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Reservoir simulation is required to aid in the decision-making for high-impact projects. It is a culmination of geophysical, geological, petrophysical, and engineering assessments of sparse, uncertain, and expensive data. History matching is a process of elevating trust in numerical models as they are calibrated to mimic the behaviour of the real-life asset. Traditional history matching relies on direct parameter assignment based on flat files used as input to the reservoir simulator. This enables a convenient method for the perturbation of uncertain parameters and their value assignments during the history matching process. Given the nature of the input files, the scope for uncertainty parameters is limited to the original petrophysical properties, their derived simulation properties in a specified group of grid blocks, and occasionally extended to include fluid and multiphase flow properties. However, there are key influential model-building steps prior to reservoir simulation related to data interpretation. These steps control not only the values of petrophysical properties but also their spatial correlation, cross-correlation, and variability. The limitation in the scope for parameterization adds bias to the model calibration process, hence negatively impacting its outcome. In an era where ML/AI algorithms are shaping data interpretation methods, key modelling decisions can be revisited to realize the maximum value of subsurface data. However, a framework is required whereby these important model-building steps are captured in history matching to eliminate bias and ensure the geological consistency of the subsurface model during and after history matching. This paper demonstrates a liberated workflow to calculate the recommended parameters that achieve the minimum mismatch score. The workflow is executed through a cloud platform offering compute elasticity to expedite the history matching workflow. It is composed of three main steps. The first step is data loading, where simulation results and parameters are extracted from the submitted ensemble(s). Meanwhile, the second step involves data preparation and cleaning. Wells devoid of data are removed, and scaled metrics are created to calculate the mismatch score. The simulation ID then groups the data to get a field-level aggregation. The now aggregated and cleaned simulation results are merged with the parameters list to create the input dataset to the final step, where several machine learning models are trained and evaluated in parallel. The data is split into training and testing datasets. The target variable is the mismatch score, as the models are trying to predict the mismatch for a given set of parameters. Supervised learning regression algorithms were used. The best-performing ones were found to be random forest and gradient boosted trees. After fine-tuning the machine learning models and evaluating them based on their coefficient of determination (R2 score), the best fitting model is used to calculate the optimized parameters. This happens iteratively by generating new series of parameters within a range and using the machine learning model to predict the mismatch for each until the lowest mismatch is found. The parameters resulting in the minimum mismatch are the recommended parameters. This workflow is implemented on a simulation model built for a mature gas condensate field in the Mediterranean of Egypt. The field comprises three anticlines with a spill-fill Petroleum system, where the majority of the wells are in one of the anticlines. In contrast, the other anticlines have few wells and are candidates for appraisal. Moreover, there is high uncertainty in the sand distribution and reservoir properties, spill points depth, depletion, and observing an explained phenomenon of a sustainable gas water contact in the new anticline even after 30 years of production from the old Anticline. This uncertainty in the understand of the relation between the two anticlines makes the selection of the drilling locations a challenge. To Assess remaining reservoir volumes and identify potential infill targets, we used the ML to study all the uncertainties combinations in a full-loop approach from static to dynamic model and generate multiple representations that honour the geological understanding. The cloud-based Agile reservoir modeling approach enriched with ML / AI algorithms enabled us to generate Multiple realizations that match 30 years of historical production and pressure profiles capturing many possible combinations of uncertain geological parameters and concepts. In addition, several forecast scenarios for 3 new appraisal wells were optimized based on the ensemble of history matched models minimizing the risk of drilling dry wells. In addition to going through the work process and results, this paper highlights the method's practical effectiveness and common issues in practical application. The use of the cloud-based technology had a great cost saving and efficiency improvements, for example giving the existing on-premises Infrastructure would take 1-2 years to achieve the same results that was achieved in 1-2 months and cost saving around 1 million dollars in cluster hardware purchase. Moreover, Cloud based technology enable collaborative, iterative working styles for integrated teams and access to scalable technologies that are developed on cloud only.

Background: Soft tissue normal values represent useful guidelines for proper diagnosis and evaluation of orthodontic patients. The objective of this cross-sectional study is to determine the normal values of the vertical facial soft tissue of Egyptian female adolescents. Methodology: Thirty female Participants 11-15 years of age with balanced facial proportions, full permanent dentition and Angle Class I molar and canine relationship were included in this study. Three-dimensional surface data was acquired using Planmeca ProMax 3D ProFace unit. The participant’s data was admitted to the Planmeca Romexis 4.5.0.R software in the associated computer unit prior to the imaging procedure. For all processed images five standard anthropometric landmarks were identified to perform our measurements: Trichion (Tr`), Gnathion (Gn`), Nasion(N`), Subnasale (Sn`) and Sublabiale (Sl`). Results: The mean anterior face height (Tr-Gn’) for the total sample was found 172.6mm±7.99mm. While, the mean height of the forehead (Tr-N’) for total sample was 63.6mm ±7.5mm. The mean morphological height of the face (N’-Gn) was 112.6mm +6.4mm The mean lower face height (Sn-Gn’) was 64.2mm ±5.3mm. The chin height (Sl-Gn’) for the total sample was 22.9mm±2.6mm. Conclusion: Soft tissue normal values represent useful guidelines for proper diagnosis and evaluation of orthodontic patients. Most of the facial measurements of Egyptian female adolescents were can be different or similar according to different ethnic groups.

Introduction: Digital models showed promising results for orthodontic diagnosis and treatment planning. Digital models can be obtained from alginate impressions as well as direct intra-oral scanners. Studies assessing the accuracy of digital models have shown digital models to be valid, clinically acceptable, and more quickly obtainable. With the advent of new scanners with better scanning technology researches are necessary to evaluate their accuracy and reliability. Aim of Study: To evaluate the diagnostic accuracy of 3D digital models obtained through intraoral and extraoral scanning modalities to the reference gold standard plaster model. Material & Methods: Twenty-four adult male and female subjects were randomly selected for this study. The intraoral scanners evaluated in this study were Sirona (CEREC Omnicam) and 3 shape (TRIOS 3), while the laboratory scanners used were Sirona (inEos X5), and 3 shape (D850). Intra-oral scanning of the subjects and extra-oral scanning of their alginate impressions, plaster models of the alginate impression, rubber base impression, and plaster model of their rubber base impression were done. Linear dental measurements included intermolar width, interpremolar width, intercanine width, mesiodistal width of the 1st permanent molar, 1st premolar, canine and central incisor and arch width. All data were collected, tabulated and subjected to statistical analysis. Results: Small differences between the plaster and digital models were observed. Intra-observer reliability analysis for 14 out of the 16 measurements showed that all variables exhibited good to excellent reliability. Conclusions: There was no difference between the digitization using the intraoral scanner or the laboratory scanner. The most accurate digitization technique was the 3 Shape laboratory scanner of the cast of the alginate impression. The inEos X5 showed the highest error of digitization of the alginate and rubber base impressions.

Aims To investigate the transverse dental and skeletal aspects of malocclusion in a sample of temporomandibular disorders (TMD) patients and to assess the correlations of these aspects with the signs and symptoms of TMD. Methods A total of 150 TMD patients diagnosed according to the Diagnostic Criteria for TMD were divided into five groups: Group 1 (myalgia), Group 2 (disc displacement with reduction [DDWR]), Group 3 (disc displacement without reduction [DDWOR]), Group 4 (degenerative disorders), and Group 5 (subluxation). The transverse occlusion was assessed clinically, and any posterior crossbite present was recorded. Using cone beam computed tomography, several skeletal and dental transverse measurements were evaluated in each patient to diagnose the presence of skeletal posterior crossbite and possible facial and dental asymmetry. One-way analysis of variance was used to compare the means of more than two groups. Pearson correlation coefficient was used to assess the correlations of quantitative continuous variables. Significance level was considered at P Results Posterior crossbite was found in only 18% of the sample, while 28.7% of the subjects showed transverse skeletal crossbite. All skeletal and dental measurements evaluating symmetry showed no statistically significant differences between the groups except for the occlusal plane cant, which was significantly higher in Group 2 compared to Group 1. Dental and skeletal transverse discrepancies showed no correlation with TMD. Conclusions Transverse malocclusion is not correlated with the signs and symptoms of TMD.

Structured AbstractObjectives This study sought to investigate the three-dimensional (3D) changes in anteroposterior, vertical and mediolateral positions and orientations of the mandibular condyle as well as joint space parameters following maxillary first premolar extraction and incisor retraction in skeletal Class II patients. Setting and Sample Population Thirty patients were treated by orthodontic maxillary first premolar extraction at the Faculty of Oral and Dental Medicine, Cairo University, Egypt. Materials and Methods Cone beam computed tomography (CBCT) analysis was performed in patients pre- and post-treatment. Sixty joints were evaluated based on the volumetric images, and the following 3D measurements were evaluated: (i) mandibular condylar position relative to the cranial base and the joint itself, (ii) condylar inclination and (iii) anterior, posterior, superior and medial joint spaces. Results There was a statistically significant (P≤.05) posterior positioning of the condyle relative to the vertical plane. The distance increased significantly from 5.77 to 6.82 mm as this plane is anterior to the mandibular condyle. There was an increased anterior joint space (from 3.10 to 3.90 mm) and decreased posterior joint space (from 2.78 to 2.23 mm) following treatment. No changes were observed in mediolateral and vertical condylar positions. Conclusions Posterior positioning of the condyle after orthodontic extraction and incisor retraction may occur, but its clinical significance requires further assessment in future studies.

Gravel pack completion operations are a sand production management technique that is considered successful if the well produces no sand and has minimal impact upon the potential productivity and hydrocarbon recovery. However, statistics show that many gravel packed wells suffer reduced productivity as a result of damaging mechanisms induced by gravel pack operations and completion fluids. This provides an opportunity for improved hydrocarbon recovery if the mechanisms are understood. A study was conducted to simulate the alterations caused by the gravel pack operations including gravel carrier fluid, completion fluid and lost circulation material. Simulations using reservoir core samples were carried out at near-wellbore conditions, in order to examine operational fluid interactions with the reservoir and assess the impact of a stimulation fluid. Cores from a range of rock types were selected, and prepared to initial gas-leg saturation. An operational sequence consisting of completion fluid, gas production, stimulation fluid, completion fluid, and production of gas was carried out, with permeability measurements before and after the sequence. In all core samples, the introduction of the completion fluid during gravel pack installation resulted in alterations of 30-60% reduction in core permeability. Geological interpretative analysis showed damage mechanisms including clay fines movement and pore blockage, dissolution of native cement, and retention of operational fluid in the pores. It was believed that retention of fluids was having the most significant impact upon permeability. Stimulations were carried out for all samples to quantify the effect of acid on removing the formation damage resulting from the gravel pack operations. The experiments showed 5-10% improvement on average except for one core sample, which showed 40% improvement. Based upon the previous results, a modified sequence was examined, utilizing an alternative stimulation fluid/acid sequence and adding an extra operational stage. The experiments showed that after treatment an improvement of around 10% was noted, and after an additional stage, a further 8% improvement was seen. The final permeability was over 80-90% of the initial permeability, indicating that there was the potential for good productivity and recovery of hydrocarbons. The results of the study were applied to seven gravel pack jobs in three wells and the field results showed the reduction in productivity after gravel pack installation was around only 10%, compared to previous wells which showed more than 50% reduction in productivity.

Aims To investigate the dental and skeletal aspects of malocclusion in the anteroposterior and vertical dimensions in a sample of temporomandibular disorders (TMD) patients and to correlate these aspects with the signs and symptoms of TMD. Methods A total of 150 TMD patients were divided into five groups according to the Diagnostic Criteria for TMD: Group 1 = myalgia (M); Group 2 = disc displacement with reduction (DDWR); Group 3 = disc displacement without reduction (DDWOR); Group 4 = degenerative disorders (D); and Group 5 = subluxation (S). Molar and canine relations, overjet, overbite, occlusal guidance, occlusal interferences, and centric slides were recorded for each patient, and the skeletal craniofacial patterns were analyzed for each patient using cone beam computed tomography. One-way analysis of variance was used to compare the variable means of the different groups. Pearson correlation coefficient was used to assess the correlations of quantitative continuous variables. Significance level was considered at P Results No significant difference was found among the groups regarding any aspects of dental occlusion except for mediotrusive interferences, which were significantly higher in Group 3 (DDWOR) (P = .02). Regarding skeletal craniofacial pattern, Group 4 (D) had significantly smaller mean ± standard deviation sella-nasion-B (SNB) point angle (74.31 ± 3.04 degrees) than Group 3 (DDWOR) (78.04 ± 4.88 degrees), and Group 1 (M) showed the greatest SNB angle (79.87 ± 3.73 degrees) (P = .03). Group 3 (DDWOR) showed significantly greater mean mandibular plane/SN angle (39.56 ± 6.19 degrees) than Group 1 (M) (34.73 ± 5.65 degrees) (P = .04). Relations between occlusal variables and TMD parameters were nonsignificant. Conclusion This study provides robust evidence to diminish the TMD-malocclusion association, especially in myogenic types of TMD.

Background To investigate three-dimensionally using cone beam computed tomography (CBCT) morphological and spatial characteristics of the temporomandibular joints (TMJs) in different anteroposterior skeletal malocclusions. Materials and Methods Pretreatment CBCT scans of 60 young adult patients (18–25 years) were obtained. Among those patients, 20 were characterized as Skeletal Class I, 20 as Skeletal Class II, and 20 as Skeletal Class III malocclusion. Bilateral TMJs were evaluated on the CBCT images and the following three-dimensional measurements were assessed: (1) mandibular fossa position, inclination, and parameters; (2) mandibular condyle position, inclination, and parameters; and (3) circumferential TMJ space measurements. Results Class II patients showed the lowest condylar width (6.47 ± 1.14 mm), the highest condylar height (11.14 ± 1.99 mm), and the highest anterior joint space (2.73 ± 1.14 mm). Class III patients exhibited the lowest anterior (2 ± 0.57 mm), superior (2.92 ± 0.63 mm), and medial joint spaces (2.18 ± 0.72 mm), and the highest mandibular fossa width (19.12 ± 2.48 mm), as well as the highest anteroposterior condylar dimension (7.43 ± 1.50 mm). The three skeletal malocclusions differed significantly in the vertical condylar position (Class III had the most superior and Class II had the most inferior position). Conclusions There are significant differences in specific TMJ parameters between different skeletal malocclusions that might play a role in development of temporomandibular disorders with or without orthodontic treatment.

Objectives: To evaluate the effect of hydroxyapatite nanoparticles’ addition and determine the utility role of CO2 laser in improving esthetics of enamel surfaces after debonding. Methods: 90 extracted human premolars were used. 10 teeth were used as a control group. Trans bond Plus Self Etching Primer with Trans bond Supreme Low Viscosity Light Cure Adhesive, 3M/Unitek, was used to bond the orthodontic brackets (NU-EDGE.022" ROTH RX.TP Orthodontics) to the labial enamel surfaces. All specimens were stored in artificial saliva for 6 months. Orthodontic brackets were then removed using bracket removing pliers (Ortho Organizers, Carlsbad, USA).Residual composite removed by Sof-Lex finishing discs. The 80 teeth were divided randomly into 4 groups (n=20) according to the protocol of nanoparticles’ addition, 1) no nanoparticles were added, 2) nanoparticles suspended in water and rubbed on the dry enamel surface, 3) nanoparticles suspended in ethanol and rubbed on the etched enamel surface, and 4) nanoparticles suspended in bonding agent [Single Bond 2 adhesive (SB)] & rubbed on the etched enamel surface. Each group assigned into two subgroups (n=10) according to exposure to CO2 laser (9.6μm), where enamel of the first subgroup was irradiated at 3W; 20Hz; 4sec and 212J/cm2 while the other subgroup was not irradiated. The SE bonding agent was applied to the third group after its treatment. Specimens were tested for color changes using Quanta Environmental Scanning Electron Microscope. Data were statistically analyzed using two-way Analysis of Variance (ANOVA) and Tukey’s post-hoc test. Results: highest mean color value was found with no particles. There was no significant difference between group 1 and 2. There was no difference between groups 3 and 4; both showed the statistically significant lowest mean color values. Meanwhile, no significant effect was found between laser and non-laser subgroups. Conclusions: the addition of hydroxyapatite nanoparticles improved the enamel esthetics after brackets debonding.

Background To investigate three-dimensionally using cone beam computed tomography (CBCT) imaging the morphological and spatial characteristics of the temporomandibular joints (TMJs) in different vertical skeletal facial patterns. Materials and Methods Sixty adult patients with no signs and symptoms of temporomandibular disorders were divided equally into three groups: skeletal normal vertical face, long face, and short face malocclusions. Bilateral TMJs were evaluated on the CBCT images, and the following three-dimensional measurements were assessed: (1) mandibular fossa position, inclination, and parameters, (2) mandibular condyle position, inclination, and parameters, and (3) circumferential TMJ space measurements. Results The average mandibular plane inclination was 32.77 ± 1.17° for average pattern, 48.33 ± 2.76° for long face, and 27.27 ± 2.30° for short face malocclusion. Long face showed the statistically significant highest glenoid fossa width (18.34 ± 2.20 mm), more lateral positioned condyles, and more anterioposterior condylar joint position. The long face pattern showed the highest mean value of medial joint space. The short face pattern showed the highest glenoid fossa surface area (106.40 ± 14.68 mm 2 ), sagittal condylar surface area (48.47 ± 4.54 mm 2 ), and superior and anterior joint spaces, as well as lowest posterior joint spaces. Conclusion The TMJ parameters differ between different vertical facial patterns that should be considered when planning an orthodontic case.

To investigate the effect of low-intensity laser therapy on mini-implant stability using resonance frequency analysis during canine retraction with fixed appliances.A split-mouth randomised clinical trial.Subjects were recruited and treated in the outpatient clinic, Department of Orthodontics, Faculty of Dentistry, Cairo University.Fifteen subjects with mean age 20.9 (±3.4) years who required extraction of maxillary first premolar teeth and mini-implant-supported canine retraction.Thirty orthodontic mini-implants were inserted bilaterally in the maxillary arches of recruited subjects following alignment and levelling. Mini-implants were immediately loaded with a force of 150 g using nickel titanium coil springs with split-mouth randomisation to a low-intensity laser-treated side and control side. The experimental sides were exposed to low-intensity laser therapy from a diode laser with a wavelength of 940 nm at (0, 7, 14, 21 days) after mini-implant placement. Mini-implant stability was measured using resonance frequency analysis at (0, 1, 2, 3, 4, 6, 8, 10 weeks) after implant placement.A total sample of 28 mini-implants were investigated with 14 in each group. Clinically, both mini-implant groups had the same overall success rate of 78.5%. There were no significant differences in resonance frequency scores between low-intensity laser and control sides from baseline to week 2. However, from week 3 to 10, the low-intensity laser sides showed significantly increased mean resonance frequency values compared to control (P 0.05).Despite evidence of some significant differences in resonance frequency between mini-implants exposed to low-intensity laser light over a 10 weeks period there were no differences in mini-implant stability. Low-intensity laser light cannot be recommended as a clinically useful adjunct to promoting mini-implant stability during canine retraction.

A new method is devised for locating a single crack in a frame.Simulated noise free and contaminated natural frequency measurements are considered.Noise free measurements yield pointed predictions.Noisy measurements yield crack location ranges.Empirical probability distributions can be used to illustrate the crack location ranges. A new method is devised for locating a single crack in a frame using natural frequency degradations. Simulated noise free and contaminated natural frequency measurements are considered. The frame is discretised into a number of points. Selected natural frequencies are calculated using the Wittrick-Williams algorithm in the uncracked case and when the crack is placed at each point individually. The variation between the uncracked and cracked frequencies is normalised in the analytical and measured cases. Exact simulations yield point crack locations. Applying interval arithmetic, simulated contaminated measurements give crack location ranges. The combined ranges are illustrated by empirical probability distributions.

The problem of calculating the natural frequencies of beams with multiple cracks and frames with cracked beams is studied. The natural frequencies are obtained using a new method in which a rotational spring model is used to represent the cracks. For beams, dynamic stiffness matrices of order 4 are obtained in a recursive manner, according to the number of cracks, by applying partial Gaussian elimination. The Wittrick–Williams algorithm is used to compute the natural frequencies in the resulting transcendental eigenvalue problem. Published numerical examples for cracked beams are used for validation. The global dynamic stiffness matrix of a frame with multiply cracked members is then assembled. A published two bay frame example is used to evaluate the new method. The effect of changing the location of a crack in a two bay two storey frame is studied numerically, giving insight into the inverse problem of damage detection.