Igneous Rock Types Research Articles

Characteristics of Host Rocks Manganese of The Anabanua Village Barru District South Sulawesi Province, Indonesia

One of the prospects for a wealth of geological resources that can be utilized for the benefit of mankind is manganese metal mineral resources. In Anabanua Village, especially at the research location, there is an indication of manganese mineralization that the type of rock carrying the mineralization is not yet known. The purpose of this study was to determine the chemical elements of metallic minerals, mineralogy, and types of mineralization-carrying rocks, as many as three samples in the form of chunks, which were analyzed using megascopic analysis methods identifying the texture and structure of carrier rocks, XRD (X-Ray Diffraction) analysis minerals, and XRF (X-Ray Fluorescence). The characteristics of manganese mineralization carrier rocks consist of metallic elements Mn (0.046%-20.455%), Fe (1.555%-3.673%), and nonmetallic elements SiO2 (11.403%-48.165%), K2O (0.398%-4.177%). Mineralogy of manganese mineralization carrier rocks are roeblingite (Pb2Ca6Mn2+(Si3O9)2(SO4)2(OH)2·4H2O), rhodonite (CaMn3Mn[Si5O15]), diopside (CaMgSi2O6), calcite (CaCO3), kieserite (Al, Ga)2(GeO4)(OH)2), zeolite (Mn2O.Al2O3.xSiO .yH2O), and palygorskite ((Mg, Al)2 Si4O 10(OH)·4H2O). Manganese mineralization host rocks are determined by referring to the SiO2 (%weight) and K2O(%weight) diagrams to produce basalt igneous rock types.

An integrated remote sensing, petrology, and field geology analyses for Neoproterozoic basement rocks in some parts of the southern Egyptian-Nubian Shield

The main objective of this study was to use deep learning, and convolutional neural networks (CNN), integrated with field geology to identify distinct lithological units. The Samadia-Tunduba region of the South Eastern Desert of Egypt was mapped geologically for the first time thanks to the use of processed developed CNN algorithms using Landsat 9 OLI-2, which were further enhanced by geological fieldwork, spectral measurements of field samples, and petrographic examination. According to previously published papers, a significant difference was observed in the distribution of rocks and their boundaries, as well as the previously published geological maps that were not accurately compatible with the nature of the area. The many lithologic units in the region are refined using principal component analysis, color ratio composites, and false-color composites. These techniques demonstrated the ability to distinguish between various igneous and metamorphic rock types, especially metavolcanics, metasediments, granodiorite, and biotite monzogranite. The Key structural trends, lithological units, and wadis affecting the area under study are improved by the principal component analysis approach (PC 3, 2, 1), (PC 2, 3, 4), (PC 4, 3, 2), (PC 5, 4, 3), and (PC 6, 5, 4) in RGB, respectively. The best band ratios recorded in the area are recorded the good discrimination (6/5, 4/3, and 2/1), (4/2, 6/7, and 5/6), and (3/2, 5/6, and 4/6) for RGB. The classification map achieved an overall accuracy of 95.27%, and these results from Landsat-9 data were validated by field geology and petrographical studies. The results of this survey can make a significant difference to detailed geological studies. A detailed map of the new district has been prepared through a combination of deep learning and fieldwork.

An ensemble-based strategy for robust predictive volcanic rock typing efficiency on a global-scale: A novel workflow driven by big data analytics

Laboratory measurements, paleontological data, and well-logs are often used to conduct mineralogical and chemical analyses to classify rock samples. Employing digital intelligence techniques may enhance the accuracy of classification predictions while simultaneously speeding up the whole classification process. We aim to develop a comprehensive approach for categorizing igneous rock types based on their global geochemical characteristics. Our strategy integrates advanced clustering, classification, data mining, and statistical methods employing worldwide geochemical data set of ~25,000 points from 15 igneous rock types. In this pioneering study, we employed hierarchical clustering, linear projection analysis, and multidimensional scaling to determine the frequency distribution and oxide content of igneous rock types globally. The study included eight classifiers: Logistic Regression (LR), Gradient Boosting (GB), Random Forest (RF), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), and two ensemble-based classifier models, EN-1 and EN-2. EN-1 consisted of LR, GB, and RF aggregates, whereas EN-2 comprised the predictions of all ML models used in our study. The accuracy of EN-2 was 99.2 %, EN-1 achieved 98 %, while ANN yielded 98.2 %. EN-2 provided the best performance with highest initial curve for longest time on the receiver operating characteristic (ROC) curve. Based on the ranking features, SiO2 was deemed most important followed by K2O and Na2O. Our findings indicate that the use of ensemble models enhances the accuracy and reliability of predictions by effectively capturing diverse patterns and correlations within the data. Consequently, this leads to more precise results in rock typing globally.

Experiments on image data augmentation techniques for geological rock type classification with convolutional neural networks

The integration of image analysis through deep learning (DL) into rock classification represents a significant leap forward in geological research. While traditional methods remain invaluable for their expertise and historical context, DL offers a powerful complement by enhancing the speed, objectivity, and precision of the classification process. This research explores the significance of image data augmentation techniques in optimizing the performance of convolutional neural networks (CNNs) for geological image analysis, particularly in the classification of igneous, metamorphic, and sedimentary rock types from rock thin section (RTS) images. This study primarily focuses on classic image augmentation techniques and evaluates their impact on model accuracy and precision. Results demonstrate that augmentation techniques like Equalize significantly enhance the model's classification capabilities, achieving an F1-Score of 0.9869 for igneous rocks, 0.9884 for metamorphic rocks, and 0.9929 for sedimentary rocks, representing improvements compared to the baseline original results. Moreover, the weighted average F1-Score across all classes and techniques is 0.9886, indicating an enhancement. Conversely, methods like Distort lead to decreased accuracy and F1-Score, with an F1-Score of 0.949 for igneous rocks, 0.954 for metamorphic rocks, and 0.9416 for sedimentary rocks, exacerbating the performance compared to the baseline. The study underscores the practicality of image data augmentation in geological image classification and advocates for the adoption of DL methods in this domain for automation and improved results. The findings of this study can benefit various fields, including remote sensing, mineral exploration, and environmental monitoring, by enhancing the accuracy of geological image analysis both for scientific research and industrial applications.

Recycling of Paleo-Tethyan oceanic crust: Geochemical record from Early–Middle Triassic igneous rocks in the East Kunlun Orogen in western China

Abstract Deciphering the contribution of crustal materials to generation of mafic arc igneous rocks at different subduction stages is of great significance to unravel the fate of the subducted paleo-oceanic crust. Here we present an integrated geochemical study on two types of early Mesozoic mafic arc igneous rocks from the East Kunlun Orogen. Zircon U-Pb isotopic analyses yield ages of 252–248 Ma for lamprophyres and 239–238 Ma for diorite porphyries. All the samples display arc-like trace element distribution patterns, high zircon δ18O values, and variably low zircon εHf(t) values. However, significant geochemical distinctions exist in terms of trace element concentrations, radiogenic isotopes, and other geochemical variations between them. The Early Triassic lamprophyres are characterized by significant enrichment in fluid-mobile trace elements and weakly enriched whole-rock Sr-Nd-Hf isotopes, whereas the Middle Triassic diorite porphyries show high contents of light rare earth elements, Th, Zr, and Hf, and more enriched Sr-Nd-Hf isotopes. Furthermore, the lamprophyres exhibit remarkably higher ratios of Ba/Th, Ba/La, K/La, and Sr/Nd and slightly higher ratios of La/Sm, Th/Yb, and Th/La than mid-oceanic-ridge basalt (MORB), while the diorite porphyries display higher La/Sm, Th/Yb, Th/Nd, and Th/La ratios compared to normal MORB but closer to those of seafloor sediments. Taken together, these differences can be attributed to the incorporation of two distinct slab liquids into their mantle sources, including oceanic slab-derived aqueous solutions and minor sediment-derived hydrous melts for the formation of the lamprophyres, and sediment-derived hydrous melts for the formation of the diorite porphyries. As a result, we suggest the lamprophyres were generated during the Early Triassic subduction of the Paleo-Tethyan oceanic crust, while the diorite porphyries may be generated due to rollback of the subducting oceanic slab in response to the closure of the Paleo-Tethyan Ocean basin. Therefore, the studied Early–Middle Triassic mafic igneous rocks provide important evidence for the recycling of the Paleo-Tethyan oceanic slab at different stages.

Petrogenesis of the eudialyte-bearing syenite and indication for Nb-Zr-REE mineralization in Bashisuogong, Northwest China

The Bashisuogong alkaline igneous intrusion is located between the South Tianshan Orogenic Belt and the Kepingtage foreland thrust belt at the northern margin of the Tarim Craton and hosts economically significant Nb–Ta–Zr–rare earth element mineralization. Eudialyte has recently been discovered in the syenite unit of this intrusion, which is the primary host mineral for high-field-strength and rare earth elements. Based on detailed petrographic investigations, this study investigated the behavior of trace elements during magma evolution and the enrichment of ore-forming elements using whole-rock geochemical analyses of eudialyte-bearing syenite and compositional analyses of aegirine–augite and different types of eudialyte. We also undertook in situ titanite U-Pb dating. The Bashisuogong syenite comprises aegirine–augite and aegirine–augite–eudialyte syenite, the latter of which have higher total rare earth element contents. Both types of syenite exhibit slight enrichments in light rare earth elements, significant enrichments in high-field-strength elements (Nb, Ta, Zr, Hf, and Th), depletions in large-ion lithophile elements (Ba and Sr), and large negative Eu anomalies. There are two types (I and II) of eudialyte. Eudialyte I has higher Mn/Fe, Zr/Hf, and Nb/Ta ratios but lower Th/U ratios compared with eudialyte II but similar Y/Ho ratios. Eudialyte II crystallized earlier than eudialyte I, and aegirine–augite, titanite, and apatite crystallized earlier than eudialyte I. Both aegirine–augite and eudialyte have similar trace element characteristics to the host rocks, exhibiting enrichments in highly incompatible high-field-strength and rare earth elements, as well as marked negative Eu anomalies and depletions in Sr. These characteristics suggest that the Bashisuogong alkaline rocks formed by low-degree partial melting of geochemically enriched, metasomatized lithospheric mantle, which formed an alkaline basaltic parental melt that then underwent protracted magma evolution and fractionation in the shallow crust. The eudialyte syenite yield a titanite U-Pb age of 277.3 ± 1.2 Ma, which is consistent with the ages of different types of alkaline igneous rocks in the study area, indicating they were the products of the same magmatic event. Temporally and spatially, the Bashisuogong ore-bearing alkaline rocks were associated with the Tarim mantle plume, and the mantle plume provided the heat for their formation.

Characterization of Silica Nanoparticles from Pumice as an Aerogel Adsorbent

Pumice is often found around the banks of rivers, this stone is a type of igneous rock formed from volcanic eruptions. One of the compounds contained in pumice is silica. Therefore, the synthesis of silica nanoparticles from pumice using the sol gel method was used because it is simpler and more efficient in terms of cost and processing time. the initial step was by reacting pumice powder and NaOH at 70°C - 80°C then synthesized by adding 2M HCI to form a gel or white precipitate, soaking in ethanol, teos, hexane solutions was then synthesized to become an aerogel. Silica synthesis results into silica aerogels were characterized by FTIR and XRF. From FTIR silanol and siloxane functional groups were found, and the SiO2 composition increased to 93,299% after synthesis.

Correlation between Static and Dynamic Young’s Modulus of Elasticity of Different Types of Rocks

Correlation between static and dynamic elastic modulus in rocks has often been addressed in various studies. In this study, the correlation between the static and dynamic elastic modulus of six different sedimentary, metamorphic and igneous rock types namely coarse-grained sandstone, fine-grained sandstone, schist, quartzite, basalt and granite are studied. Physical properties such as bulk density and porosity are evaluated of all samples. Static elastic modulus is determined by uniaxial compression test and dynamic elastic modulus is found out by ultrasonic pulse velocity testing. Scanning Electron Microscope experiment, X-Ray Diffraction experiment are also conducted on all the samples for mineralogical and petrological studies. The individual correlation between the static and dynamic elastic modulus of all the rock types have been proposed using linear regression with zero intercept and high values of coefficient of determination. These equations are useful in calculating the static elastic modulus using non-destructive techniques, in a wide range of rock materials. Finally, a general linear equation has been developed to relate ratio of static and dynamic elastic modulus with density of the rock.

Sedimentological and Mineralogical Fingerprint of the Beach Sediments, Western Mediterranean Coast, Egypt

The composition and texture of beach sediments along continental coastlines vary considerably. Beach sands made completely of carbonate sediments are prevalent along Egypt's Western Mediterranean Coast. Forty-five sediment samples were collected from various locations (El-Dekhela, Kilo-21, Abu Talat, and Sidi Krir) along the Western Mediterranean Coast of Egypt. The sedimentological and mineralogical attributes of the collected sediments were investigated using collaborative techniques. The beach sediments in the coastal region between El-Dekhela and Sidi Krir consist mainly of carbonate sands that are mineralogically composed of dolomite, calcite, and aragonite with smaller amounts of quartz, sylvite, anhydrite, gypsum, and trace amounts of microcline. They contain ooids with bioclasts and very few heavy minerals, except for notable amounts of these minerals in the El-Dekhela region. These heavy minerals primarily consist of opaque minerals, amphiboles, and pyroxenes, with smaller amounts of epidote, zircon, tourmaline, rutile, garnet, kyanite, monazite, sphene, staurolite, and biotite. The combination of heavy minerals in these deposits indicates a wide variety of igneous, metamorphic, and sedimentary rock types as potential source rocks. Heavy mineral concentrations decrease westward from the Nile River's mouth near Rosetta to Egypt's Western Mediterranean Coast. Most of the studied ooids are white colored and usually have a pearly luster; these characteristics indicate that these sediments were formed in agitated water. The current study reveals that the ooids in the study area originated from a variety of sources, including autochthonous and allochthonous ooids that eroded and broke, implying that they may have originated from coastal plain carbonate ridges.

Characterization of Silica Nanoparticles from Pumice as an Aerogel Adsorbent

Pumice is often found around the banks of rivers, this stone is a type of igneous rock formed from volcanic eruptions. One of the compounds contained in pumice is silica. Therefore, the synthesis of silica nanoparticles from pumice using the sol gel method was used because it is simpler and more efficient in terms of cost and processing time. the initial step was by reacting pumice powder and NaOH at 70°C - 80°C then synthesized by adding 2M HCI to form a gel or white precipitate, soaking in ethanol, teos, hexane solutions was then synthesized to become an aerogel. Silica synthesis results into silica aerogels were characterized by FTIR and XRF. From FTIR silanol and siloxane functional groups were found, and the SiO2 composition increased to 93,299% after synthesis.

Trace elements and Li isotopes distinguish between liquid and solid phases contributing to mafic arc magmas

It is generally accepted that metasomatism of the mantle wedge peridotite by subducting slab-derived fluids plays a key role in dictating the composition of mafic arc magmas. However, this fluid metasomatism model has been challenged recently by the mélange diapirism model. In order to distinguish between liquid and solid phases that would exclusively contribute to mafic arc magmas, we have carried out an integrated study of whole-rock and mineral geochemistry for two types of contemporaneous mafic igneous rocks (gabbroic diorites and diorite dikes) from an accretionary orogen. The results indicate primary contributions from liquid phases composed of not only slab-derived aqueous solution but also seafloor sediment-derived hydrous melt. Although these mafic rocks all exhibit typical arc-like trace element distribution patterns, they show a series of differences in stable Li and radiogenic Sr–Nd–Hf isotope compositions as well as other geochemical variables. In general, the gabbroic diorites are characterized by enrichment in fluid-mobile elements (e.g., Rb, Ba, K, Pb, and Sr), high δ7Li and δ18O values, and depletion in Sr–Nd–Hf isotope compositions. By contrast, the diorite dikes exhibit enrichment in melt-mobile elements (e.g., LILE, LREE and Th), relatively low δ7Li values, and slight enrichment in Sr–Nd–Hf isotope compositions. There are also systematic differences and pertinent variations between Li isotope compositions and slab-derived fluid indicators such as whole-rock Rb/Nd, Sr/Nd, Nb/U, Th/La, Th/Nd and Th/Yb ratios for the two types of mafic igneous rocks. These indicate that the mantle sources of these mafic rocks would possess geochemical signatures that were acquired through chemical metasomatism by slab-derived fluids rather than physical mixing with mélange diapirs. Furthermore, the geochemical signatures allow for distinction between the oceanic slab-derived aqueous solution and the seafloor sediment-derived hydrous melt. This qualitative interpretation is quantitatively confirmed by model calculations of trace elements and Sr–Nd–Li isotopes in the two types of mafic igneous rocks. Therefore, the target mafic igneous rocks provide the geochemical evidence for the formation of their mantle sources through chemical metasomatism by incorporating the two types of metasomatic agent into the mantle wedge. This demonstrates a strong preference for the fluid metasomatism model over the mélange diapirism model for the origin of mafic arc magmas.

Estimating the thermal conductivity of plutonic rocks from major oxide composition using machine learning

SUMMARY The accurate estimation of temperature distribution in the earth's crust and modelling of heat-related processes in geodynamics requires knowledge of the thermal conductivity of plutonic rocks. This study compiled an extensive data set of 530 representative plutonic rock samples, including thermal conductivity, major oxide composition and (for two subsets of data) modal mineralogy. For the first time, three machine learning algorithms (ML; i.e. support vector regression, random forest and extreme gradient boosting) were employed to estimate the thermal conductivity of plutonic rocks using the major oxide composition feature as input variables. The performance of these ML-based models was evaluated against a geochemically compositional model and eight mineral-driven physically based empirical mixing models. Results show that the means of predicted thermal conductivity by the ML-based models and the geochemically compositional model are not significantly different from the measured thermal conductivity at a significance level of 5 per cent. However, the ML-based models outperformed the best-performing non-ML model, the geochemically compositional model. The highest prediction accuracy was achieved by extreme gradient boosting, which reduced the mean absolute percentage error and root mean square error by more than 50 per cent. Furthermore, SiO2 is confirmed as the most important independent variable, followed by Al2O3, TiO2, CaO and K2O. The turning point observed in the thermal conductivity trend with SiO2 wt per cent may be primarily attributed to variations in mineral composition within the subgroup of igneous rock types classified based on SiO2 wt per cent. This study explores, for the first time, the use of ML algorithms to estimate the thermal conductivity of plutonic rocks from their major oxide composition.

Formation of granitic pegmatites during orogenies: Indications from a case study of the pegmatites in China

Granitic pegmatites are a type of igneous rock with very coarse-to gigantic-sized textures, and are the primary source of rare metals (e.g., Li, Be, Nb, and Ta) and gem resources. Their formation is closely related to plate movements and crustal growth that occurred during an orogeny. In order to study the formation patterns of pegmatites and their controlling factors during orogeny, we collected the isotopic ages and compositions of granite-pegmatite fields in the ten major pegmatite belts identified in China. Pegmatites in China first formed in the North China Craton at ∼ 2.7 Ga, with the greatest number of mapped pegmatites having formed during the Mesozoic Era. Over geologic time, the pegmatites type tended to change from abyssal pegmatites to muscovite pegmatites to predominantly the LCT-type pegmatites. Pegmatites that formed within a single orogenic cycle usually crystallized during a brief time period. Within an orogenic belt that was subject to multiple orogenies, different pegmatite groups are associated with the orogenies; the pegmatite groups tend to increase in terms of size, numbers and mineralization intensity from the old to the young orogenic cycle. The pegmatite lineage, identified in the orogenic history of China Mainland, indicates that the convergences of micro-blocks in China constrained pegmatite formation in China. Anataxis of the metasediments (i.e., metapelites), as demonstated by their isotopic compositions, during the orogenies produced the granitic-pegmatitic melts. During the Earth’s crust evolution, the increasing maturity of the pegmatite source-rock metasediments promoted the occurrences of large pegmatites with great degrees of rare element mineralization in the Mesozoic Era in the Songpan-Ganze-West Kunlun and Altay orogenic belts, and the common formation of spodumene-subtype pegmatite rather than petalite-subtype pegmatites in the Phanerozoic orogenies in China. The Archean metasediments in the North China Craton, due to their low maturity with few terrigenous components, did not produce large LCT-type pegmatites. Accordingly, recognizing the linkage of metasediments within the orogenies to pegmatite formation can point to potential prospecting areas for new rare metal deposits. Thick metapelites within their structural-metamorphic domes are important markers of pegmatite prediction. In addition, granites that formed within the pegmatite-forming peak periods during orogenies may preferentially produce pegmatites relative to other time periods.

Petrogenetic and tectonic implications of Neoproterozoic igneous rocks from the western Yangtze Block, South China

Spatiotemporal variations in magma sources and the petrogenetic types of igneous rocks generally record major changes in tectonic styles and crustal growth mechanisms and thus play vital roles in tectonic reconstruction. In this study, we present new petrological, geochronological, geochemical and Sr-Nd-Hf isotopic data for Neoproterozoic igneous rocks in the Western Yangtze Block (WYB), South China, aiming to constrain their petrogenesis and tectonic implications. Geochronological and geochemical data compilations indicate a prolonged (ca. 910 to 730 Ma) Andean-type magmatic arc system in the WYB; however, the initial magmatism and subsequent magmatic flare-up events in different regions of the WYB are asynchronous. Petrogenetic study reveals that most Tonian mafic rocks exhibiting typical arc-related geochemical affinities and depleted Nd-Hf isotopes are generated by the partial melting of mantle wedge that is metasomatized by subduction-related fluids and/or melts. Elemental and isotopic studies suggest that the newly identified ca. 880–851 Ma adakitic rocks in the WYB are derived from melting of thickened juvenile or ancient continental crust, while the studied A2-type and I-type granitoids originate from differentiation of mantle-derived magma or reworking of continental crust, which are the key mechanisms of crustal evolution in the WYB. This study indicates that the Yangtze Block probably lies on the periphery of the Rodinia supercontinent, and long-lived arc magmatism including mafic magma underplating and crustal reworking, and episodic magmatic flare-up that occur due to slab rollback play key roles in Neoproterozoic continental evolution of the WYB.

Brittle-ductile transition stress of different rock types and its relationship with uniaxial compressive strength and Hoek–Brown material constant (mi)

Rocks deformed at low confining pressure are brittle, which means that after peak stress, the strength declines to a residual value established by sliding friction. The stress drop is the variation between peak and residual values. But no tension reduction takes place at high confining pressure. A proposed definition of the brittle-ductile transition is the transition pressure at which no loss in strength takes place. However, studies that consider information about the brittle-ductile transition, the criterion's range of applicability, how to determine mi, and how confining pressures affect mi's values are scarce. This paper aims to investigate the link between brittle-ductile transition stress, uniaxial compressive strength and Hoek–Brown material constant (mi) for different kinds of rock. It is essential to accurately determine the brittle-ductile transition stress to derive reliable values for mi. To achieve this purpose, a large amount of data from the literature was chosen, regression analysis was carried out, and brittle-ductile transition stress (σTR) was determined based on the combination of Hoek–Brown failure criteria and the recently used brittle-ductile transition stress limit of Mogi. Moreover, new nonlinear correlations were established between uniaxial compressive strength and Hoek–Brown material constant (mi) for different igneous, sedimentary and metamorphic rock types. Regression analyses show that the determination coefficient between σTR and UCS for gneiss is 0.9, sandstone is 0.8, and shale is 0.74. Similarly, the determination coefficient between σTR and mi for gneiss is 0.88. The correlation between Hoek–Brown material constant (mi) and σTR was not notable for sedimentary and metamorphic rocks, probably due to sedimentary rocks' stratification and metamorphic ones' foliation.

Examination of the accuracy of SHRIMP U–Pb geochronology based on samples dated by both SHRIMP and CA-TIMS

Abstract. Estimations of the reproducibility of U–Pb ages from SHRIMP (Sensitive High-Resolution Ion MicroProbe) instruments are based on data from studies that are nearly 2 decades old. Since that time, refinement of analytical procedures and operational improvements have reduced the historically identified uncertainties of SHRIMP U–Pb analysis. This paper investigates 36 SHRIMP thermal ionisation mass spectrometry (TIMS) double-dated “real-world” geologic samples from a variety of igneous rock types to better understand both geological and analytical sources of disagreement between the two dating methods. Geoscience Australia's (GA) use of high-precision chemical abrasion thermal ionisation mass spectrometry (CA-TIMS) for chronostratigraphy in Australian sedimentary basins has produced a substantial selection of precisely dated zircons, which we can use to cross-correlate the SHRIMP and CA-TIMS ages throughout the Phanerozoic. A total of 33 of the 36 ages were reported with external SHRIMP uncertainties less than 1 % (95 % confidence). Six of eight cases where the CA-TIMS age was outside the SHRIMP uncertainty envelope were in samples where the 95 % confidence interval of the reported SHRIMP age was below 0.66 % uncertainty, suggesting that SHRIMP analyses of untreated zircon with smaller uncertainties are probably overoptimistic. The mean age offset between SHRIMP and TIMS ages is 0.095 %, but the distribution appears bimodal. Geological explanations for age discrepancies between SHRIMP and CA-TIMS are suggested by considering intrusive and extrusive age results separately. All but one sample where the SHRIMP age is more than 0.25 % older are volcanic. This offset could be explained by the better single-grain age resolution of TIMS, allowing identification and exclusion of antecrysts from the eruptive population, while SHRIMP does not have a sufficient single-grain precision to deconvolve these populations – leading to an apparent older SHRIMP age. In contrast, SHRIMP ages from plutonic rocks – particularly plutonic rocks from the early Paleozoic – are typically younger than the CA-TIMS ages from the same samples, most likely reflecting Pb loss from non-chemically abraded SHRIMP zircons, while chemical abrasion of zircons prior to TIMS analysis destroyed or corrected these areas of Pb loss.

In Situ Trace Elements in Quartz and K-Feldspar from Felsic Igneous Rocks: A Titanium-in-K-Feldspar Geothermometer for Natural Magmatic Systems

Abstract Scanning electron microscope, cathodoluminescence (CL) imaging and laser ablation–inductively coupled plasma–mass spectrometry analyses were conducted on coexisting pairs of quartz and K-feldspar from 14 samples of various types of felsic igneous rocks. Difference of the concentration of trace elements in quartz and K-feldspar among plutonic, pegmatitic and volcanic rocks is closely related to the rock-forming process and P–T condition. In general, a decreasing Ti concentration and increasing Al, Li, and Ge concentrations from plutonic to pegmatitic quartz suggest a higher degree of magmatic fractionation and lower crystallization temperature. Sensitive elements to magma differentiation in K-feldspar such as Ba, Sr, and LREE show a decreasing trend from various granitic rocks to pegmatite, while Rb, Cs, Li, Ge, and P exhibit increasing trends. The K-feldspar from various types of felsic igneous rocks typically shows similar CL textures but relatively higher luminescence intensity compared with coexisting quartz. Both quartz and K-feldspar phenocrysts in the volcanic rhyolite have a bright rim and a dark core in CL images, corresponding to bimodal Ti concentrations. Among all samples, Ti concentrations in both quartz and coexisting K-feldspar positively correlate with their CL intensities, suggesting the activation of Ti-impurity in these minerals leads to increased CL intensity. Meanwhile, there is a good positive correlation between Ti concentrations in quartz and those in K-feldspar with an R2 value of 0.86. It is considered that Ti concentrations in the both minerals are mainly temperature dependent at relatively constant pressure on basis of a fair aTiO2 restriction. Here, for the first time, we calculated a titanium-in-K-feldspar (TitaniKfs) thermometer in the form of log (XTi, kfs/aTiO2) = −(3430 ± 268)/T(K) + (5.081 ± 0.298) for natural felsic magma systems. The Ti contents of K-feldspar (in ppm by weight) increase exponentially with reciprocal T at temperatures ranging from 500°C to 800°C, at 200–300 MPa. An application of this thermometer to granitic rocks from Xinjiang and Inner Mongolia in China fits well with other geothermometers. In addition, the present TitaniKfs thermometer is expected to be particularly useful in determining the temperature condition of K-feldspar-bearing extraterrestrial materials such as lunar rocks.

Sedimentation, tectonics and climate in Ladakh, NW Trans-Himalaya-with a special reference to Late Quaternary Period

Ladakh, the newly formed Union Territory of India, is a cold arid high altitude desert lying in the Trans-Himalaya and is an important region for geographers and geologists, because of its lunar/martian landscapes, exposures of sedimentary, metamorphic and igneous rock types, glacial, fluvial lacustrine sediments and active tectonic and climatic processes. This paper sums up the sedimentary characteristics, tectonic and climatic history with examples from the variety of sediment exposures along the Indus River. The overall geomorphological evolution of Ladakh is basically governed by two sets of geological processes—the continental scale geological processes that have primarily provided the basic framework for the landscape and second the regional/local scale geological processes in which the role of tectonics and climate which has been significant in determining the glacial, fluvial, lacustrine and aeolian processes. The transient topography of the region is attributed to (a) the movement along active Stok thrust, along the Indus Suture Zone; (b) long term steady state perturbed by climate change; (c) location in orographic rain shadow zone; and (d) the landscape being not in cosmogenic steady state due to topographic effect and methodological uncertainties of data.

An evolutionary system of mineralogy, Part VII: The evolution of the igneous minerals (>2500 Ma)

AbstractPart VII of the evolutionary system of mineralogy catalogs, analyzes, and visualizes relationships among 919 natural kinds of primary igneous minerals, corresponding to 1665 mineral species approved by the International Mineralogical Association—minerals that are associated with the wide range of igneous rock types through 4.566 billion years of Earth history. A systematic survey of the mineral modes of 1850 varied igneous rocks from around the world reveals that 115 of these mineral kinds are frequent major and/or accessory phases. Of these most common primary igneous minerals, 69 are silicates, 19 are oxides, 13 are carbonates, and 6 are sulfides. Collectively, these 115 minerals incorporate at least 33 different essential chemical elements.Patterns of coexistence among these minerals, revealed by network, Louvain community detection, and agglomerative hierarchical clustering analyses, point to four major communities of igneous primary phases, corresponding in large part to different compositional regimes: (1) silica-saturated, quartz- and/or alkali feldspar-dominant rocks, including rare-element granite pegmatites; (2) mafic/ultramafic rock series with major calcic plagioclase and/or mafic minerals; (3) silica-undersaturated rocks with major feldspathoids and/or analcime, including agpaitic rocks and their distinctive rare-element pegmatites; and (4) carbonatites and related carbonate-bearing rocks.Igneous rocks display characteristics of an evolving chemical system, with significant increases in their minerals’ diversity and chemical complexity over the first two billion years of Earth history. Earth’s earliest igneous rocks (>4.56 Ga) were ultramafic in composition with 122 different minerals, followed closely by mafic rocks that were generated in large measure by decompression melting of those ultramafic lithologies (4.56 Ga). Quartz-normative granitic rocks and their extrusive equivalents (>4.4 Ga), formed primarily by partial melting of wet basalt, were added to the mineral inventory, which reached 246 different mineral kinds. Subsequently, four groups of igneous rocks with diagnostic concentrations of rare element minerals—layered igneous intrusions, complex granite pegmatites, alkaline igneous complexes, and carbonatites—all first appeared ~3 billion years ago. These more recent varied kinds of igneous rocks hold more than 700 different minerals, 500 of which are unique to these lithologies.Network representations and heatmaps of primary igneous minerals illustrate Bowen’s reaction series of igneous mineral evolution, as well as his concepts of mineral associations and antipathies. Furthermore, phase relationships and reaction series associated with the minerals of a dozen major elements (H, Na, K, Mg, Ca, Fe, Al, Si, Ti, C, O, and S), as well as minor elements (notably Li, Be, Sr, Ba, Mn, B, Cr, Y, REE, Ti, Zr, Nb, Ta, P, and F), are embedded in these multi-dimensional visualizations.

Mapping the facies and geomorphology of igneous bodies by integrating multiple disciplines data: A case study of the BZ-A oilfield, Bohai Bay Basin, China

The BZ-A oilfield is one of the significant discoveries within the Huanghekou Sag, the southern Bohai Sea Basin, China, and the reservoirs of the BZ-A oilfield were deposited in the Paleogene period. Unfortunately, the spatial continuity of the Paleogene clastic reservoirs of the BZ-A oilfield was destroyed by the widely distributed igneous rocks. Characterizing those “isolated” clastic geobodies is the main task in the exploration and production phases. The exploration wells within the BZ-A oilfield demonstrate that the size of the clastic geobodies is one of the main factors that determine if a new drilled well is a commercial oil-producing well. The spatial distribution and the size of igneous rocks are other important factors affecting whether a drilled well is an oil-producing well. Thus, the analysis of 3D geomorphology of igneous rocks is among the most important tasks in well and development planning. We integrate 3D seismic data, well logs, and core data to characterize the Paleogene igneous bodies within the BZ-A oilfield. The analyzing procedure begins with determining the igneous rock types by analyzing the texture of cores and corresponding thin sections. Then, the volcanic/volcaniclastic facies are defined by integrating the well logs and igneous rock. Finally, the volcanic edifices are interpreted by integrating the seismic data, well logs, and core data. The analysis demonstrates that the volcanic edifice usually consists of five facies (volcanic conduit, effusive, explosive, extrusive, volcanic sedimentary, and subvolcanic facies). The overall shape of the edifice and the distribution of each facies are controlled by the volcanic eruption styles. In our study area, the seismic variance attribute can be used to locate the volcanic conduit facies, and the seismic root-mean-square amplitude can characterize the volcanic effusive facies.