Prediction of Oil Formation Volume Factor Using an Intelligent Tool: Artificial Neural Network

The Oil Formation Volume Factor parameter is a very important fluid property in reservoir engineering computations. Ideally, this property should be obtained from actual measurements. Quite often, this measurement is either not available, or very costly to obtain. In such cases, empirically derived correlations are used in the prediction of this property. This work focuses on the use of an intelligent tool known as an artificial neural network (ANN) to address the inaccuracy of empirical correlations used for predicting oil formation volume factor. The new intelligent model was developed  using 448 published data from the Middle East, Malaysia, Africa, North Sea, Mediterranean basin, Gulf of Persian fields and 160 data set collected from the Niger Delta Region of  Nigeria. The data set was randomly divided into three parts of which 60% was used for training, 20% for validation, and 20% for testing. Both quantitative and qualitative assessments were employed to evaluate the accuracy of the new intelligent model to the existing empirical correlations. The ANN intelligent model outperformed the existing empirical correlations by the statistical parameters used with a lowest rank of 0.6313 and better performance plot.Key words: Oil formation volume factor; Empirical correlation; Artificial neural network; Back propagation; Statistical analysi

Forecasting Oil Formation Volume Factor for API Gravity Ranges Using Artificial Neural Network

The Oil Formation Volume Factor (FVF) parameter is a very important fluid property in reservoir engineering computations. Ideally, this property should be obtained from actual measurements. Quite often, this measurement is either not available, or very costly to obtain. In such cases, empirically derived correlations are used in the prediction of this property. This work centers on building an artificial neural network (ANN) model to predict oil formation volume factor for the different API gravity ranges. The new models were developed using combination of 448 published data from the Middle East, Malaysia, Africa, North Sea, Mediterranean basin, Gulf of Persian fields and 1389 data set collected from the Niger Delta Region of Nigeria. The data have been divided into the following four different API gravity classes: heavy oils for API≤21, medium oils for 2135. The data set was randomly divided into three parts of which, 60% was used for training, 20% for validation, and 20% for testing for each particular API grade. Both quantitative and qualitative assessments were employed to evaluate the accuracy of the models to the existing empirical correlations. The ANN models outperformed the existing empirical correlations by the statistical parameters used with the best rank and better performance plots.Key words: Oil formation volume factor; Artificial neural network; Back propagation; Statistical analysis; API gravity range

Economics Analysis on the Development of Nigerian Offshore Marginal Fields Using Probabilistic Approach

Marginal Field Development in the prolific Niger Delta environment is of strategic importance to the Federal Government of Nigeria’s drive towards aggressive Reserve and Production Capacity enhancement. The objective of this study is to provide a perspective on portfolio diversification, investment and resource development on offshore marginal field in Nigeria. The economic analysis was carried out deterministically using economic indices like Net Present Value, Internal Rate of Return, Present Value Rate and others. Probabilistic model was also incorporated to assess the impact of the uncertainties in the input parameters using Monte Carlo simulation through the use of Crystal ball software. The key uncertainties were represented and their respective impacts on economic viability defined. The deterministic model results obtained from the studies were very impressive with Net Present Value of $526,749,924.84 at a discount value of 15% and Internal Rate of Return at 60%. Probabilistically, certainty of having a positive net present value (NPV) and good internal rate of return (IRR) values far above the hurdle rate for investment in Nigeria was obtained. The sensitivity analysis outlined oil price and tax rate as key sensitive parameters in maximizing profit. These clearly showed that the development of offshore marginal fields in Niger Delta of Nigeria is economically viable. Key words: Offshore marginal field; Probabilistic approach; Sensitivity analysis; Economic yardstic

Economic Analysis of Liquefied Natural Gas Floating Production Storage and Offloading Plant (LNG FPSO) Using Probabilistic Approach

The global yearning for clean and safe environment coupled with the need of monetizing stranded gas fields to meet the growing demand of Natural gas in the world today has called for understanding of the range of potential for commercial realization of Liquefied Natural Gas Floating Production Storage and Offloading Plant (LNG FPSO). This places a heavy burden on the economic evaluation process which will give the maximum insight into the basis for a decision to invest or not to invest in the LNG FPSO. An economic analysis of 5.2 million tonnes per annum (MTPA) LNG FPSO plant was undertaken. A Monte Carlo simulation method was adopted in this study through the use of Crystal Ball Software. The key uncertainties were represented and their respective impacts on economic viability defined. The deterministic model results obtained from the studies were very impressive with Net Present Value of $2.3 billion at a discount value of 15% and Internal Rate of Return at 32.68%. Probabilistically, 74.96% certainty of having a positive net present value (NPV) and good IRR values far above the hurdle rate for investment in Nigeria was obtained. These clearly showed that LNG FPSO is profitable. Certainty of payback period of not exceeding 5 years was obtained to be 55.89%.Key words: LNG FPSO; Offshore LNG liquefaction; Probabilistic approach; Sensitivity analysis; Economic yardstic

Performance of Equilibrium Zeolite in Water-Based Mud at Elevated Temperature Conditions

This study looks at the performance of nano equilibrium zeolite treated drilling fluids at high temperatures conditions, and their potential as alternatives for oil-based muds (OBM). Mud samples for this study were prepared and aged with the equilibrium zeolite nanoparticles concentrations of 0.0 g, 0.5 g, 1.0 g and 1.5 g. Tests were performed to determine the rheological, filtration control properties, the pH and consequently the thermal stability of the study mud samples over a temperature range of 120 °F to 360 °F. One sample without the equilibrium zeolite served as a control for the study. From the results obtained, all the nano samples had their rheological properties not exhibiting much significant variation with temperature, thus they were more thermally stable, with the optimum nanoparticle concentration being 1.5 g. It was also hypothesized that the nano equilibrium zeolite behaved as thinners, since they were able to reduce the shear stresses, yield points, plastic viscosities and gel strengths of the mud samples as temperature was varied incrementally. It was therefore concluded that the optimum concentration of aged equilibrium zeolite has the potential to act as a thermal stability additive for Water Based Mud systems (WBMs)

Design and implementation of an effective information system for Nigerian universites

The population explosion in Nigeria Universities even in the second generation Universities like the University of Port Harcourt has brought its own attendant problems in terms of handling student records and in the computation of results to accertain the true positions of students. Such records and computation of results are needed for the graduation of students. In view of these, there is the need to design and implement an effective information system for Nigerian Universities. In the development of this system various data object models were used such as the Data Access Object as well as the latest Microsoft technology for database management, the ActiveX Data Object. The implementation is done using Microsoft Visual Basic With the developed system, it is possible to add, delete, update or edit records in the database. Range searches as well as the use of wildcard character are supported by the system. Various reports are produced such as student progress score sheets, probation list, withdrawal list, as well as final graduation list. The system has been tested using student results in the department of Chemical Engineering, Faculty of Engineering, University of Port Harcourt. The computer resources required to use this system are: windows 98 and above, 16 MB RAM with a minimum hard disk space of 113.40 MB. Keywords: Information System; System Design; Nigerian UniversitiesJournal of Modeling, Design and Management of Engineering Systems, Vol. 3 (1) 2005: pp. 39-5

Thermal Stability of Bio-Polymers and their Blends

Studies from research have shown that one of the major problems associated with the use of polymers during polymer flooding is polymer degradation. Polymers lose their viscosity as well as their efficiency in the presence of high temperatures. Hence, the need for polymers that are environmentally friendly and can withstand high reservoir temperatures. Therefore, this study was necessary to address this challenge. Three commercial bio-polymers currently being used in the oil and gas industry were used in this study, they are Xanthan gum, Guar gum, and the Imported Locust bean gum (LBG). Also used in this study were, Gum Arabic and Nigerian Locust bean gum (LBG). The thermal stabilities of these polymers were investigated at different temperatures to determine their thermal resistances at high temperatures. Polymer blending was applied to study the impact of blending on the thermal stabilities of the different polymer blends formulated. Rheological analysis was carried out before and after subjecting the polymers and polymer blends using temperatures from 50oC to 150oC. The results showed that Guar gum, Imported LBG, and Nigerian LBG displayed improved resistances from 75oC to 90oC compared to Xanthan gum, which was thermally stable up to 70oC. Furthermore, the blends showed higher stable temperatures compared to that of polymers alone and also compared to the thermal stability of Xanthan gum. This study showed that the blends would perform better at high-temperature reservoir conditions