always yield the best result. These findings demonstrate that ML models, particularly the manual labeling approach, substantially outperform the petrophysical method. This new algorithm, designed for real-time applications, uses selected input parameters to effectively minimize problems associated with the sensor offset of LWD tools. It rapidly adapts to changes, offering a quicker and more cost-effective interpretation of lithology. This eliminates the need for time-consuming bottoms-up circulation to evaluate cuttings. Ultimately, this approach enhances drilling efficiency and significantly improves the accuracy of lithology prediction, notably in identifying interbedded geological layers.

Metamorphic and chronological records of early Permian continental collision in Beni Bousera granulites (Internal Rif belt): implications for the tectonic evolution of northern Morocco during Pangea construction

This work presents petrological data obtained from shielded mineral inclusions within large garnets from the Beni Bousera metamorphic unit (internal Rif belt, northern Morocco) combined with in situ U‒Th‒Pb dating of monazite inclusions. In the considered Beni Bousera metapelites, the occurrence of mineral inclusions of kyanite + rutile + plagioclase + K-feldspar + quartz ± graphite trapped in garnet cores is diagnostic of high-pressure granulite-facies metamorphism. Geothermobarometry combined with thermodynamic modelling yields minimal P ‒ T conditions of approximately 1.37–1.5 GPa and 780–795°C, consistent with the development of palaeogradients during crustal thickening in collision belts. A concordant U/Pb age of 281 ± 3 Ma is obtained from associated monazite inclusions in the same garnet cores. These new petrochronological data attest to the early Permian continental collision in northern Morocco. The obtained dataset is constrained with petrological and geochronological parameters available on other neighbouring segments of the Variscan belt. Within the framework of recently unified full plate reconstruction models, the presented tectonic scenario suggests that all these orogenic segments were built during the late Carboniferous–early Permian crustal thickening at the northwestern Gondwana margin in response to the convergence of Laurentia and Gondwana during the late stages of Pangaea construction.

Vertebrate taphonomy and taphofacies of the Capianga Member, Aliança Formation (Jurassic), Jatobá Basin, Brazil

In addition to the study of sedimentary facies, the reconstruction of paleoenvironments depends on a detailed understanding of the taphonomy of a fossil accumulation. The Capianga Member of the Aliança Formation (Middle to Late Jurassic of the Jatobá Basin, northeastern Brazil) reveals vertebrate fossil accumulations composed predominantly of disarticulated bone and osteoderms, scales, spines and isolated teeth from a lacustrine paleoenvironment. However, the taphonomic history of the accumulation has not yet been studied extensively. The present work aims to interpret taphonomic facies based on lithological data and the systematic collection of fossils from the Capianga Member of the Aliança Formation, located in the northeastern portion of the Jatobá Basin, mainly in the municipality of Ibimirim. Six lithofacies were identified: Fm – massive claystones, Fl – Shale laminated Lt – calcilutites, Lc – calcarenites, Gf – fibrous gypsum and Scl – calciferous sandstones. Two primary taphonomic classes were recognized, consisting essentially of disarticulated elements, including (1) incomplete, semi-complete, or rarely complete bioclasts (such as osteoderms and fish scales) and (2) small-sized, occasionally complete bioclasts (osteoderms and scales) that sometimes compose bonebeds. According to the vertebrate taphonomy characteristics, three taphofacies were identified, with the Taphofacies A and B occurring in calcarenites and the Taphofacies C in calcilutites. The interpretation of these taphofacies reveals a multi-episodic history of the lacustrine environment. The integrated model suggests that the genesis of the identified taphofacies is linked to the action of lowering the water level of the paleolake, as well as the agents responsible for transport and disarticulation. These agents are related to pre-burial sub-aerial exposure, the action of unidirectional turbidity currents in shallow waters, and the likely influence of storms.

Identifying suitable boreholes for irrigation in the bedrock regions of the Sahel

AbstractThis study addresses the critical challenge of optimizing borehole drilling techniques and predictive models to improve groundwater utilization for irrigation in Burkina Faso. Initially, the analysis involved drilling 22 boreholes as part of a photovoltaic micro‐sprinkler irrigation project (PRECIS), with only 11 deemed suitable for irrigation, highlighting the difficulty in achieving the required flow rate of 5 m3/h. To enhance the robustness of the study, additional data from 205 high‐yield boreholes provided by the Office National de l'Eau et de l'Assainissement (ONEA) were incorporated. These boreholes, primarily intended for potable water supply, had flow rates often exceeding 5 m3/h. This extensive dataset was crucial in identifying significant predictors of the project flow rate (Qproj), including the flow rate at the end of drilling (QEndBorh) and lithological factors. The predictive model combining QEndBorh and lithological data explained 73.7% of the variance in Qproj, with an adjusted coefficient of determination (R2adj) of 72.4%. The CART (classification and regression tree) regression model effectively identified branches with flow rates suitable for irrigation, such as Terminal Node 3 with a predicted Qproj of 6.67 m3/h and Terminal Node 4 with a predicted Qproj of 10.5 m3/h, demonstrating the model's robustness. These findings underscore the necessity of detailed lithological assessments and advanced predictive modelling to ensure efficient and reliable borehole drilling for irrigation purposes in regions with complex geological conditions.

Eccentricity control on fluvial sedimentation in the tropics during the Middle-Late Pennsylvanian icehouse (∼306–314 Ma, Upper Silesian Basin)

Far-field effects of the Late Paleozoic glaciation (∼340–260 Ma) recorded in well-dated stratigraphic intervals of the Pangea can be instrumental in detecting the short-term variability of icehouse climate and deconvolving the climate mechanisms. This study examines the Cracow Sandstone Series (CS), which provides a snapshot of the Middle to Late Pennsylvanian (∼306–314 Ma) fluvial sedimentation in the eastern equatorial Pangea (Upper Silesian Basin, ∼2°N paleolatitude). Spectral estimates of borehole lithological data suggest predominant ∼100-kyr eccentricity pacing of coal-bearing fluvial cycles and persistence of this pattern across the onset of Late Pennsylvanian aridification. The immediate climatic and depositional controls involve changes in seasonal precipitation along the Intertropical Convergence Zone and resulting fluctuations in sediment input. The prominence of eccentricity pacing and suppression of precession-scale variability in the fluvial environment contrasts with the frequency spectra of seasonal insolation series – an issue comparable to the “100-kyr problem” of the Late Pleistocene. The traditional explanation considers the eccentricity component being imposed as a far-field response to glaciation, analogous to the Pleistocene carbon-cycle feedback. Here we propose an alternative possibility that calls upon time-integrated insolation at the equator and the role of semi-annual wet/dry cyclicity in transferring variance from precession-scale insolation changes to the modulating eccentricity term. Autogenic processes in the fluvial system might have participated in “shredding” the precessional and semi-precessional signals. The alternative scenario is decoupled from high-latitude climate and would imply a muted climate sensitivity of the eastern equatorial Pangea to glaciation. The individual options cannot be evaluated with the Upper Silesian data alone, but offer testable hypotheses, potentially helpful in revealing the short-term structure of glaciation and climate teleconnections during the Late Paleozoic.

Petrophysical Parameters and Electrofacies Models of the Itararé Group Applying Multi-Resolution Graph-Based Clustering Method, Paraná Basin

Volume shale (Vsh) and effective porosity (Φe) were calculated and partially applied as petrophysical input parameters to generate electrofacies models using the Multi-Resolution Graph-Based Clustering method in sedimentary successions of the Itararé Group. The petrophysical parameters and electrofacies models were determined from geophysical data from two wells located in the eastern portion of the Paraná Basin. The stratigraphic intervals in each well (analogues of hydrocarbon reservoirs) allowed petrophysical analysis and the determination of electrofacies models based on gamma ray profiles, apparent density and neutron porosity, together with lithological data. The petrophysical parameters were calculated by different procedures, and the effective porosity results were applied as input parameters for electrofacies modeling. The electrofacies models were correlated to lithological data and patterns of gamma ray profiles and apparent density, as well as different types of porosity. The generated models provide differences related to the type of porosity, the method applied to calculate the effective porosity and present probable relationships with the lithological units of the wells.

Sinkholes Mapping in Tanjungsari, Gunung Kidul Regency, Yogyakarta: A Preliminary Data for the Assessment of Sinkhole’s Susceptibility

Abstract Tanjungsari district is located in Gunung Kidul Regency, Yogyakarta, known as the karst region where the dissolution process has taken place and caused some sinkhole occurrence. However, there is no any study that carry out the characteristic and the specific number of sinkholes presence in this area yet. Therefore, this study aims to create a sinkhole map in the study area with the observation of its physical characteristics based on some important data such as lithological data, geomorphological feature, existed sinkhole location as well as its physical characteristic that were collected by field observation and the secondary data evaluation. Limestone is the only lithology type was found in the study area and it is likely to be influenced by the dissolution process. Furthermore, there are more than 20 sinkholes were found with approximate 1m to 80 m in diameter and a few meters onward in depth. Some of them formed like a shallow bowl and some are vertical wall. Most of them associated with the gentle slope and the soil cover area. The results from the study will serve as important information for further detail study such as sinkhole’s susceptibility mapping.

Three‐Dimensional Probabilistic Hydrofacies Modeling Using Machine Learning

AbstractCharacterizing the 3D distribution of hydraulic properties in glacial sediments is challenging due to fine‐scale heterogeneity and complexity. Borehole lithological data provide high vertical resolution but low horizontal resolution. Geophysical methods can fill gaps between boreholes, providing improved horizontal resolution but low vertical resolution. Machine learning can combine borehole and geophysical data to overcome these challenges. However, few studies have compared multiple machine learning methods for predicting hydrofacies in glacial aquifer systems. This study uses colocated airborne electromagnetic resistivity and borehole lithology data to train multiple machine learning models and predict the 3D distribution of hydrofacies in glacial deposits of eastern Nebraska, USA. Random Forest, Gradient Boosting Classifier, Extreme Gradient Boosting, Multilayer Perceptron, and Stacking Classifier were used to model 3D probabilistic distributions of hydrofacies (sand and clay) at a grid size of 200 m × 200 m × 3 m. Comparison of the predicted 3D hydrofacies models shows that the probability distributions and the contrasts between hydrofacies vary. The classification metrics show that the Stacking Classifier model performed better than other machine learning models in predicting hydrofacies. Multi‐Layer Perceptron and Stacking Classifier models show sharp vertical transitions between the low and high sand probability while other machine learning models show gradual transitions. K‐means clustering was used to translate the Stacking Classifier model into a 4‐class hydraulic conductivity model. This study shows that machine learning methods advance our understanding of glacial hydrogeology by improving the vertical and horizontal resolution of hydrofacies distribution and resolving aquifer‐aquifer and stream‐aquifer connections.

Increasing the accuracy of oil recovery factor predictions by integrating lithology data

The object of research in the paper is the process of oil extraction during flooding. The Buckley-Leverett method, which is widely used to estimate oil production in flooding, has certain limitations that lead to uncertainty in the results. This paper proposes to extend the Buckley-Leverett algorithm by integrating lithological data. This approach allows to take into account the influence of geological characteristics of the formation on the process of displacement of oil by water, which leads to a significant increase in the accuracy of forecasting the oil production coefficient. The effectiveness of the proposed method is confirmed on the basis of data analysis of a real oil field. The methodology for calculating the oil recovery coefficient during flooding using lithological dissection is presented. In this work, the steps of determining the oil recovery coefficient were analytically determined, which achieves a certain degree of accuracy due to the inclusion of the lithological characteristics of the permeable zone of the formation. The basic calculation of the lithological distribution over the layer was performed using the Kriging method. To confirm the accuracy of the Buckley-Leverett method, taking into account lithological dissection, the use of data analysis, including an experimental histogram and a theoretical normal distribution plot, is proposed. For data analysis, one hundred cases of lithological distribution were generated using the Sequential Indicator Simulation method. The comparative analysis of the data of the experimental histogram and the theoretical graph of the normal distribution of the determination of oil recovery coefficients by the Buckley-Leverett method for cases with and without lithological dismemberment allows to quantitatively assess the accuracy of both studied options. On the basis of a real oil field, it is shown that the accuracy of oil recovery coefficients by the Buckley-Leverett method, taking into account lithological fragmentation, exceeds the similar method without taking into account lithological fragmentation by 11 %.

The Ottawa River Gneiss Complex revisited: definition of the metamorphic core and detachment zone of a large Grenvillian metamorphic core complex

Using new and published data, we synthesize the tectonic evolution of the Ottawa River Gneiss Complex (ORGC), the metamorphic core and detachment zone of a large mid- to late-Ottawan metamorphic core complex in the western Grenville Province. Field and petrologic data indicative of retrogression and exhumation, combined with maps and schematic crustal-scale sections, are used to document spatial and temporal relationships of multi-scale structures developed during its formation, of which the largest, termed mega-cross-folds and megaboudins, occur within and define the detachment zone. Mega-cross-folds, orogen-normal structures up to 70 km in length with coaxial constrictional fabrics in their hinge-lines, formed in a single phase of deformation during retrogression and exhumation. A cluster of asymmetric megaboudins, individually from 10–50 km long with granulite-facies cores and high-strain amphibolite-facies rims, similarly formed during syntectonic retrogression and exhumation of granulite-facies precursors. We argue the mega-cross-folds developed in a regime of regional transtension, whereas the megaboudin cluster formed by extensional inversion of an anastomosing early-Ottawan thrust system, with the strain patterns of both suggesting the detachment zone was the site of intense ductile flow between the stronger metamorphic core and cover. Comparison of these results with generic numerical models of extensional collapse of overthickened continental crust suggests the first-order tectonometamorphic features of the ORGC developed during necking of the upper crust and associated large-scale extensional flow of the mid and lower crust into the domiform necked region during collapse of the early-Ottawan thrust stack.

Three-dimensional geological modeling applied to multiscale heterogeneity of a reservoir analog: Paleocoastal deposits from the Rio Bonito formation, Paraná Basin

Coastal sandstones have high permoporosity and contain significant hydrocarbon reserves, although they present variable flow heterogeneities. The goal of this paper is to understand the distribution of potential reservoir-flow units in the Rio Bonito Formation (early Permian, Paraná Basin) and to investigate heterogeneities on multiscale. We use stratigraphic, sedimentological, 3D model, and petrological data to evaluate reservoir heterogeneities. System tracts were modeled by sectioning the entire succession into five zones. Eleven facies associations were modeled separately within each zone, using geostatistical analysis and different algorithms. The 3D model was validated by jackknife procedure, and the distribution of facies associations adequately represented both depositional and stratigraphic frameworks. The results are adequate in a curve of accommodation changes similar to previous proposal for the study area. Tidal sand bar facies association presents as elongated (parallel to depositional dip) to sheetlike geobodies according to amalgamation grade, while upper and middle shoreface one is mostly elongated (parallel to depositional strike) to sheetlike. Besides, fluvial channel facies association occurs mainly elongated parallel to depositional dip, forming multilateral and multistory geobodies. Modeled depositional geometries were distinguished along the succession, showing similarities to Rio Bonito Formation outcrops, recent environments, and other deposits around the world, such as estuarine strata from Oriente Basin and shoreface ones from Gulf of Mexico Basin. Using a detailed petrological analysis, eleven reservoir petrofacies were defined and classified into good-, medium-, and low-quality reservoirs or non-reservoirs. Tidal sand bar, upper-middle shoreface, and fluvial channel deposits were categorized as the main reservoir-flow units. This study provides predictive scenarios for heterogeneities in reservoirs and may be applied in petroleum fields.

Identifying the origin of springs in weathered-fractured crystalline aquifers using a hydrogeophysical approach

Over the last few decades, important advances have been made in the development of relevant hydrogeological conceptual models for crystalline aquifers, and notably for weathered-fractured crystalline aquifers. Paradoxically and contrary to other types of aquifers, these researches never aimed at characterizing springs, the places were groundwater naturally outflows from such aquifers. With such an objective, our methodological approach consisted first of a lithological and hydrogeological description of the aquifer system based on borehole data and outcrops in a representative weathered-fractured crystalline aquifer (Daloa, Ivory Coast). Next, electrical resistivity tomography (ERT) has been used (after validating the appropriate inversion method) to provide the imagery of the weathering profile both below the plateaus and in the valleys where the springs outflow. Piezometric and river discharge data were also processed notably to determine the direction of groundwater flow. Results demonstrate unambiguously that the isalterites aquifer supplies the springs, and that the underlying fractured layer is not directly implied in this supply. ERT combined with borehole and field lithological data also shows that the lateritic formations (alloterites) present near surface below the plateaus, as well as the upper part of the isalterites, were eroded in the valleys, but not deep enough to let the fractured layer outcrop. This conceptual model for springs not only provides a basis for characterizing such complex aquifers, but also provides technical guidance for spring catchment and groundwater protection in these crystalline areas.

The central and southeast offshore Otway Basin well folio

Geoscience Australia (GA) has produced a folio of 32 wells across the central and southeast regions of the Otway Basin. This folio covers the areas from Normanby 1 on the Normanby Terrace, through the Shipwreck Trough and Nelson Sub-basin, to Whelk 1 in the southeast. Composite logs for each well in the folio include wireline logs, petrophysical analysis, interpreted lithology, organic geochemical data, organic petrology data, and sequence stratigraphic markers. This folio also includes core-based depositional environment (DE) and gross depositional environment (GDE) interval interpretations which were used to constrain wireline interpretation of DE/GDE away from core control. The folio includes the digital data package used to construct each well composite. The new folio complements a recently published folio of northeast offshore Otway Basin wells, with both designed as resources to support exploration in the offshore Otway Basin.

Calcium isotopic composition of the bulk silicate Earth: A komatiite perspective

Calcium (Ca) isotopic composition of the mantle has been previously estimated as δ44/40Ca. However, δ44/40Ca of the mantle records both its stable isotopic composition and excess/deficit in radiogenic 40Ca that can be produced by the decay of 40K. Here, we present the high-precision Ca isotopic compositions of 16 Archean komatiites from five representative localities (Barberton, Munro, Abitibi, Yilgarn, and Taishan). Due to the high degrees of partial melting that led to their formation, these komatiites are used here to simultaneously estimate ε40/44Ca, δ44/40Ca, and δ44/42Ca of the bulk silicate Earth. The komatiites exhibit a resolvable negative ε40/44Ca relative to SRM915a, with an average of −0.6 ± 0.1 (2SE, 95 c.i.% if not specified). Given the lack of significant differences among the samples and the non-zero value of ε40/44Ca, we suggest using δ44/42Ca to report the stable Ca isotopic composition in this study. Excluding one sample (SD6/400), which may have been affected by alteration, the remaining komatiites display relatively homogeneous δ44/42Ca, ranging from 0.39 ± 0.02‰ (2SE, N = 16) to 0.49 ± 0.02‰ (2SE, N = 10), defining a mean of 0.44 ± 0.02‰ (2SE, N = 15). The absence of correlations between δ44/42Ca and LOI, Sr/Nd, (Dy/Yb)N, and (La/Sm)N among the komatiites indicates that post-eruption alteration, the influence of residual garnet, as well as prior melt extraction from the mantle source have had a negligible influence on their stable Ca isotopic compositions. Based on available experimental petrological data and isotope fractionation factors, it is demonstrated that komatiites were insignificantly fractionated from their mantle sources (i.e., <0.02% in δ44/42Ca). Their δ44/42Ca represents the ambient mantle at the time of segregation. Accordingly, we suggest that the average δ44/42Ca and ε40/44Ca of the komatiites measured here are representative of the bulk silicate Earth. Our new estimate can serve as a reference point for Ca isotopes as a two-dimensional tracer for sources and geological processes.