A novel machine learning model for autonomous analysis and diagnosis of well integrity failures in artificial-lift production systems

The integrity failure in gas lift wells had been proven to be more severe than other artificial lift wells across the industry. Accurate risk assessment is an essential requirement for predicting well integrity failures. In this study, a machine learning model was established for automated and precise prediction of integrity failures in gas lift wells. The collected data contained 9,000 data arrays with 23 features. Data arrays were structured and fed into 11 different machine learning algorithms to build an automated systematic tool for calculating the imposed risk of any well. The study models included both single and ensemble supervised learning algorithms (e.g., random forest, support vector machine, decision tree, and scalable boosting techniques). Comparative analysis of the deployed models was performed to determine the best predictive model. Further, novel evaluation metrics for the confusion matrix of each model were introduced. The results showed that extreme gradient boosting and categorical boosting outperformed all the applied algorithms. They can predict well integrity failures with an accuracy of 100% using traditional or proposed metrics. Physical equations were also developed on the basis of feature importance extracted from the random forest algorithm. The developed model will help optimize company resources and dedicate personnel efforts to high-risk wells. As a result, progressive improvements in health, safety, and environment and business performance can be achieved.Cited as: Salem, A. M., Yakoot, M. S., Mahmoud, O. A novel machine learning model for autonomous analysis and diagnosis of well integrity failures in artificial-lift production systems. Advances in Geo-Energy Research, 2022, 6(2): 123-142. https://doi.org/10.46690/ager.2022.02.0

On the Behavior of Coupled Shear Walls: Numerical Assessment of Reinforced Concrete Coupling Beam Parameters

Modern construction of high-rise and tall buildings depends on coupled shear walls system to resist the lateral loads induced by wind and earthquake hazards. The lateral behavior of this system depends on the structural behavior of its components including coupling beams and shear walls. Although many research studies in the literature investigated coupling beams and shear walls, these studies stopped short of investigating the coupled shear walls as a system. Therefore, in this research, the effect of the coupling beam parameters on the nonlinear behavior of the coupled shear walls system was investigated. The full behavior of a 10-story coupled shear wall system was modeled using a series of finite element analyses. The analysis comprised of testing several coupling beam parameters to capture the effect of each parameter on system response including load-deflection behavior, coupling ratio, crack pattern, and failure mechanism. The results indicated that a span-to-depth ratio equal to two is a turning point for the coupling beam behavior. Specifically, the behavior is dominated by ordinary flexure for a ratio of more than two and deep beam behavior for a ratio of less than two. This study showed that the coupling beam width does not have a significant effect on the coupled shear wall response. Additionally, it was concluded that the excessive coupling beam diagonal reinforcement could significantly affect the coupled shear walls behavior and therefore an upper limit for the diagonal reinforcement was provided. Moreover, limitations on the longitudinal and diagonal reinforcement and stirrups are presented herein. The analysis results presented in this paper can provide guidance for practitioners in terms of making decisions about the coupling ratio of the coupled shear walls.&nbsp

Effect of drilling and wellbore geometry parameters on wellbore temperature profile: Implications for geothermal production

Prediction of the wellbore fluids and formation temperatures is crucial during drilling operation, especially for high temperature wells, such as geothermal applications. This work presents the applications of an improved comprehensive drilling simulator for predicting the wellbore system temperature during the drilling process. A fully transient numerical model of the wellbore temperature is developed for drilling and geothermal production applications. The model describes the dynamic behaviour of the thermal state of the wellbore during circulation and static conditions. The developed model is implemented with the commercial virtual drilling simulator through an application programming interface. This implementation allows the coupling of the thermal model with other physical models, which leads to more advanced and realistic simulations. The model has been previously validated through a direct comparison with field data from geothermal well located in the Hanover area in Germany. The results showed a good agreement between the predicted outlet fluid temperature and the measured one. Furthermore, an analysis of the effect of various parameters on the wellbore system temperature is performed. This analysis showed the impact of these parameters on the wellbore temperature profile including the critical areas such as the casing setting point and bottom hole assembly. This information may lead to enhancing the wellbore stability by monitoring the thermal stresses, especially in high-temperature wells. Moreover, predicting the drill bit temperature can result in increasing the lifetime of the bit by adjusting the operating conditions to keep the bit temperature within the specified range. Based on these results, the enhanced drilling simulator with the transient temperature model showed to be a suitable tool for effective well planning.Document Type: Original articleCited as: Abdelhafiz, M. M., Oppelt, J., Mahmoud, O., Hegele, L. A. Effect of drilling and wellbore geometry parameters on wellbore temperature profile: Implications for geothermal production. Advances in Geo-Energy Research, 2023, 8(3): 170-180. https://doi.org/10.46690/ager.2023.06.0

Plasma and intracellular (platelet) zinc levels in chronic renal failure (CRF) patients under different treatment modalities

The causes and degree of zinc (Zn) deficiency in uraemia are still controversial. The effect of different treatment modalities are still unsettled. Plasma Zn represents only a small part of the total body Zn (about 0.5%). Thus determination of intracellular Zn in the peripheral blood cells might be more reliable. The present study was designed to assess the actual Zn status in uraemia and to find whether the treatment modalities of CRF (conservative and dialytic) could influence Zn status. Also to determine the elfeet of single dialysis session, type of dialysis and dialysate buffer on the Zn status.This study included ten healthy controls and fourty CRF patients divided in three subgroups on different treatment modalities (10 conservative treatment, 15 on intermittent perioneal dialysis ((IPD) and 15 on haemedialysis (HD). Zinc was measured by atomic absorption spectrophotometry in plasma and platelets. Statistically significant decrease of plasma Zn and significant increase of platelet Zn were found in CRF patients on different treatment modalities as compared to controls (P<0.01), but there was no significant difference in this respect hetween the three uraemic subgroups. There was no difference as regard serum protein and albunun levels in uraemic subgroups compared to controls. Moreover plasma Zn was significantly increased (still less than control) and platelet Zn was significantly decreased (P<0.01) after a single dialysis session in both IPD and HD subgroups, but the changes of both parameters (before and after dialysis) were insignificant in IPD patients compared to HD patients.Significant negative correlation was found between platelet Zn and creatinine clearance in the three uraemic subgroups (r = -0.81 P<0.01 in conservative patients, r= -0.72 P<0.01 in IPD and r= -0.76 P<0.01 in HD) while no correlation could be detected between the duration of dialysis and each of platelet & plasma Zn and between plasma Zn and each of platelet Zn, serum creatinine and clearance. Plasma Zn showed transient significant rise in HD patients using bicarbonate (11.6 ± 1.1 umol/L) as compared to those using acetate buffer (9.1 ± 1.3 umol/L), P<0.01. We can conclude that intracellular measurements of Zn (platelet) is of value in diagnosis and monitoring of Zn status in uraemics. Different treatment modalities does not influence Zn haernostasis. with no superiority of particular type of dialysis in this respect. The effect of a single dialysis session and the use of bicarbonate versus acetate buffer was just a transient rise of plasma Zn due to haemoconcentration and better correction of acidosis during dialysis

Effect of physical therapy rehabilitation program (exercise-therapy) on Irritable Bowel Syndrome

To evaluate the effect of physical therapy rehabilitation program consisted of moderate intensity aerobic exercise training (60% MHR) (Maximum Heart Rate) treadmill training on irritable bowel syndrome (IBS) symptom and quality of Life in post cholecystectomy patients. Thirty post cholecystectomy patients complaining from irritable bowel syndrome were recruited for this study; age ranged from 25 to 40 years, Patients were divided randomly into two equal groups, Group (A): received 4 weeks moderate intensity aerobic training program (60% MHR treadmill training (3 sessions per week) plus routine medical treatment protocol, Group (B): received routine medical care only. Patients assessed by Irritable Bowel Syndrome Symptom Severity Score (IBS-SSS) and Irritable Bowel Syndrome Quality of Life (IBS-QOL), Assessment was carried out before treatment and 4 weeks after treatment in both groups. Results showed that there was a significant decrease in post treatment values of IBS-SSS and IBS-QOL in comparison to pre-treatment values at both groups with (p-value < .001). Comparison between both groups post treatment showed significant difference in IBS-SSS and IBS-QOL variables, in group (A) more than group (B). Moderate intensity aerobic exercise training (60% MHR) for 4 weeks is effective in treatment of IBS post cholecystectomy through reducing IBS symptoms and improving Quality of Life

Exogenous glutathione-mediated tolerance to deficit irrigation in salt-affected Capsicum frutescence (L.) plants is connected with higher antioxidant content and ionic homeostasis

As an important medicinal plant used in traditional and modern medicine, chili peppers are sensitive or moderately sensitive to drought or salt stress, respectively. Therefore, potential changes due to foliar-applied glutathione (GSH; 0, 0.4 and 0.8 mM) response on growth, yield, and physio-biochemical attributes, as well as water use efficiency (WUE) and fruit alkaloid capsaicin of chili pepper plants were investigated when grown under deficit irrigation in salt-affected soil (EC = 6.74 dS m–1). Two deficit irrigation water (DiW) regimes (80% and 60% of soil field capacity; FC) were used versus 100% of FC as a control. Both DiW treatments negatively affected growth and yield parameters, SPAD chlorophyll index, nutrient status, K+/Na+ ratio, and plant anatomical features. In contrast, osmoprotectants, ascorbate, glutathione, capsaicin, and phenolic contents, as well as WUE were increased in association with higher Na+ and Cl– contents. However, exogenously-applied GSH caused significant increases in the above-mentioned parameters along with an additional increase in osmoprotectants, antioxidants, and capsaicin contents, and a decrease in Na+ and Cl– levels compared to corresponding controls. The highest WUE, growth, and fruit yield responses were recorded at 0.8 mM GSH applied to plants under DiW at 80% FC + salinity (6.74 dS m–1). Therefore, this study suggested the use of leafy-applied GSH at 0.8 mM for satisfactory growth and yield with the highest WUE of chili pepper plants grown under salt-affected conditions with deficit irrigation

An effective transmit packet coding with trust-based relay nodes in VANETs

ehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate

Genetic distance and heterogenecity between quasispecies is a critical predictor to IFN response in Egyptian patients with HCV genotype-4

BACKGROUND: HCV is one of the major health problems in Egypt, where it is highly prevalent. Genotype 4 is the most common genotype of HCV and its response to treatment is still a controversy. METHODS: HCV genotype 4 quasispecies diversity within the 5' untranslated region (5'UTR) was studied in a series of 22 native Egyptian patients with chronic hepatitis C virus with no previous treatment who satisfied all NIH criteria for combined treatment of pegylated IFN and ribavirine and was correlated with the outcome of treatment. The study also included 7 control patients with no antiviral treatment. HCV sequencing was done using the TRUGENE HCV 5-NC genotyping kit. RESULTS: At the 48(th )week of treatment, 15 patients (68%) showed virological response. Whereas HCV-RNA was still detected in 7 patients (32%) in this period; of those, 6 experienced a partial virological response followed by viral breakthrough during treatment. Only one patient did not show any virological or chemical response. The four females included in this study were all responders. There was a significant correlation between the response rate and lower fibrosis (p = 0.026) as well as the total number of mutation spots (including all the insertions, deletions, transitions and transversions) (p = 0.007, p = 0.035). CONCLUSION: Patients who responded to interferon treatment had statistically significant less number in both transitions (p = 0.007) and the genetic distances between the quasispecies (p = 0.035). So, viral genetic complexity and variability may play a role in the response to IFN treatment. The consensus alignment of all three groups revealed no characteristic pattern among the three groups. However, the G to A transitions at 160 was observed among non responders who need further study to confirm this observation

Comparative Study: PRP Enhanced Fat Graft Versus Fat Graft Alone in Treatment of Postacne Scars with Clinical and Histopathological Eyes

Fat grafting has a role in rejuvenation owing to its mesenchymal cell precursor content especially with growth factors added. Platelet Rich Plasma (PRP) is known for its high growth factor content. The objective of this study is to compare the effect of PRP when added to fat graft in acne scars. 28 patients were randomly divided into 2 groups. Group A was treated with fat grafting while group B was treated with PRP enhanced fat grafting. All patients received a single treatment session. Assessment was conducted by comparing digital photos and biopsies before and after 6 months of treatment. The results shows that acne scars improved with PRP enhanced fat graft (93%) more than fat graft (64%). The biopsy results also confirmed the significantly better improvement for PRP group (85.7%) than the fat graft group (58%) (p=0.042). PRP has provided an enhancement of fat grafting in treatment of post acne scars. Icepick scars were better treated by fat grafting alone, while rolling and boxcars showed better results with the addition of PRP

Enhancing Parkinson's disease diagnosis accuracy through speech signal algorithm modeling

Parkinson's disease (PD), one of whose symptoms is dysphonia, is a prevalent neurodegenerative disease. The use of outdated diagnosis techniques, which yield inaccurate and unreliable results, continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field. To solve this issue, the study proposes using machine learning and deep learning models to analyze processed speech signals of patients' voice recordings. Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers. Results were highly successful, with 90% accuracy produced by the random forest classifier and 81.5% by the logistic regression classifier. Furthermore, a deep neural network was implemented to investigate if such variation in method could add to the findings. It proved to be effective, as the neural network yielded an accuracy of nearly 92%. Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients' voices. This research calls for a revolutionary diagnostic approach in decision support systems, and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD