The standard petrography test method for measuring air voids in concrete (ASTM C457) requires a meticulous and long examination of sample phase composition under a stereomicroscope. The high ...expertise and specialized equipment discourage this test for routine concrete quality control. Though the task can be alleviated with the aid of color-based image segmentation, additional surface color treatment is required. Recently, deep learning algorithms using convolutional neural networks (CNN) have achieved unprecedented segmentation performance on image testing benchmarks. In this study, we investigated the feasibility of using CNN to conduct concrete segmentation without the use of color treatment. The CNN demonstrated a strong potential to process a wide range of concretes, including those not involved in model training. The experimental results showed that CNN outperforms the color-based segmentation by a considerable margin, and has comparable accuracy to human experts. Furthermore, the segmentation time is reduced to mere seconds.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Organic matter (OM)-hosted pores are important constituents of the pore system of black shales and play a crucial role in determining their methane adsorption capacity and porosity. OM-hosted pores ...are generally observed and described with scanning electron microscope (SEM) on Ar ion-milled surfaces. However, SEM imaging is not able to reliably distinguish OM types and relate the observed pores to specific macerals. Partly because of this inability to relate organic pores to macerals, the evolution of organic porosity during thermal maturation remains poorly understood.
In this paper, we review the petrographic characteristics of dispersed organic matter (DOM) in black shales under the SEM. Organic petrographic classification of DOM developed for reflected-light microscopy is so far the most practical method when describing DOM in black shales under the SEM because this classification has information on the origin of DOM. Therefore, correlative microscopy (combination of reflected-light and electron microscopy) is the most effective method to identify both OM types and OM-hosted pores. This method, however, is not readily available to most researchers. Although identifying OM on the basis of SEM observations is a challenging task, it is achievable provided there is a good understanding of the studied shales, especially their thermal maturity and original OM composition. Therefore, the overall objective of this paper is to review petrographic characteristics of DOM in black shales under the SEM to provide some guidelines for identifying DOM from SEM observations.
We also review factors that control the formation and preservation of OM-hosted pores. OM-hosted pores consist of primary and secondary organic pores. Primary organic pores are pores inherited from the biological structure of the original OM. Secondary organic pores develop during hydrocarbon generation and expulsion from oil-prone OM and are hosted by solid bitumen or pyrobitumen. The development of secondary organic pores is controlled by thermal maturity and OM type, and their preservation is subject to thermal maturity, OM content, and mineralogical composition.
The presented view of the evolution of micropore and mesopore characteristics of OM with thermal maturity is based on data from the literature. The specific surface area and pore volume of OM in black shales follow parabolic patterns with increasing thermal maturity (quantified via vitrinite reflectance, Ro). The initial increase reflects development of OM-hosted pores, and the subsequent decrease is due to denser stacking of aromatic units in the macromolecular structure of OM, with maximum values (specific surface area ~ 300 m2/g and pore volume ~ 0.3 cm3/g) reached at Ro values in the 2.5–3.5% range. The contribution of OM-hosted pores to the pore characteristics of black shales depends on OM content, OM type, and thermal maturity.
•Petrographic characteristics of dispersed OM in black shales under the SEM were reviewed.•Factors controlling the formation and preservation of OM-hosted pores were discussed.•Differentiating OM type under the SEM is challenging, but achievable.•Specific surface area and pore volume of OM follow parabolic patterns with increasing thermal maturity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The geology of the DRC has already been studied on regional plans, on the scale of a province or territory. But these studies are too synthetic and they do not consider the variations of petrographic ...facies that can occur at the scale of a locality or a village. Thus, to overcome this possibility, the present study aims to make a petrographic characterization of the rocks of the locality of Mabuku in the territory of Beni. To achieve this, we proceeded by a microscopic analysis of 10 field samples (selected on the basis of the variability of the petrographic characteristics of the rocks). Analyzes of these samples at the petrographic laboratory of the University of Nairobi in Kenya at the LPA and LPNA revealed that the lithology of the Mabuku locality consists of orthogneiss, schists, dolerite and diorite intrusions, quartzites , laterite and sandstones. However, there are four dominant formations. These are the orthogneiss found to the north; schist, dominant in the eastern part; doleritic intrusions in the northwest part; and the sandstones which are distributed along a SW-NE diagonal. Nevertheless, important gaps remain to be completed from the geochemical and metallogenic point of view in the locality of Mabuku.
A caracterização da porosidade de reservatórios de hidrocarbonetos é um grande desafio na indústria petrolífera, uma vez que o entendimento desta importante propriedade petrofísica irá exercer grande ...influência nos processos exploratórios e explotatórios. Ao se estudar diferentes tipos de reservatórios, o conhecimento dos variados tipos de porosidades é de extrema relevância, pois a permeabilidade, propriedade fundamental na produção e desenvolvimento de poços de hidrocarbonetos, irá ser afetada pela disposição dos poros. Sendo assim, este trabalho traz descrições petrográficas das lâminas dos principais reservatórios da Bacia do Recôncavo, tais como, Formação Água Grande, Formação Sergi e o Membro Gomo da Formação Candeias, com informações dos seus constituintes, arredondamento, esfericidade e tipo de porosidade. Além disso, o artigo aborda uma proposta de quantificar a porosidade de forma semiautomática, onde visa estimar porosidade por meio de imagens de lâminas delgadas através do método semiautomático desenvolvido que utiliza as informações do pixel, visto que, as lâminas usualmente são impregnadas com resina de cor azul, destacando a porosidade em um espectro de cor que a diferencia da matriz da rocha, possibilitando que um simples código de programação em python detecte, com o auxílio de um intérprete, a faixa de cor que representa os poros.
Palavras-chave: petrografia, porosidade, pixel, python.
O Granito Capote constitui um corpo intrusivo de forma alongada, de 600 Km2, localizado nas proximades das cidades de Capão Bonito, Guapiara e Ribeirão Branco e no extremo nordeste de Araçaíba. Está ...associado a Província Mantiqueira Central e correlacionado a evolução neoproterozoica do Terreno Apiaí. As rochas do batólito foram divididas em quatro fácies, denominadas de Paiol da Telha, Serra Velha, Associação Capote e Apiaí-Mirim. Petrograficamente suas rochas constituem hornblenda-biotita granodiorito a quartzo monzonito (Fácies Paiol da Telha e Serra Velha) a biotita monzogranito a sienogranito com hornblenda (Associação de Fácies Capote e Apiaí Mirim), leucocrática, predominantemente inequigranular, porfirítica, com fenocristais de microclínio branco a rosa de dimensões inferiores a 3 a 4 cm, granulação fina a média, coloração cinza ou rósea e isotrópica a sub-orientada com discreta foliação milonítica e ou cataclástica. A fácies Apiaí-Mirim é considerada uma fácies indiscriminada, devido à alta taxa de deformação, o que gera milonitos e cataclasitos. Análises de química mineral determinam como mineralogia principal microclínio, oligoclásio, anfibólio (edenita a ferroedenita) e biotita (flogopita e annita), com ferroedenita e annita mais comum nas fácies mais evoluídas. As rochas granitoides apresentam caráter cálcio alcalino, peraluminoso, do tipo I cordilheirano, sin colisional de ambiente de arco magmático e geradas pela fusão de rochas da crosta inferior.
To better understand evolution of oil-prone sedimentary organic matter to petroleum and expulsion from source rock, we evaluated organic petrographic features of Leonardian Wolfcamp A repetitive ...siliceous and calcareous mudrock and fine-grained carbonate lithofacies cycles occurring in the R. Ricker #1 core from Reagan County, Midland Basin, Texas. The objectives of the petrographic investigation were to estimate thermal maturity, identify organic matter types and abundances, and identify the presence or absence of migrated hydrocarbons in organic-lean carbonate layers. An integrated analytical program included geochemical screening total organic carbon (TOC) content by LECO, programmed pyrolysis by hydrocarbon analyzer with kinetics (HAWK) including analysis of solvent-extracted samples, X-ray diffraction mineralogy, organic petrography, scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) including correlative light and electron microscopy (CLEM), and micro-Fourier transform infrared spectroscopy (μ-FTIR) analyses of solid bitumen. The data indicate all samples are early to middle oil window thermal maturity with solid bitumen reflectance (BRo) values of 0.55–0.86% and Tmax of 440–455 °C. Organic matter is predominantly solid bitumen (as identified by optical microscopy) in all lithofacies with minor contributions from inertinite. Solid bitumen abundance decreases from siliceous mudrock (TOC >3.0 wt%) to calcareous mudrock (TOC 1.0 to 3.0 wt%) to fine-grained carbonate (TOC <1.0 wt%) lithofacies. Interpretations of petrographic data suggest siliceous and calcareous mudrocks are source rock lithofacies and contain solid bitumen (with petroleum generation potential) that is residual (what remains) from conversion of an original Type II sedimentary organic matter. In turn, fine-grained carbonates are interpreted as reservoir lithofacies which contained little or no original oil-prone sedimentary organic matter and at present-day contain only a minor component of migrated solid petroleum sourced from adjacent siliceous and calcareous mudrock lithofacies. This work helps to document petroleum generation and migration processes, improve unconventional reservoir characterization and better define areas of oil window thermal maturity in an area critical to United States hydrocarbon production.
•Organic petrography of Wolfcamp A mudrocks and carbonates from Midland Basin was studied.•Thermal maturity is early to middle oil window.•Organic matter is predominantly solid bitumen in all lithofacies with minor contributions from inertinite.•Solid bitumen is residual from thermal conversion of oil-prone sedimentary organic matter.•Mudrocks are source rock lithofacies whereas carbonates are reservoir lithofacies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Petrographic analysis is based on the microscopic description and classification of rocks and is a crucial technique for sedimentary and diagenetic studies. When compared to hand specimens, thin ...sections provide better and more accurate means for analysis of mineral proportion, distribution, texture, pore space analysis, and cement composition. Most petrographic analysis relies on visual inspection of rock thin sections under a microscope, a task that is laborious even for experienced geologists. Large projects with a tight time frame requiring the analysis of a large amount of thin sections may require multiple petrographers, thereby risking the introduction of inconsistency in the analysis. To address this challenge, we explore the use of deep convolutional neural networks (CNN) as a tool for acceleration and automatization of microfacies classification. We make use of transfer learning based on robust and reliable CNN models trained with a large amount of non-geological images. With a relatively small number of labeled thin sections used in “fine-tuning” training we are able to adapt CNN models that achieve low error levels (<5%) for the classification of microfacies from the same dataset, and moderate results (<40%) for the classification of microfacies of thin sections from different datasets. These alternate datasets differ from the training data on two independent factors: the thin sections are from different formations and are prepared by different laboratories. While becoming widely accepted as a useful tool in the biological and manufacturing disciplines, CNN is currently underutilized in the geoscience community; we foresee an increase of use of such techniques to help accelerate and quantify a wide variety of geological tasks.
•Workflow for microfacies classification with convolutional neural networks.•Methodology can be used to quickly organize large amounts of thin section images.•High accuracy (>95%) for several tests performed (using data from same source).•Accuracy decreases when model is used to classify data processed by different labs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Forty-five years after the Apollo and Luna missions returned lunar samples, China's Chang’E-5 (CE-5) mission collected new samples from the mid-latitude region in the northeastern Oceanus ...Procellarum of the Moon. Our study shows that 95% of CE-5 lunar soil sizes are found to be within the range of 1.40–9.35 μm, while 95% of the soils by mass are within the size range of 4.84–432.27 μm. The bulk density, true density and specific surface area of CE-5 soils are 1.2387 g/cm3, 3.1952 g/cm3 and 0.56 m2/g, respectively. Fragments from the CE-5 regolith are classified into igneous clasts (mostly basalt), agglutinate and glass. A few breccias were also found. The minerals and compositions of CE-5 soils are consistent with mare basalts and can be classified as low-Ti/low-Al/low-K type with lower rare-earth-element contents than materials rich in potassium, rare earth element and phosphorus. CE-5 soils have high FeO and low Mg index, which could represent a new class of basalt.
The CE-5 sample is consistent with weathered mare basalts in mineralogy and petrochemistry, and is classified as low-Ti/low-Al/low-K type with lower REE (rare earth element) contents than KREEP (potassium, rare earth element, and phosphorus). This new sample characterized by high FeO and low Mg index could represent a new lunar basalt.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Salt giants are large-scale, basin-wide deposits formed sporadically in the geological past, from the early Paleozoic to the late Cenozoic. Their role as sinks for seawater dissolved ions is well ...known, however the biogeochemical conditions that accompany salt giant formation and their effects on carbon cycling remain poorly constrained. Here we show that massive gypsum deposits of the Mediterranean salt giant – the youngest salt giant on Earth – formed in a particularly dynamic biogeochemical environment controlled by orbitally-driven climate oscillations at the precessional scale. Using multiple sulfur isotopes combined with a steady-state sulfur cycle model, we show that, prior to gypsum precipitation, more than 80% of its constituting sulfate was first microbially reduced into sulfide, possibly stored as elemental sulfur, and then almost completely microbially reoxidized back to sulfate. This “cryptic” sulfur cycling contemporaneous to gypsum precipitation implies both negligible net sulfate consumption and sulfide production, despite a significant benthic flux of organic carbon remineralized through microbial sulfate reduction. This is the first known evidence of cryptic sulfur cycling in the geological past.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The magnetic susceptibility is a reflection of minerals like the iron oxide that affect the pore system. This work applied the magnetic susceptibility as an effective indicator of reservoir quality. ...A total of (38) sandstone samples were collected from the Nubia Group exposed in Northeast Aswan, representing the Sabaya, Abu Agag and Um Bramil Formations. The samples were petrophysically examined in terms of porosity, grain density, bulk density, permeability and magnetic susceptibility (κ). Reservoir quality index (RQI) and distribution of the sample within the Global Hydraulic Elements (GHEs) were determined. Several relations constructed between (κ) as a function of iron oxides and the measured properties. The results showed Sabaya and Abu Agag samples are characterized by the highest average values of κ, (287 & 219SI) respectively, matched with the lowest average values of porosity, permeability, RQI and the highest average values of grain & bulk density, hence most samples lie in the lower quality zones (GHE-1, 2, 3 and 4). On the contrary, the lowest average value of (κ) is (37.9 SI) for Um Bramil samples, matched with the highest average values of porosity, permeability, RQI and the lowest average values of grain & bulk density, hence most samples lie in the higher quality zones (GHE-6, 7 and 8). Petrographic description showed the tight and wide pore system relation to the magnetic susceptibility values. The novelty here is utilizing the magnetic susceptibility as an effective pointer for the reservoir quality expectation and classification into hydraulic units.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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