Hasil untuk "Petrology"

J. Leterrier, P. Grandclaude, M. Marchal

C. Spandler, Cassian Pirard

L. Stixrude, C. Lithgow‐Bertelloni

Editorial Board

Hughes Ery, Buse Ben, Kearns Stuart et al.

The water content (H2O) and iron oxidation state (Fe3+/FeT) of silicate glass are useful compositional parameters to measure in volcanology and igneous petrology due to: (1) their influence on the chemical and physical properties of magmas, and (2) their use in constraining the pressure-temperature-composition conditions of magma storage and ascent. We present techniques using electron probe microanalysis (EPMA) that carefully mitigate for the effects of sub-surface charging, which causes beam damage and modifies X-ray emission. The calibrated volatiles-by-difference technique quantifies H2O (assuming that this is the dominant volatile species) in silicate glass at a spatial resolution of 5-10 μm diameter with uncertainties of ±0.5-0.7 wt% and has been tested on basaltic glasses. The time-dependent-ratio flank method quantifies Fe3+/FeT at a spatial resolution of 20-60 μm diameter with uncertainties of ±0.1 and has been tested on a wide range of basaltic and peralkaline rhyolitic glasses. EPMA often requires straightforward sample preparation and is more accessible than other techniques used to quantify both H2O and Fe3+/FeT (e.g., SIMS, FTIR, Raman, XANES, Mössbauer), although uncertainties are typically larger using EPMA. For H2O, the spatial resolution of EPMA is often higher than other techniques (e.g., SIMS, FTIR), whereas for Fe3+/FeT it is often lower (e.g., Raman, XANES). Both EPMA techniques can be used on natural (e.g., melt inclusion and matrix glass) and experimental glasses, in addition to standard EPMA for quantification of major and minor element concentrations, for extensive chemical characterisation using EPMA.

C. Biagioni, C. Biagioni, J. Sejkora et al.

<p>Marioantofilliite (IMA 2025-012), ideally [Cu<span class="inline-formula">₄</span>Al<span class="inline-formula">₂</span>(OH)<span class="inline-formula">₁₂</span>](CO<span class="inline-formula">₃</span>)<span class="inline-formula">⋅</span> 3H<span class="inline-formula">₂</span>O, is a new member of the hydrotalcite supergroup discovered in the Cu–Fe ore deposit of Monte Copello–Reppia, Graveglia Valley, Liguria, Italy. It occurs as globular aggregates up to 1 mm in diameter formed by <span class="inline-formula">µm</span>-sized prismatic crystals. The streak is light blue, and lustre is greasy. Calculated density is 2.825 g cm<span class="inline-formula">⁻³</span>. Marioantofilliite is optically biaxial (–), with <span class="inline-formula"><i>α</i>=1.613(4)</span>, <span class="inline-formula"><i>β</i>=1.626(3)</span>, and <span class="inline-formula"><i>γ</i>=1.633(5)</span> (in 589 nm light). 2<span class="inline-formula"><i>V</i>_calc</span> is 72°. It is distinctly pleochroic, ranging from colourless to pale blue. The empirical chemical formula of marioantofilliite (with rounding errors) is [Cu<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M19" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi/><mn mathvariant="normal">4.23</mn><mrow><mn mathvariant="normal">2</mn><mo>+</mo></mrow></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="18pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="89080c3eca3fd94521ffbc657cd70b55"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="ejm-37-733-2025-ie00001.svg" width="18pt" height="17pt" src="ejm-37-733-2025-ie00001.png"/></svg:svg></span></span>Mg<span class="inline-formula">_0.02</span>Al<span class="inline-formula">_1.76</span>(OH)<span class="inline-formula">₁₂</span>](CO<span class="inline-formula">₃)_0.82</span>(SO<span class="inline-formula">₄)_0.01</span>[Si(OH)<span class="inline-formula">₆</span>]<span class="inline-formula">_0.05⋅3</span>H<span class="inline-formula">₂</span>O. Unit-cell parameters of marioantofilliite are <span class="inline-formula"><i>a</i>=5.590(3)</span>, <span class="inline-formula"><i>b</i>=2.9358(11)</span>, <span class="inline-formula"><i>c</i>=7.675(3)</span> Å, <span class="inline-formula"><i>β</i>=100.958(17)</span>°, and <span class="inline-formula"><i>V</i>=123.66(9)</span> Å<span class="inline-formula">³</span>, with space group <span class="inline-formula"><i>C</i></span>2/<span class="inline-formula"><i>m</i></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M36" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi>Z</mi><mo>=</mo><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">3</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="41pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="828edc207d6ef858da7929ec24df6e45"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="ejm-37-733-2025-ie00002.svg" width="41pt" height="14pt" src="ejm-37-733-2025-ie00002.png"/></svg:svg></span></span>. The crystal structure was refined to <span class="inline-formula"><i>R</i>₁=0.0372</span> for 181 unique reflections with <span class="inline-formula"><i>F</i>&gt;4<i>σ</i>(<i>F</i>)</span> and 23 refined parameters. It is topologically similar to that of other hydrotalcite-supergroup minerals and shows a distorted <span class="inline-formula"><i>{</i>001<i>}</i></span> brucite-like layer with Cu and Al statistically occupying an octahedrally coordinated <span class="inline-formula"><i>M</i></span>(1) site. The interlayer hosts disordered CO<span class="inline-formula">₃</span> and H<span class="inline-formula">₂</span>O groups. Marioantofilliite formed through the oxidative dissolution of primary Cu ores by mine drainage aqueous solutions and neutralization by gangue carbonates. Its name honours Mario Antofilli (1920–1983) for his contributions to the knowledge of the mineralogy of Liguria.</p>

Mohammad Ali Davari, Alireza Bigdeli

Abstract This study presents a data-driven modeling approach using machine learning techniques to evaluate the impact of various salt concentrations and types on interfacial tension (IFT) under different temperature and pressure conditions. Accurate IFT prediction is critical for optimizing carbon capture and storage (CCS) operations because it controls capillary trapping, plume migration, and injectivity in geological formations A dataset of 1,830 data points was compiled from the literature, encompassing three temperature levels (27 °C, 71 °C, and 100 °C) and pressure ranges from 50 to 250 bar. The salinity types analyzed included NaCl, CaCl₂, and their mixtures, with concentration ranges varying by experimental setup. A stacking ensemble learning model was developed using K-Nearest Neighbors (KNN), Decision Tree (DT), Support Vector Machines (SVM), Naive Bayes, and Logistic Regression. The model achieved a high prediction performance with a R² of 0.960 and RMSE of 1.532 on the test set. Interpretable regression formulas (linear, polynomial, and symbolic) were developed for each brine system, with polynomial regression achieving R² values above 0.97 in individual systems. The model captures known physical trends, such as an increase in IFT with higher salinity and a decrease with increasing temperature. The study demonstrates that divalent ions (Ca²⁺) have a stronger impact than monovalent ions (Na⁺), especially at lower temperatures, which is consistent with recognized interfacial thermodynamics. These findings are consistent with and help quantify salt-type effects on IFT, improving their integration into flow assurance and reservoir simulation frameworks. Furthermore, temperature moderates the salinity impact, resulting in IFT convergence at high temperatures. This study is the first to create a data-driven methodology compares the separate and combined effects of NaCl and CaCl₂ on CO₂–brine IFT. The findings provide a useful method for estimating IFT quickly and can be integrated into reservoir simulation, site screening, and operational optimization in CCS operation. However, additional validation under field-specific conditions is advised to assure accuracy beyond the laboratory scale.

Lian Wang, Liang Zhang, Rui Deng et al.

Abstract Surrogate-assisted management of water-flooding, as a reservoir production optimization strategy, dynamically adjusts development schemes at each production step, leading to improved economic benefits and enhanced recovery. However, many computationally expensive numerical simulation runs are needed to build the surrogate model in most existing surrogate-assisted reservoir production optimization methods. With that in mind, this study proposes an efficient intelligent optimization method based on active learning strategy and surrogate ensemble for multi-objective reservoir production optimization named ALSA-MOPO. In this proposed ALSA-MOPO method, three frequently-used surrogate models, the radial basis function network, Gaussian process regression, and support vector regression are adopted to construct the surrogate ensemble. In addition, an active learning strategy is adopted to reduce the sample of establishing surrogate model and query for the worse and best samples based on the surrogate ensemble using particle swarm optimization which are infilled to the dataset for improving the accuracy and quality of the surrogate ensemble. The ALSA-MOPO method stands out due to its unique use of an active learning strategy to enhance the accuracy of the surrogate model, combined with a surrogate ensemble to improve robustness. Furthermore, two synthetic reservoirs with different scales and one complex fault block reservoir were utilized to test the effectiveness and practicability of the ALSA-MOPO method. The optimization results indicated that the ALSA-MOPO framework outperformed numerical simulation-based methods by approximately 50, 20, and 35 times in the three respective cases.

Nurul Aimi Ghazali, Shigemi Naganawa, Yoshihiro Masuda

Abstract Bentonite suspension in water-based drilling fluid is susceptible to deterioration in high-temperature environments, hence requiring a deflocculant to stabilize the solid particles. Considering the use of highly toxic chrome-based deflocculant in the industry, Rhizophora spp. tannin-lignosulfonate (RTLS) was synthesized in this study as an alternative deflocculant. A viscometer was used to study the rheological properties, and the filtration performance was evaluated using low-pressure low-temperature and high-pressure high-temperature filter press in accordance with the American Petroleum Institute standard procedure. The addition of 0.5 wt% RTLS to water-based drilling fluid (WBDF) was effective in a significant reduction of the plastic viscosity (PV) and yield point (YP) of WBDF at elevated temperatures. As the amount of RTLS added to the suspension exceeds 0.5 wt%, the effect on PV and YP becomes negligible. A higher fluid loss of 13 mL was observed in the WBDF without RTLS aged at 177 °C. The addition of 2.0 wt% RTLS reduced the fluid loss to 10.7 mL. This suggests that RTLS is an effective deflocculant that can be used to improve the filtration properties of WBDF at high temperatures. The morphology of RTLS filter cakes was examined using field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FESEM-EDX). The interlayer between clay particles was identified as RTLS, a natural additive that plays a vital role in enhancing filtration while minimizing fluid loss. The outcomes of this research are promising, and this non-toxic deflocculant has the potential to replace chrome-based deflocculants that are still in use for borehole drilling.

M. Lenin Lara Calderón, Inés del Pino, Sol López-Andrés et al.

The relevance of the Franciscan community is reflected in the San Francisco church in Quito, which was built between 1535 and 1755. This architectural work belonging to the Franciscan complex was implanted on a plot of land with an area of 3.5 hectares and was one of the first buildings in the Audience of Quito. Eleven mortar samples that covered the walls of the central nave and side chapels were taken from the church’s main temple. The procedure proposed by the authors is based on a combined methodology following the standards and protocols for the less-invasive extraction of heritage samples. Tests included X-ray diffraction, petrography, and scanning electron microscopy with a microanalysis of the samples. Mortars with a rustic composition and rough manufacturing were identified to differentiate two types of mortar, one of earthen with volcanic aggregates and another of lime with volcanic aggregates. The mining data validated the existing historical documentation, the imaginary process, and the stages of the established constructions.

Huan Miao, Zhenxue Jiang, Xianglu Tang et al.

Abstract A significant deposition of black shales occurred during the Mesoproterozoic Oxygenation Event (MOE). In order to investigate the hydrocarbon generation potential and organic matter enrichment mechanism of these shale deposits, we studied the Xiamaling Formation shale in the North China region as a representative sample of the Mesoproterozoic shale. The research involved organic petrology, organic geochemistry, mineralogy, and elemental geochemistry. The following observations were made: (1) The depositional environment of the Xiamaling Formation shale can be categorized as either oxic or anoxic, with the former having shallow depositional waters and high deposition rates, while the latter has deeper depositional waters and slower deposition rates. (2) Anoxic shales exhibited significantly better hydrocarbon generation potential compared to shales deposited in oxic environments, although the latter still demonstrated high hydrocarbon generation potential. (3) Shales deposited in anoxic environments displayed higher paleoproductivity compared to those deposited in oxic environments. The high deposition rate in oxic environments slowed the decomposition and mineralization of organic matter, leading to the formation of high-quality shales. In contrast, the strong paleoproductivity, along with favorable preservation conditions, accounted for the high hydrocarbon potential of anoxic shales.

Fatemeh mohammadinia, Ali Ranjbar, Moein Kafi et al.

Abstract By determining the hydraulic flow units (HFUs) in the reservoir rock and examining the distribution of porosity and permeability variables, it is possible to identify areas with suitable reservoir quality. In conventional methods, HFUs are determined using core data. This is while considering the non-continuity of the core data along the well, there is a great uncertainty in generalizing their results to the entire depth of the reservoir. Therefore, using related wireline logs as continuous data and using artificial intelligence methods can be an acceptable alternative. In this study, first, the number of HFUs was determined using conventional methods including Winland R35, flow zone index, discrete rock type and k-means. After that, by using petrophysical logs and using machine learning algorithms including support vector machine (SVM), artificial neural network (ANN), LogitBoost (LB), random forest (RF), and logistic regression (LR), HFUs have been determined. The innovation of this article is the use of different intelligent methods in determining the HFUs and comparing these methods with each other in such a way that instead of using only two parameters of porosity and permeability, different data obtained from wireline logging are used. This increases the accuracy and speed of reaching the solution and is the main application of the methodology introduced in this study. Mentioned algorithms are compared with accuracy, and the results show that SVM, ANN, RF, LB, and LR with 90.46%, 88.12%, 91.87%, 94.84%, and 91.56% accuracy classified the HFUs respectively.

Nikolovski Zlatko, Isailović Jelena, Jeremić Dejan et al.

The rare earth elements represent an increasingly more and more important industrial resource. The increased use may result in waste generation, and their impact upon the environment quality has not been studied sufficiently. Their interaction with soil has been studied in this paper. The Freundlich adsorption isotherm has been determined for lanthanum, erbium and gadolinium at three different soil types (humus, clay and sand type), whereas the sequential extraction at these soil types has been applied for lanthanum and neodymium. The interaction of certain rare earth elements with soil components has been tested as well as the quantity in which these elements are bound to soil and later on extracted in solutions. The objective was to determine the soil capacity for disposal, first of all, of the electronic waste that contains these elements and to assume their fate in the environment.

Gianfranco Ulian, Giovanni Valdrè

Abstract Calcite (CaCO3, trigonal crystal system, space group $$R\overline{3}c$$ R 3 ¯ c ) is a ubiquitous carbonate phase commonly found on the Earth’s crust that finds many useful applications in both scientific (mineralogy, petrology, geology) and technological fields (optics, sensors, materials technology) because of its peculiar anisotropic physical properties. Among them, photoelasticity, i.e., the variation of the optical properties of the mineral (including birefringence) with the applied stress, could find usefulness in determining the stress state of a rock sample containing calcite by employing simple optical measurements. However, the photoelastic tensor is not easily available from experiments, and affected by high uncertainties. Here we present a theoretical Density Functional Theory approach to obtain both elastic and photoelastic properties of calcite, considering realistic experimental conditions (298 K, 1 atm). The results were compared with those available in literature, further extending the knowledge of the photoelasticity of calcite, and clarifying an experimental discrepancy in the sign of the p 41 photoelastic tensor component measured in past investigations. The methods here described and applied to a well-known crystalline material can be used to obtain the photoelastic properties of other minerals and/or materials at desired pressure and temperature conditions.

S. V. Tsybulyaev, K. A. Savko, A. V. Samsonov et al.

Mahyar Rajabi-Kochi, Ehsan Khamehchi

Abstract An integrated model of the PUNQ-S3 reservoir in the North Sea was constructed. Then, 16 parameters with the highest impact on target functions were selected for sensitivity analysis. The sensitivity analysis was based on the two-level Plackett–Burman design of experimental method. Finally, seven variables with the highest impact on the target functions were selected. Net present value, cumulative oil production, and cumulative water production were three target functions. The proxy model was constructed using the three-level Box–Behnken experimental design for each of the three target functions, taking into account the effect of the variable’s interactions on each other. Then the compliance and predictivity of the proxy model for each target function were validated according to the decision variables. In the end, multiobjective optimization was conducted with the aim of maximizing net present value and cumulative oil production and minimizing cumulative water production using a parameter called composite desirability.

Sherif Fakher

Abstract Hydrolyzed polyacrylamide polymer (HPAM) is the most used polymer in enhanced oil recovery operations in the oil industry. This is mainly attributed to its cost and availability. An important aspect during polymer injection in the formation for mobility control is the ability to inject the polymer easily and safely in the reservoir without having to deal with extremely high pressure gradients and without risking formation fracture. This research develops two mathematical models that can help obtain values for polymer injectivity as a function of HPAM concentration, injection flowrate, and the porous media pore size. The mathematical models were developed based on experiments conducted previously using different polymer concentrations, pore sizes, and polymer injection flowrates. After the models were developed, different data were used to validate the model and examine its accuracy in determining polymer injectivity. The models were also used to predict polymer injectivity for different conditions and illustrate the pore sizes at which the polymer was not able to propagate in the formation. Since the models have several limitations, these were mentioned in the manuscript in order to reduce any error obtained while using the models.

Ali Rasoolzadeh, Jafar Javanmardi, Amir H. Mohammadi

Abstract In this work, the effects of three ionic liquids (ILs), namely, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylimidazolium dicyanamide and tetraethyl-ammonium chloride, on methane hydrate formation and dissociation kinetic parameters were studied. The kinetic parameters including the initial rate of hydrate formation, hydrate stability at atmospheric pressure and hydrate storage capacity were evaluated. The experimental measurements were performed in an initial pressure range of 3.5–7.1 MPa. It was found that both of ILs with imidazolium-based cation increase the initial methane hydrate formation rate while the IL with ammonium-based cation leads to a decrease in the initial methane hydrate formation rate. It was also interpreted from the results that all of the three studied ILs decrease methane hydrate stability at atmospheric pressure and increase methane hydrate storage capacity. Finally, both of ILs with imidazolium-based cations were found to have higher impacts on decreasing hydrate stability at atmospheric pressure and increasing the methane hydrate storage capacity than the applied IL with ammonium-based cation.

Ali Shabani, Hamid Reza Jahangiri, Abbas Shahrabadi

Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM.

A. B. Vrevskii