Diagnosing High Water Production in Kalama Field, Niger Delta

Produced water is water trapped in underground formations that is brought to the surface along with oil or gas. It is by far the largest volume by-product or waste stream associated with oil and gas production especially in brown fields. Management of produced water present challenges and costs to operations. In this paper, the possible causes, effects and solutions of high water-cut is being investigated in some production oil wells in Niger Delta, using Kalama field as a case study. Diagnostic and performance plots were developed in order to determine the source of water as well as to evaluate the impact of excess water production on oil production and in field economics in general. Results obtained from the diagnostic plots showed the possible sources of water production are channeling behind casing and multi-layered channeling. The recommended remediation is cementation through a workover operation. Also, a concise step to be taken for identifying excess water was also developed in this work to effectively control excess water production in oil producing wells.

Mathematical Modelling of the Drying Characteristics of Milled Sorghum Residue

During milling of cereal grains, bran which is separated from the starchy endosperm of the grain is a major by-product. In this study, milled sorghum residue was dried in a cabinet dryer under different conditions (temperature and air velocity). The obtained drying data were fitted into ten existing mathematical models and obtained the best model while, the effective moisture diffusivity and activation energy of the drying process was determined using Arrhenius type approach. The result shows that the initial moisture content obtained for the sorghum residue using standard oven drying method were 41.28 ± 0.33%, 49.52 ± 0.63 % and 47.06 ± 0.42 % on wet basis for the wet residue of variety A, B and C, respectively, at equilibrium point, the final moisture content of about 12.93 ± 0.14 – 14.31± 0.07 as temperature ranges from 40 oC to 70 oC and air velocity ranges from 0.8 m/s to 1.2 m/s. During the drying process, the drying rate falls more rapidly as it was initially high as a result of more moisture in the sorghum residue and the drying rate decreases slowly until reaching the reduced moisture content. The obtained values of effective moisture diffusivity (Deff) ranges between 9.89 x 10-10 and 22.21 x 10-10 m2/s, 9.45 x 10-10 and 20.62 x 10-10 m2/s and 8.56 x 10-10 and 20.76 x 10-10 m2/s for variety A, B and C, respectively. However, the result of the modelling shows that the drying characteristics of variety A and B of the sorghum residue can be predicted using Midilli et al. model while the drying behaviour of Variety C can be predicted using Hii et al. model.

Innovative and Sustainable Materials in Architectural Engineering

The advantages of fiber-reinforced polymer (FRP) composite material have attracted architectural engineers as alternative construction materials. FRP materials are noncorrosive, lightweight, exhibit high tensile strength, and stiffness, are easily fabricated and constructed. For architectural applications, FRP materials are fabricated using a polymer matrix, such as epoxy, vinyl ester, or polyester, and reinforced with various grades of carbon, glass, and/or aramid fibers. In this study, FRP coupons have been tested under axial tensile load to evaluate the strength of these materials for architectural application. Coupon specimens were cut from two different types of glass-FRP (GFRP) tubes namely: Type I and II, the two types had constant internal diameter equal to 152 mm. The GFRP tubes Type I consist of six layers with (±60°) fibers angles oriented mainly in the hoop direction with respect to the longitudinal axis of the tubes, the total thickness is 2.65 mm. While GFRP tubes I consist of fourteen layers with different fibers angles (±65, ±45, ±65) and the total thickness are 6.4 mm. The test results were presented and discussed. The strength of the coupon showed an acceptable level to be used for architectural application. Some of the FRP composites successful applications are briefly presented and discussed to provide the appropriate background for the application of FRP composites in architectural engineering. The promising results presented for the GFRP materials represent a further step toward architectural application.

Use of the Correlation Coefficient for Rotating Machine Monitoring

The use of electronics and computer technology in production systems has greatly improved the quality of our industrial products. The productivity of these installations is a function of the maintenance quality applied to the equipment. Several methods are used to monitor the functioning of industrial installations. One of these methods is vibration analysis. The vibration signals from the rotating machines support several types of information related to the working state of the production tool. The processing of this information makes it possible to have decision tools for maintenance. In this work, we propose a method of anticipating the maintenance of rotating machines. The algorithm we propose starts with the removal of 512 point windows during the running time of the ball bearing. Each signal is decomposed by DWT: we obtain the approximation coefficients. These coefficients make it possible to determine the correlation coefficient between the so-called reference window and the other windows following the functioning of the ball bearing. The correlation coefficient is then the fundamental element of the decision. This algorithm has been applied to real vibration data and the results are encouraging.

Modelling of Soil Profile Pollutant Yield on Slaughterhouse Wastes Deposited Land

Aim: The study aimed at modeling the concentration of pollutants along soil profile using finite element method. Study Design: Data was generated from the laboratory on the concentrations of selected heavy metals at varying depths of land discharged slaughterhouses. This was used to estimate the level of nutrient build-up in the soil within these environs, hence, used to verify and validate the finite element analysis. The model upon validation was used to predict the rate of pollutant build-up in the soil within the slaughterhouses discharge areas. Methodology: A total of twelve composite samples were collected from three different land discharged locations. The three composite samples each were collected from the sampling locations at a depth of 0 to 10cm, 10 to 20cm, 20 to 30cm and 30 to 40cm. Four composite samples each were collected for analysis from the three sampling locations on specified sampling dates. The samples were then placed in sterile polythene bags and transported to the laboratory for processing. The laboratory results obtained for heavy metals were used for the generated model verification and validation, hence predictions for pollutants accumulation was done on a time step. Results: Model verification showed a good fit of a nonlinear polynomial curve for both the measured and predicted values with R² values of 0.9978 to 0.9985 for zinc and 0.9978 to 0.9984 for lead at a selected time step of 15years. It was observed however, that there was an increasing tendency to uniformity of concentration as the time step increased; this was due to parameters build-up with time in the soil. Conclusion: Finite element results revealed a high build-up in the concentration of pollutants (Zinc and Lead) in the land discharged slaughterhouses.

Research Status and Development Trend of Magnetic Fluid Acceleration Sensors

As a new type of accelerometer, in recent years, the magnetic liquid acceleration sensor has attracted widespread attention worldwide, and related research results have also continued to emerge. This article mainly introduces the theoretical basis and general structure of the magnetic liquid acceleration sensor, and according to the difference of inertial mass, briefly describes the research progress of the magnetic liquid acceleration sensor by national and foreign scholars in recent years and some in existing problems. Finally, suggestions and prospects for the future development trend of the magnetic liquid acceleration sensor are given.

Structural Behavior of Ferrocement Concrete Plates Subjected to Flexural and Dynamic Loadings

Ferrocement is one of the structural materials, widely used due to its advantages from its particular behavior such as mechanical properties, and impact strength. This paper deals with the impact studies and energy absorption properties of ferrocement slabs. For these studies, 11 different ferrocement slabs of size 50 mm X 500 mm X 25 mm were cast with alteration in the combinations of mesh layers and test results are analyzed to find the different crack patterns .The test specimens were loaded by 3.10 kg under its height 1.20 m in the center of plates. The ferrocement plates were divided into 4 groups reinforced with steel mesh, steel mesh with steel bars, percentage of rubber and fiber. The impact energy at initial cracking stage and at failure was determined for all the slabs. Results of reinforced ferrocement plates emphasized that increasing the number of the steel mesh layers in the ferrocement forms increases the first cracking load, ultimate load and energy absorption. Using steel bars with steel meshes led to higher energy absorption than that obtained when using mild steel bars only. Using rubber and fiber achieved high impact energy.

Real-time Optimization and Implementation of Multi-rate Digital FIR Kernel Filter

One ideal performance of this design is in the areas of decimation where a decimation factor of 10, 45-order and pass band ripple of 1dB and interpolation of sampled rates where a sinusoidal signal input produced a ripple free output with interpolation factor of 10, 52-order and stopband attenuation of 60dB. Owing to the multiple samples of filter length of 200, the filter performed down sampling preceded with filtering as well as up sampling preceded with filtering, hence multi-rate filter by allowing a low threshold of frequency of to be passed, blocking a high threshold of and vice versa. There was resampled output increased to 150% preceded by filtering. The filter coefficients for low pass and high pass Digital FIR filter, through the least square regression method, parks McClellan Algorithm and window methods were employed for easy optimization. More so, there was creation of 2-4-5 filter channel banks through the 2nd-level convolution of their down sampling and up sampling filtering techniques during the multi-irate filtering to ensure the design of error-free Digital FIR Filter using MATLAB File editor(M-File) and tool boxes for writing the C-programming of the design. In the analysis, the mean and standard deviation of the low pass Digital FIR Filter output during decimation and interpolation are (0.26, 6.13) and (0.004,1.22) respectively.

Effect of Calcination on the Chemical and Microstructural Properties of Sugarcane Bagasse Ash (SCBA)

This research study is for the evaluation of the effect of the burning temperature on the chemical and microstructural properties of Sugarcane Bagasse Ash. The Sugarcane Bagasse Ash (SCBA) is a byproduct of sugarcane which is dumped without proper handling and causing environmental issues because of the burning on dump site and loss of the area due to dumping in the commodity. The current research study is conducted for burning of SCBA on different temperatures and duration for finding the optimum burning temperature and duration of burning. The chemical and microstructural properties of SCBA evaluated at burning temperatures of 800°C for the duration of 01 hour, at temperature of 600° for the duration of 03 and 06 hours by conducting the tests of FTIR, XRD and XRF on the samples. The test results show that the burning temperatures of 800°C for the duration of 1 hour contains amorphous silica and also fulfilling the requirement of pozzolanic material (Composition of Silica, alumina and iron oxide is greater than 70%) as compared to other ash samples of sugarcane bagasse.

Surface Roughness Characterization for Stress Concentration Factor Predictions: A Bayesian Learning Approach

The surface roughness has an important influence on the fatigue life of the structures. The fatigue life reduces due to the stress concentration caused by surface roughness. The stress concentration governs the fatigue crack initiation and propagation. The accurate acquisition of the stress concentration factor of rough surfaces is a key issue in determining fatigue life. Nevertheless, semi-empirical models may be biased for various machining processes. Besides, finite element method simulations cannot give explicit expression of the stress concentration factor. Bayesian learning can construct accurate prediction models which offering a number of additional advantages. In this paper, based on several data pairs constructed by finite element method, the correlation expression between the stress concentration factor and statistical roughness parameters of surfaces is established quickly through Bayesian learning. Compared with some other semi-empirical models, the accuracy and stability of the proposed method are certified. This paper provides a simple and effi-cient approach to determine the stress concentration factor for rough surfaces under different processing conditions.