A companion paper (England & Thompson, 1984a) investigates the pressure-temperature—time (PTt) paths followed by rocks undergoing burial metamorphism in continental thickening events. This paper discusses problems involved in inferring such paths from the petrological data available in metamorphic rocks and—once such paths are determined—how they may be interpreted in terms of the thermal budgets of metamorphism. Each of the principal facies series (glaucophane-jadeite, andalusite-sillimanite and kyanite-sillimanite) may be encountered by rocks involved in the thickening and erosion of continental crust in a regime of average continental heat flow. The inference of a minimum thermal budget required for a given metamorphism depends strongly on a knowledge of the PTt paths followed by rocks during the metamorphism. Discrimination between possible thermal regimes is greatly enhanced if portions of PTt paths, rather than single PT points, are available, and additional constraint is possible if these paths are supplemented by geochronological, structural and heat flow data.
Abstract The significant heterogeneity of sandstone and mudstone interbedded reservoirs complicates the accurate evaluation of formation brittleness, thereby affecting the optimization of fracturing stage design. This paper first derives a statistical damage constitutive model to predict rock stress-strain curves under in-situ conditions, and the application of the model has been validated by experimental results. It then develops an energy-based brittleness evaluation procedure that accounts for the effects of lithology, physical properties and in-situ conditions on rock brittleness at a logging scale. The results indicate that highly brittle rocks can store significant elastic energy during loading and release it abruptly without requiring additional energy input. Rocks with a low Young’s modulus can exhibit high brittleness, as the post-peak mechanical behavior of rock controls its overall brittleness. As confining pressure increases, the brittleness of rocks decreases, rocks with the same Young’s modulus exhibits a 44.4% increase in brittleness when confining pressure decreases by 20 MPa. The newly proposed method effectively evaluates the reservoir energy-based brittleness index at the logging scale. This evaluation method is more sensitive to strongly heterogeneous formations and is more objective considering the cumulative impact of internal and external conditions without biased energy weighting.
Franco Grosso Giordano, Quinten Mariën, Nele De Belie
et al.
ABSTRACT Portland cement largely replaced hydraulic lime over the past century because of its rapid hardening. Achieving earlier hardening in lime through faster carbonation is thus essential to help overcome one of lime’s limiting qualities. Here, we isolated two alkaliphilic bacteria, Shouchella clausii and Shouchella patagoniensis, from a lime mortar wall. S. clausii was then further grown in high pH (>11) by adaptive laboratory evolution to acclimate a third isolate. Bacterial suspensions of all three isolates were followed for 14 days in serum bottles at pH 11, and gas composition of the headspace, intact/damaged cell populations, and pH were measured. In parallel, lime mortar samples were incubated in a closed environment with bacterial suspension of the isolates and analyzed with thermogravimetric analysis after 7 and 14 days to quantify carbonation. S. patagoniensis produced more CO2, close to the estimated maximum CO2 uptake rate of lime, and carbonated the lime mortars to a larger extent than the other isolates. Finally, the bacterial suspensions were directly mixed with lime. A linear and homogeneous carbonation of the paste samples was measured compared to water-based pastes, and the development of Liesegang patterns was observed upon phenolphthalein spreading. All this indicated that the organic addition altered the carbonation dynamics of the material, although bacteria did not accelerate carbonation relative to media alone and inhibited it relative to water-based paste. Still, a relationship between bacterial activity, CO2 emission, and carbonation rate was established, but practical aspects of bacterial delivery into lime must be addressed.IMPORTANCEPortland cement is the dominant binder used in most construction today, but until last century, lime was the ubiquitous construction material. The increase in use of cement has sprung from its higher strength and faster hardening; yet, lime still remains a relevant material, particularly in masonry structures and the built heritage. As such, novel lime materials are necessary to tackle some of the current limitations of lime, such as earlier hardening, which would not only make lime easier to work with but would also limit failure due to environmental conditions. As existing strategies to speed up lime hardening have had limited uptake due to their reliance on expensive and often toxic chemicals, the need for novel solutions is in place. We show that bacterial-based strategies could be a viable option to go beyond the limitations of current strategies, but limitations are in place.
Tatiana Vasileva, Yana Legostaeva, Olesya Shadrinova
et al.
IntroductionMining in the Arctic induces severe environmental transformations, particularly soil salinization, which threatens the fragile ecosystems of permafrost-affected landscapes. This study investigates the mechanisms of this process in the Daldyn-Alakit region (Western Yakutia), focusing on the interaction between the geogenic potential of waste rocks and technogenic triggers.MethodsWe conducted an integrated analysis of technogenic massifs (waste rock dumps, tailings) and soils at the Udachninsky and Aikhal mining and processing plants. The methodology included petrographic microscopy, X-ray diffraction (XRD) analysis, geochemical analysis of major oxides and trace elements, and ion chromatography of water extracts to characterize salinity.ResultsWe identified that gypsum-bearing dumps at the Aikhal site present a high inherent risk for sulfate salinization, while the kimberlites contribute primarily to trace metal (Ni, Cr) enrichment. However, the actual widespread salinization is driven by technogenic factors: the primary activator for chloride salinization is the surface interaction with highly mineralized brines from injection sites and tailings storage facilities. The secondary driver is the enhanced weathering of waste dumps, releasing sulfates.DiscussionOur results demonstrate that salinization type is not a simple function of waste rock composition but a complex interplay between inherent geochemical properties and mining-induced pathways. This finding is crucial for developing targeted reclamation strategies.
Abstract The cost of implementing improved oil recovery measures after the formation of dominant seepage channels is high, and the effectiveness is often not significant. By predicting the formation of dominant seepage channels and actively intervening in their early stages, it is possible to reduce development costs and improve oil recovery factor. Consequently, the prediction of dominant seepage channels has emerged as a key focus of research in reservoir engineering. This research introduces a novel method for predicting dominant seepage channels, termed Label Matrix of Seepage Channels Informer (LMSC-Informer), which integrates deep learning with reservoir engineering principles. It employs an evaluation method for the development of dominant seepage channels and a label matrix for seepage channels. Unlike existing approaches that primarily depend on geological and formation parameters, this method leverages reservoir production data, making it more accessible and versatile. An experimental prediction conducted in a reservoir in China demonstrated the practical effectiveness of the proposed methods, achieving a prediction accuracy of 73.9%.
Abstract Rock typing plays a crucial role in describing the heterogeneity of the reservoir. Most of the conventional rock typing methods are implemented to classify the target reservoir into various rock types based on various petrophysical properties (e.g., porosity and permeability), but fail to provide more critical information that significantly affects the final performance of the reservoir characterization including: (1) the porosity and permeability contribution of each rock type and (2) the geological genesis of each rock type. Along with the universal application of various imaging devices, the image-based microscale rock typing (IMRT) can be directly conducted based on the observed pore structures which fundamentally determine the rock types. The IMRT belongs to the computer vision field which can be divided into pattern recognition-related rock typing (PRRT) and texture segmentation-related rock typing (TSRT). The PRRT is mainly used to identify the category (e.g., lithofacies, reservoir zone, or Dunham textures) of a given rock sample. The TSRT aims to classify a single image into several areas where each area denotes a relatively homogeneous porous structure. In this paper, the popular IMRT methods and their applications are reviewed thoroughly. Many successful applications proved that IMRT is an effective way to quantitatively estimate the porosity and permeability contributions of each rock type in a heterogeneous rock sample with the help of numerical flow simulation. Besides, the IMRT results also can be used to reveal the geological genesis of each rock type when its texture is determined by a special geological process.
Pooya Naghizadeh Ardebili, Golnaz Jozanikohan, Ali Moradzadeh
Abstract The key problem in oil exploration and engineering is the lack of accurate and reliable data about the reservoir parameters of a field. Having a precise assessment of petrophysical properties can provide the ability to make decisions with a high degree of confidence about planning for production, exploitation, and further field development scenario. In this research, an artificial intelligence (AI)-based approach was developed to improve the estimation of reservoir parameters including porosity and volume of shale, which has a significant role in different stages of hydrocarbon exploration, in the Kashafrud Gas Reservoir in the northeast of Iran. For this purpose, we measured the petrophysical properties of 27 samples of the Kashafrud Formation. To increase the amount of data for employing a multilayer perceptron (MLP) artificial neural network (ANN), a geostatistical algorithm was used to increase the amount of laboratory measured data of porosity and volume of shale to 686 and 702, respectively. In addition, 2263 well-logging data from the same well were provided. The optimal MLP network with the topology of 6-7-1, and 6-8-1 was selected to estimate the porosity and shale volume with mean squared error (MSE) of 2.78731E−4, and 1.28701E−9, respectively. The training process was performed using two different sets of input data. In the first approach, all available well-logging data were used as input, ending up in high MSE. In the second approach, some selected well logs were used based on the results of sensitivity analysis which clearly improved the estimations. The ability of MLP networks made great improvements in the estimation of the both parameters up to 99.9%. The presence of valuable core data in this study significantly improved the process of comparison and conclusion. The final results prove that AI is a trusted method, also the potential of the ANN method for the reservoir characterization and evaluation associated problems should be taken into consideration. Due to the unavailability of core data along the whole wells, the application of intelligent methods, such as machine learning (ML) can be used to estimate the parameters in other oil or gas fields and wells.
The 9th national conference on applied geochemistry in China will be held in Chengdu, Sichuan province, in October 2023, hosted by the committee of applied geochemistry, the Chinese Society for Mineralogy, Petrology and Geochemistry (CSMPG) [...]
Abstract Prediction of stable mineral equilibria in the Earth's lithosphere is critical to unravel the tectonomagmatic history of exposed geological sections. While the recent advances in geodynamic modeling allow us to explore the dynamics of magmatic transfer in solid mediums, there is to date no available thermodynamic package that can easily be linked and efficiently be accounted for the computation of phase equilibrium in magmatic systems. Moreover, none of the existing tools fully exploit single point calculation parallelization, which strongly hinders their applicability for direct geodynamic coupling or for thermodynamic database inversions. Here, we present a new Mineral Assemblage Gibbs Energy Minimizer (magemin). The package is written as a parallel C library, provides a direct Julia interface, and is callable from any petrological/geodynamic tool. For a given set of pressure, temperature, and bulk‐rock composition magemin uses a combination of linear programming, extended Partitioning Gibbs Energy and gradient‐based local minimization to compute the stable mineral assemblage. We apply our new minimization package to the igneous thermodynamic data set of Holland et al. (2018), https://doi.org/10.1093/petrology/egy048 and produce several phase diagrams at supra‐solidus conditions. The phase diagrams are then directly benchmarked against thermocalc and exhibit very good agreement. The high scalability of magemin on parallel computing facilities opens new horizons, for example, for modeling reactive magma flow, for thermodynamic data set inversion, and for petrological/geophysical applications.
Tatsuo Kanamaru, Kuniyuki Furukawa, Xiangyu Zhao
et al.
Abstract Magnetic petrological investigations were conducted on the pumice fall deposits of the 1783 eruption of Asama volcano to examine relationships between bulk magnetic properties and petrological features related to the magmatic and volcanic processes of the eruption. The magnetic properties of the deposits agree with the mineralogical investigation, indicating the existence of titanomagnetite and pyrrhotite as magnetic minerals in the deposits. Although most magnetic properties are common over depositional units, mass-specific magnetic susceptibility decreases as the eruption progressed, implying a change in titanomagnetite abundance. This is consistent with a previously proposed binary magma mixing model and is because of the increasing mafic endmember component without titanomagnetite. Our results demonstrate that magnetic petrology can be a useful tool for investigating volcanic and magmatic processes. Graphical Abstract
Abstract The Mesozoic tectono-magmatism in SE China has widely been considered to relate to subduction of the Paleo-Pacific Ocean. However, there lacks robust petrologic and geochemical evidence from subduction-related mafic igneous rocks to reconstruct the architecture of the subduction zone. This paper presents a comprehensive geochemical dataset (petrography, mineral chemistry, zircon U-Pb age, in-situ Sr and Pb isotope compositions of plagioclase and whole-rock major, trace element and Sr-Nd-Pb-Hf isotope data) of three early Cretaceous (Pingtan, Daiqianshan and Quanzhou) mafic intrusions from the coastal region in SE China, with aims to understand their petrogenetic link with subduction of the Paleo-Pacific Ocean. The mafic rocks comprise predominantly calcic hornblende and Ca-rich plagioclase and show varying degrees of crystal accumulation. Petrological observations and mass balance calculation indicate their parental magmas are hydrous and calc-alkaline with typical arc-type trace element features. These rocks are also characterized by “crust-like” isotopic signatures, i.e., moderately radiogenic Sr, unradiogenic Nd and highly radiogenic Pb compositions. The narrow variations of in-situ plagioclase Sr and Pb isotope ratios and the nearly identical isotope compositions between the plagioclase and bulk rock in each intrusion indicate a minor role of crustal assimilation during magmatic evolution. Instead, such “crust-like” isotopic signatures were largely resulted from source enrichment through an input of subducted sediment. Further element-isotopic modeling results suggest that the parental magmas were likely produced by melting of a depleted mantle source metasomatized via the subducted sediment-derived melt. Generation of the early Cretaceous mafic intrusions can thus be explained by subduction of a relatively hot oceanic slab, during which melt derived from the subducted sediment acted as a predominant agent to enrich the mantle wedge. Our results provide powerful petrological and geochemical constraints on the early Cretaceous subduction of the Paleo-Pacific Ocean beneath the SE China and suggest that addition of subducted sediment-derived melt may be an important mechanism for mantle enrichment in relatively hot subduction zones.