Liquefied Petroleum Gas (LPG) is one of the alternate sources of energy because of its availability and high heating value. As the interest in LPG production in Nigeria and other developing countries increases, it is imperative to study some of the flow assurance issues associated with LPG. Due to the presence of moisture in commercial LPG, hydrates can form during LPG production, transportation and storage. Hence, it is important to predict hydrate forming conditions of LPG and propose a prevention plan if the LPG production, transportation or storage system falls in the hydrate formation zone. This paper examines the mechanism of hydrate formation in LPG and how LPG hydrates can be inhibited using methanol and ethanol. The inhibitor effectiveness was evaluated by the degree of temperature depression effected by equal amounts of these inhibitors. It was discovered that Methanol performed better than Ethanol when 20wt% of methanol and 20wt% of ethanol respectively were used in inhibiting hydrates formed in LPG. The effect of dehydration on LPG hydrate formation was also examined by varying the water content of the LPG from 7wt% water to 2.5wt% water. This simple approach to hydrate inhibition will enable the Engineer reduce the risk of hydrate formation during LPG production, transportation and storage.

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In recent times, polymers and surfactants have been used to influence the kinetics of hydrate growth and coagulation. However, these Low Dosage Hydrate Inhibitors are limited in terms of water-cut and sub-cooling. This work considers using a blend of Thermodynamic Hydrate Inhibitor and Ionic Inhibitor for hydrate inhibition. A comparative study was carried out to evaluate the combined effect of Ionic and Thermodynamic Hydrate Inhibitors in preventing hydrate formation by combining their temperature depression using Hammerschdmidt and Østergaard equation. This work finds application in hydrate inhibition by reducing the dosage of inhibitors. This will be useful for deepwater reservoirs and flowlines having large subcooling temperature and (or) high water-cut. The Thermodynamic Hydrate Inhibitors used are Methanol, Monoethylene Glycol and Diethylene Glycol while the Ionic Inhibitors used are Calcium Chloride, Sodium Chloride and Potassium Chloride salts. It was observed that the dosage of Thermodynamic Hydrate Inhibitors reduced by over 14% when it was combined with Ionic Inhibitors. The best blend was the hybrid of Methanol and Sodium Chloride salt which saved about 34% of methanol. This simple approach to hydrate inhibition will enable the Engineer reduce the use of methanol or glycols based on the salinity of the formation water. The operator can also save a lot by using the hybrid instead of methanol or glycol alone.

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Gas hydrate deposition is one of the major Flow Assurance problems in petroleum production in the offshore environment. Therefore, is important to accurately predict hydrate formation conditions and avoid these conditions or propose a hydrate management plan. This study compares the effectiveness of Artificial Neural Network (ANN) for predicting hydrate formation temperature to the effectiveness of other hydrate temperature prediction correlations such as: Towler and Mokhtab correlation, Hammerschmidt correlation and Bahadori and Vuthalaru correlation. The ANN was trained using 459 hydrate formation experimental data points from Katz chart and Wilcox et al chart. Pressure (P) and specific gravity (ϒ) were chosen as the inputs in the 4-layer network while temperature was the output. The data points were for gases of specific gravity of 0.5539, 0.6, 0.7, 0.8, 0.9 and 1.0. The experimental pressures considered were from 49 psia to 4000 psia. The Neural Network was built using an excel add-in tool, NEUROXL. ANN accurately predicted the experimental hydrate formation temperature with the regression coefficient greater than 0.98 for the different specific gravities considered. Moreso, the error analysis shows ANN performed better than Towler and Mokhtab correlation, Hammerschmidt correlation and Bahadori and Vuthalaru correlation because it had the least Mean Absolute percentage error, MAPE (3.5) compared to the other correlations. ANN is a viable tool for hydrate prediction and the current model can be improved upon by including more experimental data in the ANN.

Learning is effective when the learner can comprehend the principles taught and apply the knowledge to solve real-world problems. The terms online learning and blended learning became famous in 2020 due to the pandemic, which brought much innovation to the educational industry. Some of these innovative teaching techniques have tremendous benefits and should be sustained. This study discusses some innovative teaching techniques used in actively engaging engineering students at the University of Port Harcourt, particularly students of petroleum production engineering after the university was reopened from lockdown caused by the pandemic. The various feedback mechanisms employed to obtain students' feedback and ensure effective learning were also discussed. Some educational technologies applied include: google suite for education, zoom, google meet, Kahoot, poll EV and other applications that enhance learning in online teaching. The concerns of poor internet access were alleviated by sharing recorded live classes to ensure class inclusivity. This paper suggests viable options for implementing blended learning in teaching technical courses in developing countries with limited access to the internet and electricity.

As the world increases its natural gas development and exploitation projects, Gas hydrate will constitute a major flow assurance concern in most gas facilities. It is imperative to critically examine the various means of hydrate formation and effective ways of managing gas hydrates. This work considers gas hydrate formation due to gas expansion. It was discovered that hydrate formation may occur at the Joule Thompson's valve due to cooling during gas expansion. Hydrate prevention was effected by determining the critical point at which the expanded gas moves from the hydrate free zone to the hydrate risk zone. A comparative study was carried out to evaluate the effectiveness of methanol (MeOH) and monoethylene glycol (MEG) in hydrate inhibition during gas expansion. Hydrate formation curve and inhibitor performance curves were generated using CSMGem Software. MeOH performed better than MEG as 10wt% MeOH could prevent hydrate formation when the gas was expanded to about 3338 psia whereas, 10wt% of MEG could not prevent hydrate formation when gas was expanded beyond 3750 psia. This work will aid the engineer to assess problem areas upfront and to determine mitigating measures.

Gas hydrates have repeatedly plagued the oil and gas industry by impeding flow and causing catastrophic damages to subsea pipelines and equipment. Several software as well as equipment have been developed to reduce hydrate plugs in the field. In this study, steady state simulation and dynamic state simulation on a laboratory hydrate loop was carried out using Aspen Hysys. During the simulation, two mixers (Mixer 1 and Mixer 2) were selected to create the inhibitor water stream and the mixed feed stream respectively in the Process Flow Diagram (PFD). A pump was then selected to boost the pressure in the simulation to 150 psia and to agitate the fluid. Heat exchanger was selected to reduce the temperature to hydrate formation temperature, mimicking the action of the 4" PVC water bath in which the loop is immersed in the experimental set up. In the dynamic simulation, valves were included in the feed stream of the PFD created for the steady state simulation. The feed stream used in the simulation study contained 85% methane and 2wt% methanol as inhibitor. The steady state simulation did not record hydrate formation implying that the 2wt% Methanol used as inhibitor was sufficient to prevent hydrate formation in the loop. However, the dynamic state simulation which was set to run for 2 hours just as the experimental setup recorded hydrate formation at a temperature of 4.26 °C and a pressure of 83.84 psi. This can also imply that during shut in process, hydrate formation may not occur as the line may only attain hydrate formation temperature. However, during restart prrocess which is like the dynamkic simulation, a lot of aggitation takes place and hydrate formation will be noticed. Therefore, the engineer must proceed to dynamic state simulation before concluding on the effectiveness of a particular dosage of inhibitor prior to field application.