Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

In this work, the use of type-2 fuzzy logic systems as a novel approach for predicting permeability from well logs has been investigated and implemented. Type-2 fuzzy logic system is good in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crisp value; rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associated with predicting permeability from well log data, where uncertainties are very high and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed type-2 fuzzy logic system framework with those earlier used methods, using five different industrial reservoir data. Empirical results from simulation show that type-2 fuzzy logic approach outperformed others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost.     

Functional networks as a new data mining predictive paradigm to predict permeability in a carbonate reservoir

Permeability prediction has been a challenge to reservoir engineers due to the lack of tools that measure it directly. The most reliable data of permeability obtained from laboratory measurements on cores do not provide a continuous profile along the depth of the formation. Recently, researchers utilized statistical regression, neural networks, and fuzzy logic to estimate both permeability and porosity from well logs. Unfortunately, due to both uncertainty and imprecision, the developed predictive modelings are less accurate compared to laboratory experimental core data. This paper presents functional networks as a novel approach to forecast permeability using well logs in a carbonate reservoir. The new intelligence paradigm helps to overcome the most common limitations of the existing modeling techniques in statistics, data mining, machine learning, and artificial intelligence communities. To demonstrate the usefulness of the functional networks modeling strategy, we briefly describe its learning algorithm through simple distinct examples. Comparative studies were carried out using real-life industry wireline logs to compare the performance of the new framework with the most popular modeling schemes, such as linear/nonlinear regression, neural networks, and fuzzy logic inference systems. The results show that the performance of functional networks (separable and generalized associativity) architecture with polynomial basis is accurate, reliable, and outperforms most of the existing predictive data mining modeling approaches. Future work can be achieved using different structure of functional networks with different basis, interaction terms, ensemble and hybrid strategies, different clustering, and outlier identification techniques within different oil and gas challenge problems, namely, 3D passive seismic, identification of lithofacies types, history matching, rock mechanics, viscosity, risk assessment, and reservoir characterization.     

Investigating the effect of training–testing data stratification on the performance of soft computing techniques: an experimental study

Abstract

Cross-validation of soft computing techniques needs to be done efficiently to avoid overfitting and underfitting. This is more important in petroleum reservoir characterisation applications where the often-limited training and testing data subsets represent Wells with known and unknown target properties, respectively. Existing data stratification strategies have been haphazardly chosen without any experimental basis. In this study, the optimal training–testing stratification proportions have been rigorously investigated using the prediction of porosity and permeability of petroleum reservoirs as an experimental case. The comparative performances of seven traditional and advanced machine learning techniques were considered. The overall results suggested a recommendable optimum training stratification that could serve as a good reference for researchers in similar applications.     

Dietary Supplementation of Tetracarpidium conophorum (African Walnut) Seed Enhances Muscle n‐3 Fatty Acids in Broiler Chickens

The influence of dietary Tetracarpidium conophorum (African Walnut) seed meal (TCSM) on fatty acids, productivity parameters, and physicochemical properties of breast and thigh muscles in broiler chickens are assessed. A total of 180, 28‐d‐old Arbor acre broiler chickens are randomly assigned to dietary treatments containing 0% (control), 2.5%, and 5% w/w TCSM, fed for 28 d, and euthanized. Dietary TCSM reduces (p < 0.05) feed intake, body weight gain (BWG), carcass weight, and abdominal fat. Diet does not affect feed efficiency and hematological parameters. The control birds have higher (p < 0.05) serum total cholesterol and triglycerides than do the supplemented birds. Diet has no effect on pH, water holding capacity, carbonyl and malondialdehyde contents, and organoleptic properties of breast and thigh muscles. The 5% TCSM has higher redness in breast muscle than do other treatments. Dietary TCSM improves (p < 0.05) the concentration of C18:3n‐3 (4.80–8.76% vs 1.56%), C20:5n‐3 (0.54–0.79% vs 0.39%), C22:5n‐3 (0.64–0.89% vs 0.18%), and C22:6n‐3 (0.75–0.97% vs 0.19%), and reduces (p <  0.05) the fat content (2.15–2.45% vs 3.15%) in breast and thigh muscles. Dietary TCSM enhances muscle n‐3 fatty acids without instigating oxidative deterioration, but reduces BWG in broiler chickens. Practical Application: Albeit that broiler meat is rich in polyunsaturated fatty acids (PUFA), its omega 6 (n‐6)/omega 3 (n‐3) is >4. Elevated n‐6/n‐3 could have adverse effect on human physiology thereby promoting the pathogenesis of certain diseases. This heightens the need to enhance the n‐3 PUFA content of broiler meat. Dietary TCSM induced up to a fourfold increase in n‐3 PUFA content of the breast and thigh muscles in broiler chickens. Moreover, dietary TCSM induced up to a tenfold decrease in the n‐6/n‐3 of the breast and thigh muscles in broiler chickens. This finding assumes great significance because the health concerns regarding dietary fat are the foremost factors responsible for the bad image suffered by meat. These results provide insights on the potential of TCSM to improve the nutritional quality without compromising the oxidative shelf life, organoleptic traits, and physicochemical properties of broiler meat.     

New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network

Neural Computing and Applications - Permeability is an important parameter for oil and gas reservoir characterization. Permeability can be traditionally determined by well testing and core...     

Synthesis of polypyrrole–Nafion composite films by gas phase electroformation

Nafion was introduced into polypyrrole (PPy) matrix by gas phase electrochemical polymerisation. This produced a uniform, homogeneous and conductive thin film of composite polymer. The films (PPy/Nafion) also show surface features of highly ordered structural regularity. The composites obtained were characterised by cyclic voltammetry (CV) and redox performance were investigated. The relationship of the anodic current of the composite with the various experimental parameters such as concentration of Nafion, current density, polymerisation time and temperature were investigated. Anodic current increases with the Nafion concentration, polymerising time, temperature and current density.     

Antioxidant and antithrombotic effects of green mussels (Perna canaliculus) in rats

In the past decade, the use of marine mussels as seafood is being more popular. They considered being a rich source of various nutritional bioactive compounds that aroused the scientific community's interest. This study investigated the antioxidant and the antithrombotic consequences on Sprague-Dawley male rats after adding dried New Zealand mussel Perna canaliculus in their diet. The biochemical, hematological and histopathological changes were also observed. Forty rats were divided into four groups according to the amount of dried mussels in their diet, in addition to a control group that consumed a basal diet only. Group 1 consumed 25% dried mussels in its basal diet; Group 2 consumed 35% dried mussels in its basal diet, and Group 3 was consumed 45% dried mussels in its basal diet. The biochemical parameters showed improvements in liver function. Interestingly, the lipid profile decreased, especially the low-density lipoprotein cholesterol (LDL-C) levels which were reduced significantly in Group 3 (p < .01). These observations were accompanied by a decrease in iron levels significantly as the amount of dried mussels increased (p < .01). Furthermore, the noticed changes in the hematological profile prove that there is an increase in antithrombotic activity. Dried mussels had potent antioxidant effects in the liver as shown by increased lipid peroxide (p < .05), reduced glutathione (p < .05), and glutathione peroxidase (GSH-Px; p < .05). Additionally, antioxidant activity in the kidney was shown to increase through GSH-Px activity (p < .01). In conclusion, these results indicate that consuming dried mussels resulted in improved biochemical and antioxidants activities and could be used as an antithrombotic agent.     

Inhibition of mild steel corrosion in CO2 and H2S-saturated acidic media by a new polyurea-based material

Oil well acidizing is a common practice used to boost oil well productivity in the industry. This practice, however, exposes the mild steel components of the wells to extremely harsh corrosive environments. Under such conditions, highly efficient inhibitors are used to minimize corrosion attack. In the present study, corrosion inhibition of mild steel in simulated acidic medium saturated with CO₂ and H₂S gases by a newly synthesized polyurea-based material (PUCorr-1) was investigated. Electrochemical studies supported with quantum chemical density-functional theory calculations and surface characterization revealed that PUCorr-1 adsorbs onto mild steel through a chemisorption mechanism yielding a stable protective film. The polyurea exhibited an excellent efficiency of 99.9% at a temperature of 50°C and a low concentration of 100 ppm, yielding a corrosion current density of 0.3 µA/cm². In the presence of CO₂ and H₂S gases, PuCorr-1 exhibited a remarkable performance (>93% efficiency) making it a potential corrosion inhibitor in industrial processes that involve the use of acid solutions in the presence of CO₂ and H₂S gases.     

Multiple light scattering and nanotip effect of hierarchical sea urchin-like W18O49 boosting photocatalytic hydrolysis of ammonia borane

The morphology of catalysts is a key factor influencing their photocatalytic performance. Herein, we prepared three W₁₈O₄₉ photocatalysts with different morphologies of sea urchin (W₁₈O₄₉SU), nanorod (W₁₈O₄₉NR) and hollow sphere (W₁₈O₄₉HS), and evaluate their performances in photocatalytic hydrolysis of ammonia borane (AB). Remarkably, W₁₈O₄₉SU exhibited an impressive photocatalytic H₂ production rate with the highest TOF of 53.1 min^?1 under visible light, which is 10.4 and 7.5 times higher than those of W₁₈O₄₉HS and W₁₈O₄₉NR, respectively. The comprehensive characterizations and control experiments revealed that the unique sea urchin-like morphology enabled the strong light harvesting by multiple light scattering, fast separation of photogenerated charges and directional electron enrichment by nanotip effect, which collaboratively boost the photocatalytic activity. Moreover, the enhancement effect of sea urchin-like morphology is again approved well on Nb₂O₅ photocatalysts. This work opens a paradigm to synergistically improve light harvesting and charge separation efficiency through rational design of photocatalyst nanostructure.