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Understanding the depositional setting of siliciclastics reservoir is fundamental process to exploration and development of hydrocarbon reservoirs and to the multi-phase cycle of the oil and gas industry. Typically, core samples from existing or potential reservoirs can be used for interpretation of depositional environment. However, the lack of core samples in certain reservoirs represents a challenge for reservoir development plans and further exploration. To overcome the absence of core samples in the middle Miocene Sidri Member in the Badri field, Gulf of Suez, this study aimed to reconstruct its depositional settings by coupling well logging patterns and petrographic characterization of ditch cuttings. Consequently, 30 thin section samples representing the reservoir section of four wells were described in detail and standard petrographic characteristics were determined. Then, gamma-ray (GR) log patterns of the studied reservoir wells were used for interpretation of depositional environment. Petrographic analysis indicates that the sandstone reservoir is fine- to medium-grained arkose with dominant siliceous cement and composed mainly of quartz, feldspars, and lithic fragments. Pores reflecting primary and secondary porosity as well as inter-granular pores are dominant. The facies analysis indicates that the studied member has a heterogeneous nature and rapid facies change; its main lithofacies are blocky sandstones, intercalated sandstones and shales, and shales. Three electrofacies were interpreted in the studied section: (1) electrofacies-A (blocky sandstones), which is characterized by a cylindrical-shaped (right boxcar) GR trend; (2) electrofacies-B (intercalated sandstones and shales), which is characterized by an irregular log trend with serrated shape; and (3) electrofacies-C (shales), which is characterized by irregular GR trend and has no character. The interpreted results indicate a tidal channel depositional setting for electrofacies-A, mixed tidal flat depositional setting for electrofacies-B, and low relief offshore mudstone depositional setting for electrofacies-C. Finally, the results illustrate how the coupling of GR patterns with the analysis of petrographic characteristics can be used to understand the depositional setting of a hydrocarbon reservoir that lacks core samples. This work could be useful for assessment of reservoir distribution and quality, for reduction of uncertainty during field development, as well as for providing useful insight to similar hydrocarbon reservoirs elsewhere.

The interpretation of depositional environment and diagenesis controls on petroleum reservoirs are a major challenge that has an impact on the petroleum system of hydrocarbon reservoirs. For the evaluation of hydrocarbon exploration and development, detailed depositional facies and reservoir characteristics are needed. However, some oil fields worldwide lack core samples, which are needed for accurate research. This research aims to analyze the consequences of integrating gamma-ray log patterns with petrographic analysis to describe the depositional setting in the Baba sandstone hydrocarbon reservoir within the Badri field in Egypt's south-central Gulf of Suez. The effect of diagenesis on the reservoir pore system network was also investigated. For this study, the available dataset includes wireline logs dataset and ditch cutting analysis to provide rock mineralogy, grain size, texture, sorting, cementation, accessory minerals, and lithology. Petrographic analysis reveals that Baba sandstone is dominated by medium-grained, moderately to poorly sorted, and arkose. Based on petrographic analysis data, the Baba sandstone provenance is constrained to the adjacent Precambrian Basement units of the Sinai peninsula. Thin section analysis and the point count method identify primary intergranular macroporosity, secondary intragranular macropores, and intercrystalline micropores within the studied sandstone. Based on petrographic analysis, grain–grain relationships, and framework grain–cement relationships of thin sections, the Baba sandstone has most likely been subjected to significant physical and chemical diagenetic processes, resulting in a decrease in primary porosity. The diagenetic analysis suggests that the sandstone has undergone significant alteration such as compaction, cementation, dissolution, and clay minerals alteration. Based on gamma-ray log investigation, the cylindrical gamma-ray pattern is the sole electrofacies that characterized the Baba sandstone. The tidal sand bar is the most likely depositional environment based on log pattern, petrographic analysis, and elongated depositional direction. The present study provides insights into how to solve the lack of core samples in petroleum reservoirs and it can be applied elsewhere to better interpretation of depositional settings, and diagenesis control on the reservoir pore system network.

Most old oil and gas fields worldwide are depleted, making drilling in these sedimentary zones extremely difficult, especially in complex pore pressure regimes when they are accompanied by over-pressure zones. Considering that typical wellbore stability studies provide a conservative mud density curve to prevent wellbore failure, dynamic geomechanical approaches are required to provide more flexible and manageable drilling in such complex cases in order to address anticipated drilling obstacles. This study aims to apply the more dynamic concept, known as “depth of damage” (DOD), in the El Morgan oil field, Gulf of Suez Basin, to deliver a more optional mud density window that helps in the safe drilling of different pore pressure regimes within the area, as well as the implications of applying this drilling strategy in the studied basin. In this paper, well logging and downhole measurements were used to develop a 1D geomechanical earth model and infer the in situ stresses in the studied boreholes, and the modified Lade failure criterion was used to conduct the wellbore stability analysis. The study revealed that the El Morgan sedimentary succession has a complex and varied pore pressure regime. Applying the DOD approach introduces multiple mud density scenarios that can lead to successful drilling and avoid unexpected incidents while drilling. The key benefit of the DOD approach is that it widens the safe mud density window to be less than the shear failure with an acceptable amount of failure. This study provides insights into unconventional techniques such as underbalanced drilling techniques that can be used under manageable conditions in mature basins. Furthermore, the DOD approach is compared to the conventional wellbore stability analysis or breakout depth approach, and the main differences, merits, and demerits of each were discussed in this study.

A reservoir geomechanical modeling has been attempted in the hydrocarbon-bearing Miocene formations in the offshore Badri field, Gulf of Suez, Egypt. Pore pressure established from the direct downhole measurements indicated sub-hydrostatic condition in the depleted mid-Miocene Hammam Faraun and Kareem reservoirs. Vertical stress ( S v ) estimated using bulk density data yielded an average of 0.98 PSI/feet (22.17 MPa/km) gradient. Magnitudes of minimum ( S hmin ) and maximum ( S hmax ) horizontal stresses were deduced from the poro-elastic model. Relative stress magnitudes ( S v  ≥  S hmax  >  S hmin ) reflect a normal faulting tectonic stress in the Badri field. Pore pressure and stress perturbations (ΔPP and Δ S h ) in the depleted reservoirs investigated from actual measurements recognized ‘stress path’ values of 0.54 and 0.59 against the Hammam Faraun and Kareem Formations, respectively. These stress path values are far away from the normal faulting limit (0.68), indicating induced normal faulting or fault reactivation to be unlikely at the present depletion rate.

Soft robots provide a pathway to accurately mimic biological creatures and be integrated into their environment with minimal invasion or disruption to their ecosystem. These robots made from soft deforming materials possess structural properties and behaviors similar to the bodies and organs of living creatures. However, they are difficult to develop in terms of integrated actuation and sensing, accurate modeling, and precise control. This article presents a soft-rigid hybrid robotic fish inspired by the Pangasius fish. The robot employs a flexible fin ray tail structure driven by a servo motor, to act as the soft body of the robot and provide the undulatory motion to the caudal fin of the fish. To address the modeling and control challenges, reinforcement learning (RL) is proposed as a model-free control strategy for the robot fish to swim and reach a specified target goal. By training and investigating the RL through experiments on real hardware, we illustrate the capability of the fish to learn and achieve the required task.

This research aims to evaluate various traditional or deep machine learning algorithms for the prediction of groundwater level (GWL) using three key input variables specific to Izeh City in the Khuzestan province of Iran: groundwater extraction rate (E), rainfall rate (R), and river flow rate (P) (with 3 km distance). Various traditional and deep machine learning (DML) algorithms, including convolutional neural network (CNN), recurrent neural network (RNN), support vector machine (SVM), decision tree (DT), random forest (RF), and generative adversarial network (GAN), were evaluated. The convolutional neural network (CNN) algorithm demonstrated superior performance among all the algorithms evaluated in this study. The CNN model exhibited robustness against noise and variability, scalability for handling large datasets with multiple input variables, and parallelization capabilities for fast processing. Moreover, it autonomously learned and identified data patterns, resulting in fewer outlier predictions. The CNN model achieved the highest accuracy in GWL prediction, with an RMSE of 0.0558 and an R 2 of 0.9948. It also showed no outlier data predictions, indicating its reliability. Spearman and Pearson correlation analyses revealed that P and E were the dataset’s most influential variables on GWL. This research has significant implications for water resource management in Izeh City and the Khuzestan province of Iran, aiding in conservation efforts and increasing local crop productivity. The approach can also be applied to predicting GWL in various global regions facing water scarcity due to population growth. Future researchers are encouraged to consider these factors for more accurate GWL predictions. Additionally, the CNN algorithm’s performance can be further enhanced by incorporating additional input variables.

Brain atlases and templates are at the heart of neuroimaging analyses, for which they facilitate multimodal registration, enable group comparisons and provide anatomical reference. However, as atlas-based approaches rely on correspondence mapping between images they perform poorly in the presence of structural pathology. Whilst several strategies exist to overcome this problem, their performance is often dependent on the type, size and homogeneity of any lesions present. We therefore propose a new solution, referred to as Virtual Brain Grafting (VBG), which is a fully-automated, open-source workflow to reliably parcellate magnetic resonance imaging (MRI) datasets in the presence of a broad spectrum of focal brain pathologies, including large, bilateral, intra- and extra-axial, heterogeneous lesions with and without mass effect. The core of the VBG approach is the generation of a lesion-free T1-weighted image, which enables further image processing operations that would otherwise fail. Here we validated our solution based on Freesurfer recon-all parcellation in a group of 10 patients with heterogeneous gliomatous lesions, and a realistic synthetic cohort of glioma patients (n = 100) derived from healthy control data and patient data. We demonstrate that VBG outperforms a non-VBG approach assessed qualitatively by expert neuroradiologists and Mann-Whitney U tests to compare corresponding parcellations (real patients U(6,6) = 33, z = 2.738, P < .010, synthetic-patients U(48,48) = 2076, z = 7.336, P < .001). Results were also quantitatively evaluated by comparing mean dice scores from the synthetic-patients using one-way ANOVA (unilateral VBG = 0.894, bilateral VBG = 0.903, and non-VBG = 0.617, P < .001). Additionally, we used linear regression to show the influence of lesion volume, lesion overlap with, and distance from the Freesurfer volumes of interest, on labeling accuracy. VBG may benefit the neuroimaging community by enabling automated state-of-the-art MRI analyses in clinical populations using methods such as FreeSurfer, CAT12, SPM, Connectome Workbench, as well as structural and functional connectomics. To fully maximize its availability, VBG is provided as open software under a Mozilla 2.0 license (https://github.com/KUL-Radneuron/KUL_VBG). [Display omitted] (A) shows T1 images from two patients with gliomatous lesions. VBG is a lesion replacement/filling workflow with one approach for unilateral lesions (uVBG) and one for bilateral lesion (bVBG). (B) shows the lesion filling and recon-all combination selected, (C) & (D) show the output, tissue segmentations (C) and whole brain parcellations (D). If VBG is not used (non-VBG) recon-all may quit without generating a parcellation (hard failure) shown on the lower left, or finish with some errors (soft failures) in the parcellations shown on the lower right. However, using either VBG method allows recon-all to complete where it had previously failed and also improves parcellation quality. (PAT = patient, VBG = virtual brain grafting, uVBG = unilateral VBG, bVBG = bilateral VBG)

GFRP bars can be used partially or fully instead of steel bars in RC-beams to eliminate corrosion problems, especially in harsh environments. Also, the implementation of the combined use of engineered cementitious composite (ECC) and the hybrid (steel-GFRP) reinforcement in concrete beams can enhance strength and serviceability. In this paper, seven beams; one as a control beam cast with traditional concrete, and six partial ECC RC-beams with GFRP bars only or RC-hybrid (steel-GFRP) bars were designed to investigate both deflection and ductility behaviour of such beam type. This research explored reinforcement types and two ECC configurations: (a) a bottom layer of varying thickness, (b) a U-shaped formwork. All specimens underwent four-point bending testing to examine cracks distribution, moment-strain, and moment-curvature relation, in addition to the evaluation of deflection equations and assessment of ductility of the composite beams. The experimental findings revealed that thicker ECC in the tension zone led to changes in the distribution of vertical cracks, stiffness, and energy absorption. The use of U-shaped ECC configuration generally leads to an increase in the ductility index. A specific construction technique with a corrugated surface was implemented, which created a roughened surface, improved the interface shear transfer, and eliminated bond failure at the interface. The deflection values calculated using ACI 318 -19 and CSA S806-12 equations showed good correlation with the experimentally measured deflections. In contrast, the ACI 440.1R-15 equations did not accurately capture the deflection behavior across all tested specimens.

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals. [Display omitted] (Top) shows the FWT pipeline for both CSTs, AF, and motor CC bundles. (Left to right) show the required input structural parcellation maps and a priori atlases for FWT and the resulting virtual dissection include/exclude VOIs. FWT provides two approaches to virtual dissection: (1) is a bundle-specific approach where streamlines are only seeded for the bundle of interest, (2) is a whole brain tractography followed by streamlines segmentation, (top right) shows output tractograms. (Middle) Group-averaged T1 and fODF images are generated from the HCP test-retest data, and FWT is applied to generate the HCP- atlas using the bundle-specific approach (1*). FWT's whole brain tracking and segmentation approach (2*) was applied to the HCP and MASSIVE dataset (right and left) and conducted model-based, and pair-wise similarity analyses and generated voxel-wise cumulative maps per bundle. FWT = Fun With Tracts, FS = FreeSurfer, MSBP = MultiScaleBrainParcellator, PD25 = NIST Parkinson's histological, JHU = John's Hopkins university, Juelich = Juelich university histological atlas, AC/PC = anterior commissure/posterior commissure) UKBB = UK Biobank, SUIT (spatially unbiased cerebellar atlas template), dMRI = diffusion magnetic resonance imaging, CSD = constrained spherical deconvolution, fODF = fiber orientation distribution function, CST = corticospinal tract, AF = arcuate fasciculus, CC = corpus callosum, HCP = human connectome project, MASSIVE = Multiple acquisitions for standardization of structural imaging validation and evaluation.

This paper introduces the analyses of buckling and vibration of FG sandwich piezoelectric cylindrical shells with a lightweight core exposed to a 2D magnetic field resting on viscoelastic foundations using the modified couple stress theory. In this study, Maxwell’s relations are used to derive the Lorentz magnetic force. The lightweight core is referred to as a functionally graded porous structure or a hexagonal honeycomb structure. Whereas the lower and upper layers are composed of two distinct piezoelectric materials, then a power law distribution can be used to smoothly vary the mechanical and electrical properties across the thickness. A single length-scale parameter is used in the modified couple stress theory, which accounts for the size effect. Five governing equations including Lorentz force are produced in accordance with Hamilton’s principle and the sinusoidal four-variable plate theory. To determine the critical buckling load and eigenfrequency of the FG sandwich piezoelectric cylindrical shells with lightweight core, an analytical solution to the derived equations is presented. By introducing some comparison examples, the present solution is examined. The study examines the effects of several parameters, including foundation coefficients, temperature rise, moisture concentration, material length-scale parameter, magnetic field parameter, and shell geometry, on the vibration and buckling load of FG sandwich piezoelectric cylindrical shells with a lightweight core.