Thin-section Images Research Articles

ELECTROFACIES DEFINITION AND ZONATION OF THE LOWER CRETACEOUS BARRA VELHA FORMATION CARBONATE RESERVOIR IN THE PRE‐SALT SEQUENCE OF THE SANTOS BASIN, SE BRAZIL

Lower Cretaceous carbonates in the pre‐salt succession in the Santos Basin, eastern Brazil, are highly heterogeneous in terms of their reservoir characteristics as a result of depositional and diagenetic factors. Electrofacies have widely been used for reservoir zonation and, when allied with computer‐based methods such as neural networks, may help with the study of such complex reservoir rocks and with the identification of high‐quality reservoir zones. In this work, an unsupervised artificial neural network known as a self‐organizing map (SOM) was used to carry out a zonation of the pre‐salt carbonates in the Aptian Barra Velha Formation, the main reservoir unit in the Santos Basin. Available data included gramma‐ray, neutron porosity, resistivity deep, sonic, density, photoelectric factor, total porosity and effective porosity profiles from 21 wells together with mineralogical models. Core descriptions and thin section images were used as additional data for the lithological characterization of the electrofacies and consequently for reservoir zonation. A total of four electrofacies were defined from the SOM application, and five reservoir zones were identified.The characterization of the reservoir zones also considered the structural locations of the wells based on the relative depth to top‐ Barra Velha Formation; well locations were classified as structurally high, intermediate or low. Based on the reservoir zone characteristics, the results could be correlated with zonations in previous studies. A general tendency was noted for there to be an increase of finer‐grained sediments in the formation in wells located in structural lows; packstone and mudstone facies were prevalent in these wells and were in general characterized as poor‐quality reservoir rocks. By contrast, the shrubstones and grainstones which were more frequent in structurally high wells comprised higher quality reservoir rocks.The basal reservoir zone showed wide lithological variation compared to the overlying reservoir zones. Grainstone‐dominated facies were identified in the middle of the formation, and the uppermost reservoir zones were characterized by an upward increase in shrubstones and reworked grainstones which in general pointed to better quality reservoirs.

COMSOL-based investigation of the characteristics of microscopic water flooding and residual oil distribution in carbonate reservoirs

Carbonate reservoirs are rich in oil and gas reserves; thus, they have great exploitation potential. Therefore research on the microscopic mechanisms of carbonate reservoirs is of great significance. Based on the thin section images of core castings of typical Well 555 and its pore and fracture features in actual reservoirs, this study designed three kinds of images representing the pore and throat structure of real rocks by applying image stitching and binarization processing methods. A microscopic pore model of carbonate rocks was then established using COMSOL numerical simulation software. The microscopic water flooding characteristics and residual oil distributions of different schemes were observed by designing different fracture development forms. The fractures that developed in parallel main lines showed a more obvious influence on water flooding characteristics compared to fractures that developed in vertical main lines. The cluster residual oil was the main residual oil type in the early stage of water flooding in the pure matrix model. With the progress of water flooding, the continuous cluster residual oil gradually turned into mainly discontinuous porous and columnar residual oils. Vertical mainline fractures reduced the amount of residual oil in clusters and replaced it with columnar residual oil. In contrast, parallel main line fractures expanded the unswept area, with the residual oil appearing in contiguous clusters. This study microscopically analyzed the law and characteristics of water flooding in carbonate reservoirs to provide key theoretical support for enhancing oil recovery.

Superpixel segmentations for thin sections: Evaluation of methods to enable the generation of machine learning training data sets

Training data is the backbone of developing either Machine Learning (ML) models or specific Deep Learning (DL) algorithms. The lack of well-labeled training image data has significantly impeded the development of novel DL methods like Convolutional Neural Networks (CNNs) in mineral thin section images identification. However, image annotation, especially pixel-wise annotation is always a costly process. Manually creating dense semantic labels for rock thin section images has been long considered as an unprecedented challenge in view of the ubiquitous variety and complexity of minerals in thin sections. To speed up the annotation, we propose a human–computer collaborative pipeline in which superpixel segmentation is used as a boundary extractor to avoid hand delineation of instances boundaries. The pipeline consists of two steps: superpixel segmentation using MultiSLIC, and superpixel labeling through a specific-designed tool. We use a cutting-edge methodology Virtual Petroscopy (ViP) for automatic image acquisition. Bentheimer sandstone sample is used to conduct performance testing of the pipeline. Three standard error metrics are used to evaluate the performance of MultiSLIC. The result indicates that MultiSLIC is able to extract compact superpixels with satisfying boundary adherence given multiple input images. According to our test results, large and complex thin section images with pixel-wise accurate labels can be annotated with the labeling tool more efficiently than in a conventional, purely manual work, and generate data of high quality.

Construction of 2D and 3D rock physics templates for quantitative prediction of physical properties of a carbonate reservoir in SW of Iran

The characterization of carbonate rocks is not straightforward, as they often experience complex diagenetic processes causing them to expose wide variations in pore types. This research aims to characterize the properties of a carbonate reservoir with a complicated porous structure through rock physics principles and tools. Two representative wells from an oil field located in SW of Iran were selected, and two-dimensional (2D) and three-dimensional (3D) rock physics templates (RPTs) were constructed by employing the appropriate rock physics models. The porosity, water saturation, and pore type are considered reservoir parameters affecting carbonate rock's elastic properties and indicating the reservoir quality. The 2D RPTs described variations in two reservoir parameters in terms of elastic properties. However, they were not able to simultaneously characterize all three reservoir parameters. The proposed 3D RPTs revealed the underlying relationship of elastic properties with pore aspect ratio, water saturation, and porosity. To validate the constructed RPTs, well logging data, scanning electron microscope images, and thin section images were utilized. The RPTs were also employed to predict the reservoir properties quantitatively, and these predictions were compared with the petrophysical data. The average errors of the predicted porosity and water saturation by 3D RPT were, respectively, 1.22% and 6.66% for well A, and 2.65% and 8.18% for well B. The 2D RPTs provided three sets of predictions for porosity and water saturation (considering three specific pore aspect ratios of 0.03, 0.1, and 0.5), all with higher average errors compared to the predictions by 3D RPT for both wells. The obtained results proved that 3D RPT could predict reservoir properties more accurately. Finally, based on the estimated values of pore aspect ratio, water saturation, and porosity using 3D RPTs, the reservoir under study was divided into distinct depth intervals, and a quality level was assigned to each interval. The introduced rock physics-based procedure for a carbonate reservoir characterization could increase the reliability in predicting the reservoir properties, enhance the ability to detect the reservoir fluid, and thereby reduce the interpretation risk.

40Ar/39Ar geochronology of the Drakensberg continental flood basalts: Understanding large argon isotopic variations in mafic groundmass and plagioclase size fractions

The extrusive component of the Karoo Large Igneous Province, the Drakensberg Continental Flood basalts of South Africa and Lesotho, is mainly composed of altered tholeiitic basalts without uraniferous mineral phases that are suitable for high-precision dating (e.g. baddeleyite or zircon), and thus dating is restricted to 40Ar/39Ar groundmass and plagioclase. Previous 40Ar/39Ar dates of plagioclase span from 178.9 ± 4.2 Ma to 189.2 ± 3.3 Ma, while most dates range between 180 and 183 Ma (Jourdan et al., 2007b; Moulin et al., 2011; Moulin et al., 2017). Dating mafic rocks can be hindered by the presence of plagioclase xenocrysts (inherited 40Ar), and the ubiquitous presence of alteration phases. Separation protocols and acid leaching are used to minimize the effect of these issues, although previous 40Ar/39Ar studies of the Drakensburg lavas did not interpret their dates within a petrochronological context, and thus they are open to inaccuracy. We have used cathodoluminescence imaging, QEMSCAN analysis and optical petrology of thin sections to show that two distinct generations of plagioclase occur within the lavas, and at least two different phases of K-rich (adularia and K-rich clays) and Ca- alteration have occurred. 40Ar/39Ar dates have been obtained from some acid-leached and unleached aliquots of groundmass and both plagioclase generations. Our results show that i) large, cluster-forming plagioclase yield older 40Ar/39Ar dates and are interpreted to be xenocrystic, ii) apparently unaltered plagioclase in thin sections hosts secondary Ar reservoirs related to alteration, and iii) alteration and leaching can enhance the effects of 37,39Ar recoil in plagioclase. We conclude that the most accurate date for the Drakensburg lavas that applies to the entire thickness of the lava stacks is 184.4 ± 1.2 Ma, which was obtained from the matrix-forming plagioclase that contains the highest proportion of non-inherited radiogenic 40Ar, is least affected by secondary alteration and did not apparently suffer the effects of Ar isotope recoil.

On the fundamental possibility of using the bacterial and catagenetic hypotheses of the origin of oil in assessing its resources

Research subject. The estimations of oil resources in Western Siberia obtained using a basin modeling of the Bazhenov formation as an oil source stratum indicated a significant deficit of its potential, calculated based on the pyrolytic kinetic parameters of catagenesis. Aim. To search for possible additional oil generating mechanisms parallel to catagenesis, thus clarifying the conceptual foundations of the modern theory of the organic origin of oil. Key points. Based on a review of literature publications, a hypothesis was formulated about the evolution of organic matter from sedimentary flow floccules to the injection of proto-oil into the microcracks of the autofluid fracturing of source rocks. In the upper unconsolidated bottom sediment layers, biofilms appear whose microbial matrix forms a basis for future kerogen. Proto-oil bitumoids appear as a by-product of biofilm microbial metabolism under the anaerobic conditions at diagenesis stage. Рroto-oil bitumoids are encapsulated and absorbed on the surfaces and inside the chambers and conducting channels of the biofilm polymer matrix (future kerogen). Local ultra-high pressure (LUHP) inside kerogen grains appears at the final “smectite – illite” transition stage of host clays, acting as a driving force for encapsulated bitumoid expulsion from kerogen grains. On the walls of microcracks, proto-oil bitumoids undergo hydropyrolysis, consuming cohesive film water and changing the surface philicity. Microphotographs and SEM images of thin sections are provided in order to illustrate LUHP-expulsion traces. Two types of oil source rocks are differentiated based on the possibility of proto-oil LUHP expulsion: those with a plastic mineral framework and a rigid mineral framework. Conclusion. The presence of porous spaces filled with bitumoids was established in the kerogen of immature potentially oil source rocks. This mass of encapsulated bitumoids is an additional resource of oil generation within the “oil window”. Their expulsion volume can be estimated and attributed to a certain temperature range. Directions for further research are outlined.

On the generation of realistic synthetic petrographic datasets using a style-based GAN

Deep learning architectures have transformed data analytics in geosciences, complementing traditional approaches to geological problems. Although deep learning applications in geosciences show encouraging signs, their potential remains untapped due to limited data availability and the required in-depth knowledge to provide a high-quality labeled dataset. We approached these issues by developing a novel style-based deep generative adversarial network (GAN) model, PetroGAN, to create the first realistic synthetic petrographic datasets across different rock types. PetroGAN adopts the architecture of StyleGAN2 with adaptive discriminator augmentation (ADA) to allow robust replication of statistical and esthetical characteristics and improve the internal variance of petrographic data. In this study, the training dataset consists of > 10,000 thin section images both under plane- and cross-polarized lights. Here, using our proposed novel approach, the model reached a state-of-the-art Fréchet Inception Distance (FID) score of 12.49 for petrographic images. We further observed that the FID values vary with lithology type and image resolution. The generated images were validated through a survey where the participants have various backgrounds and level of expertise in geosciences. The survey established that even a subject matter expert observed the generated images were indistinguishable from real images. This study highlights that GANs are a powerful method for generating realistic synthetic data in geosciences. Moreover, they are a future tool for image self-labeling, reducing the effort in producing big, high-quality labeled geoscience datasets. Furthermore, our study shows that PetroGAN can be applied to other geoscience datasets, opening new research horizons in the application of deep learning to various fields in geosciences, particularly with the presence of limited datasets.

Experimental Studies on Rock Thin-Section Image Classification by Deep Learning-Based Approaches

Experimental studies were carried out to analyze the impact of optimizers and learning rate on the performance of deep learning-based algorithms for rock thin-section image classification. A total of 2634 rock thin-section images including three rock types—metamorphic, sedimentary, and volcanic rocks—were acquired from an online open-source science data bank. Four CNNs using three different optimizer algorithms (Adam, SGD, RMSprop) under two learning-rate decay schedules (lambda and cosine decay modes) were trained and validated. Then, a systematic comparison was conducted based on the performance of the trained model. Precision, f1-scores, and confusion matrix were adopted as the evaluation indicators. Trials revealed that deep learning-based approaches for rock thin-section image classification were highly effective and stable. Meanwhile, the experimental results showed that the cosine learning-rate decay mode was the better option for learning-rate adjustment during the training process. In addition, the performance of the four neural networks was confirmed and ranked as VGG16, GoogLeNet, MobileNetV2, and ShuffleNetV2. In the last step, the influence of optimization algorithms was evaluated based on VGG16 and GoogLeNet, and the results demonstrated that the capabilities of the model using Adam and RMSprop optimizers were more robust than that of SGD. The experimental study in this paper provides important practical value for training a high-precision rock thin-section image classification model, which can also be transferred to other similar image classification tasks.

Effects of confining pressure and microscale heterogeneity on hydrocarbon retention and pore evolution from artificial maturation of Eagle Ford Shale

Although shale heterogeneity has recently emerged as a key topic in unconventional petroleum systems, hydrocarbon (HC) retention and pore evolution in organic-rich shales still remain poorly constrained. In this study, an organic-rich Eagle Ford Shale sample (EqVRo = 0.92%) from a shale-oil prospecting well in South Texas was selected for gold-tube pyrolysis experiments to investigate organic matter (OM) -hosted pore development versus confining pressure during thermal maturation. Before heating, the OM-type heterogeneity and associated pore characteristics in the sample were examined by thin section and scanning electron microscopy imaging, combined with elemental mapping by X-ray energy-dispersive spectroscopy. Four forms of OM occurrence that are closely associated with different mineral matrix domains are distinguished, including the ductile oil-bearing primary OM and rigid primary OM in the siliceous-argillaceous seams, as well as the secondary OM in coccolith-rich lenses and in foraminifera chambers. From heating experiments, the pressure effect on pore evolution was found to be pronounced for the secondary OM in the foraminifera chambers, in which the coalescence of small pores to larger pores upon OM maturation was accelerated by increasing fluid pressure, accompanied by arrangement and densification of OM structures. However, the expulsion effect as a function of confining pressure seems to be evident only for the secondary OM in the coccolith-rich lenses. In contrast, the two types of primary OM in the siliceous-argillaceous seams do not show any apparent changes in pore development over the investigated pressure range of 10 to 120 MPa, probably due to stiffer mechanical properties of primary OM as compared to secondary OM. The discrepancies in pore evolution of different OM types as a response to the variation in confining pressure upon maturation primarily depend on the physical-chemical properties of these various OM materials.Of further importance, observed differences in OM evolution and associated pore characteristics in response to the variation in confining pressure imply that the microscale heterogeneity of shale fabric controls the extent of oil retention and pore evolution. In contrast to the intragranular pores in the foraminifera chambers, the intergranular pores in the coccolith-rich lenses from the Eagle Ford Shale sample are relatively smaller, yet more likely interconnected. Thus, these coccolith-associated pores may provide not only significant storage space but also a major flow pathway for HC production. Our investigation at the microscopic scale provides concepts indicating that HC retention and OM-hosted pore evolution occur differently in two contrasting types of mineral matrix pores, which is critical to successful unconventional shale oil and gas exploration in sedimentary basins.

Creation and application of war trauma treatment simulation software for first aid on the battlefield based on undeformed high-resolution sectional anatomical image (Chinese Visible Human dataset)

BackgroundEffective first aid on the battlefield is vital to minimize deaths caused by war trauma and improve combat effectiveness. However, it is difficult for junior medical students, which have relatively poor human anatomy knowledge and first aid experience. Therefore, we aim to create a treatment simulation software for war trauma, and to explore its application for first aid training.Methods This study is a quantitative post-positivist study using a survey for data collection. First, high-resolution, thin-sectional anatomical images (Chinese Visible Human (CVH) dataset) were used to reconstruct three-dimensional (3D) wound models. Then, the simulation system and the corresponding interactive 3D-PDF, including 3D models, graphic explanation, and teaching videos, were built, and used for first aid training in army medical college. Finally, the interface, war trauma modules, and training effects were evaluated using a five-point Likert scale questionnaire. All measurements are represented as mean and standard deviations. Moreover, free text comments from questionnaires were collected and aggregated.ResultsThe simulation software and interactive 3D-PDF were established. This included pressure hemostasis of the vertex, face, head-shoulder, shoulder-arm, upper forearm, lower limb, foot, and punctures of the cricothyroid membrane, pneumothorax, and marrow cavity. Seventy-eight medical students participated in the training and completed the questionnaire, including 66 junior college students and 12 graduate students. The results indicated that they were highly satisfied with the software (score: 4.64 ± 0.56). The systems were user-friendly (score: 4.40 ± 0.61) and easy to operate (score: 4.49 ± 0.68). The 3D models, knowledge of hemostasis, and puncture were accurate (scores: 4.41 ± 0.67, and 4.53 ± 0.69) and easily adopted (scores: 4.54 ± 0.635, and 4.40 ± 0.648). They provided information about hemostasis and puncture (all scores > 4.40), except for cricothyroid membrane puncture (scores: 4.39 ± 0.61), improved the learning enthusiasm of medical students (score: 4.55 ± 0.549), and increased learning interest (score: 4.54 ± 0.57).ConclusionOur software can effectively help medical students master first aid skills including hemostasis, cricothyroid membrane and bone marrow puncture, and its anatomy. This may also be used for soldiers and national first aid training.

Enhancement of thin-section image using super-resolution method with application to the mineral segmentation and classification in tight sandstone reservoir

The accurate characterization of rock and fluid properties in porous media of oil reservoir using thin sections depends on reliable segmentation and classification of the involved phases. However, in tight sandstone reservoirs, rock image segmentation and classification become a challenging task due to the limitation of resolution on representing the pores, throats, and other minerals at the microscale size. The resolution of an image has thus become a critical factor. Therefore, this study aims to use the super-resolution technique, which can enhance the image resolution by deep learning methods to overcome the limitation of original image resolution, and significantly improve the traditional segmentation and classification results. A Generative Adversarial Network (GAN)-based Super-resolution(SR) model was used as a pre-processing step to enhance the resolution of a given image. Then the effectiveness of super-resolution technique in post-processing procedures like segmentation and classification is evaluated using a tight sandstone data set from Ordos basin. The performance of segmentation with super-resolution enhancement is compared among Level set, Simple Linear Iterative Clustering (SLIC), and Watershed. As numerical test results reflect, segmentation in super-resolution image can achieve the segmentation of tiny minerals, pores, throats, and other blurry edges which can't be correctly segmented in the original image. Furthermore, in classification, we use a Convolutional Neural Network (CNN) model and a logistic regression model to demonstrate the advantage of SR enhancement. After the super-resolution process, the classification accuracy of CNN and logistic models have both improved for over 10%. The comparisons and analyses are presented to show that super-resolution could significantly improve these post-processing procedures. In addition, we discuss the potentials and limitations of applying super-resolution in segmentation and classification.

Intelligent pore type characterization: Improved theory for rock physics modelling

ABSTRACTThanks to the recent developments in both hardware and software capabilities of computers, intelligent rock physics modelling has emerged as an alternative to the conventional approach to the rock physics. Respecting the crucial contribution of the pore geometry into the rock physics modelling, I propose an accurate yet cost‐ and time‐efficient intelligent framework to measure pore space based on digital rock physics. In this method, total pore space was calculated after estimating the pore geometry through pattern recognition on thin section images captured through polarized‐light microscopy. Next, applying three different multi‐class classifiers (radial basis function, support vector machine and k‐nearest neighbours) for estimating pore type and aspect ratio, the best results were obtained using the fuzzy Sugeno integral, and the pore types were classified according to the most widely used pore type classification scheme. Next, an artificial neural network was applied to interpolate discrete data points (thin sections) into continuous profiles of pore type and aspect ratio. Subsequently, as a case study, the proposed approaches were applied to a real‐world carbonate reservoir for modelling the P‐ and S‐wave velocities through a rock physics model. Verifying the modelling results against ultrasonic and measured well‐logging data, the methodology showed promising performance at acceptable levels of uncertainty. The most significant advantage of the intelligent pore type quantification over the conventional methods was found to be its ability to estimate elastic properties with good accuracy. The key findings of this research include automatic detection of the pore types and aspect ratio, provision of a database of pore geometry, attenuation of uncertainty in pore type characterization and improvement of rock physics modelling in the absence of reliable S‐wave velocity data.

Nano‐FTIR Investigation of the CM Chondrite Allan Hills 83100

AbstractMid‐infrared (MIR) spectroscopy has been used with great success to quantitatively determine the mineralogy of geologic samples. It has been employed in a variety of contexts from determining bulk composition of powdered samples to spectroscopic imaging of rock thin sections via micro‐Fourier transform infrared (micro‐FTIR) imaging spectroscopy. Recent advances allow for IR measurements at the nanoscale. Near field nanoscale infrared imaging and spectroscopy with a broadband source (nano‐FTIR) enable understanding of the spatial relationships between compositionally distinct materials within a sample. This will be of particular use when analyzing returned samples from Bennu and Ryugu, which are thought to be compositionally like CI or CM1/2 carbonaceous chondrites. Returned samples will likely contain olivine/pyroxene chondrules that have been transformed into hydrous phyllosilicates, sulfides, carbonates, and other alteration phases. The use of near‐field infrared techniques to probe the boundaries between once pristine chondrules and alteration phases at the nanoscale is a novel approach to furthering our understanding of the compositional evolution of carbonaceous asteroids and the processes that drive their evolution. Here we report the results of nano‐FTIR spectroscopy and imaging measurements performed on the carbonaceous chondrite Allan Hills (ALH) 83100 (CM1/2). We show with nanoscale resolution that spatially resolved Fe‐Mg variations exist within the phyllosilicates around a chondrule rim. We also present effects of crystal orientation on the nano‐FTIR spectra to account for the spectral differences between the meteorite and mineral spectra.

Sub-micrometer morphology of human atherosclerotic plaque revealed by synchrotron radiation-based μCT—A comparison with histology

Histology is a long standing and well-established gold standard for pathological characterizations. In recent years however, synchrotron radiation-based micro-computed tomography (SRμCT) has become a tool for extending the imaging of two-dimensional thin sections into three-dimensional imaging of tissue blocks, enabling so-called virtual histology with arbitrary clipping planes, volumetric rendering and automatic segmentation. In this study, we present a thorough characterization of human carotid plaques after endarterectomy of patients with stroke or transient ischemic attack (TIA), investigating several different pathologic structures using both SRμCT and histology. Phase-contrast SRμCT was performed with two different magnifications (voxel sizes 6.5 μm and 0.65 μm, respectively), and histology was performed with multiple different stainings (Alpha-actin, Glycophorin A, von Kossa, Movat, CD68). The 0.65 μm high-resolution SRμCT was performed on selected areas with plaque typical relevant morphology, identified on the 6.5 μm low-resolution SRμCT. The tomography datasets were reconstructed with additional 3D volume rendering and compared to histology. In total, nine different regions with typical pathologic structures were identified and imaged with high-resolution SRμCT. The results show many characteristics typical for advanced atherosclerotic plaques, clinically relevant, namely ruptures with thrombosis, neo-vascularization, inflammatory infiltrates in shoulder regions, lipid rich necrotic cores (LRNC), thin fibrous cap, calcifications, lumen irregularities, and changes in vessel wall structures such as the internal elastic membrane. This method’s non-destructive nature renders details of micro-structures with an excellent visual likeness to histology, with the additional strength of multiplanar and 3D visualization and the possibility of multiple re-scans.

Classification of igneous rocks from petrographic thin section images using convolutional neural network

Classification of igneous rocks from petrographic thin section images using convolutional neural network

Identification and characterization of microfractures in carbonate samples

Based on the rock typing method of pore geometry and structure (PGS), rock samples from carbonate reservoir A and carbonate reservoir B were classified using data of routine and special core analysis and thin section images, and microfractures in the carbonate reservoir samples were identified and characterized. Establishment of rock types demonstrates that microfractures have developed in all rock types in carbonate reservoir A, but only partially in certain rock types in carbonate reservoir B with porosity of 1%–11%, less vuggy, and hardness of medium hard to hard. The cut-off porosity was determined for each type of rock to distinguish samples with and without conductive microfractures. The impact of conductive microfractures on improving permeability was analyzed. On the basis of relationship of permeability and original initial water saturation, the permeability equation was derived by certain special core analysis data with conductive microfractures selected by PGS equation, and the permeability of samples with conductive microfractures has been successfully predicted.

Surgical anatomy of hepatic arteries from its origin to segmental branching: A 500 cases CT study

BackgroundThe aim of this study was to present an overview of variations of the hepatic artery from the origin to the segmental branching. MethodsAbdominal Computed Tomography performed on consecutive patients in our tertiary center between 2019 and 2020 were analyzed. Hepatic arterial branching and its relationship to the portal veins were reported. ResultsOut of 500 imaging, 16 anatomic patterns were found for the origin of hepatic artery, with 65.6% conventional origin at celiac axis (n = 328); 10 patterns for the left hepatic artery, 23 for segment IV artery, and more than 21 for the right hepatic artery (RHA), with conventional branching in respectively 66.8%, 39.6% and in 46.4% of patients. Conventional anatomy from celiac axis to segmental branching was found in 10.4% of patients. ConclusionDedicated thin-section imaging appears to be essential for preoperative planning in liver surgery, given the high variability of arterial distribution and their surgical implications.

Objective quantification of nerves in immunohistochemistry specimens of thyroid cancer utilising deep learning.

Accurate quantification of nerves in cancer specimens is important to understand cancer behaviour. Typically, nerves are manually detected and counted in digitised images of thin tissue sections from excised tumours using immunohistochemistry. However the images are of a large size with nerves having substantial variation in morphology that renders accurate and objective quantification difficult using existing manual and automated counting techniques. Manual counting is precise, but time-consuming, susceptible to inconsistency and has a high rate of false negatives. Existing automated techniques using digitised tissue sections and colour filters are sensitive, however, have a high rate of false positives. In this paper we develop a new automated nerve detection approach, based on a deep learning model with an augmented classification structure. This approach involves pre-processing to extract the image patches for the deep learning model, followed by pixel-level nerve detection utilising the proposed deep learning model. Outcomes assessed were a) sensitivity of the model in detecting manually identified nerves (expert annotations), and b) the precision of additional model-detected nerves. The proposed deep learning model based approach results in a sensitivity of 89% and a precision of 75%. The code and pre-trained model are publicly available at https://github.com/IA92/Automated_Nerves_Quantification.

Control Mechanism and Parameter Simulation of Oil-Water Properties on Spontaneous Imbibition Efficiency of Tight Sandstone Reservoir

Spontaneous imbibition is an effective method of tight sandstone reservoirs development. However, their underlying mechanisms are still unclear due to the representative issue caused by strong heterogeneity and complex oil-brine properties. In this research, physical properties and thin-section images were systematically analyzed, and the spontaneous imbibition efficiency was examined from core tests. The results show that quartz and feldspar predominantly contribute to mineralogy. Low brine salinity, high oil viscosity, and high interfacial tension corresponded to strong spontaneous imbibition ability and fast process. High interfacial tension is the dominant controlling factor in this field. Furthermore, the parameter simulation model established by the dimension reduction method could catalyze the prediction of spontaneous imbibition efficiency, which is confirmed by higher reliability.

An Experiment-Based Study of Formation Damage Using a Microetching Model Displacement Method.

In the field of oil and gas exploration, drilling fluid is regarded as the essential “blood” for drilling, which mainly helps to control the formation pressure and remove cuttings from the well. During the drilling fluid cycle, the drilling fluid penetrates into the pores of the formation rock, thus blocking the rock pores and resulting in a decline in oil and gas recovery efficiency. Therefore, it is very important to understand the microscopic mechanism of formation damage caused by drilling fluid. However, as an important component of formation damage, the microscopic mechanism of fluid damage has not yet been clearly revealed. In this study, a new microetching model (MEM), along with displacement equipment, was designed. The pore network of rock samples was extracted from thin-section images and etched to a thin aluminum sheet by laser. Oil-based drilling fluid was used to displace the stratum water in the MEM. The displacement process was recorded by a camera and analyzed. A core flooding experiment, permeability measurement, and SEM observations were performed. The results show that, for low-porosity and low-permeability sandstone, the main forms of formation damage by drilling fluid include solid damage and liquid damage. Solid damage is mainly caused by the blockage of small pores and narrow throats with solid particles of the size 0.1~30.0 μm in drilling fluid, while liquid damage is mainly caused by the water lock and hydrocarbon lock effects formed by the oil–water two-phase interface, gas–water two-phase interface, or the oil–gas–water three-phase interface.