Spatiotemporal Morphodynamics of the Nigerian Coastline

Integrated Remote Sensing (RS) and Geographic Information System (GIS) Technology was used to predict and model the morphodynamics of the Nigerian Coastline in order to highlight mor-phodynamic active areas of threat to Oil/Gas infrastructure within coastal zone. Satellite imagery for 1987, 2002, 2015 and 2016 of the Nigerian coastline were acquired and analyzed using ArcGIS 10.5.0 software, Digital Shoreline Analysis System (DSAS v4.4) and Malthusian exponential equation Results of the satellite imagery revealed average values of end point rate (EPR) 4.17m/year and least median square (LMS) 3.54m/year for 1987 to 2016. Shoreline Area Change (SAC) was developed to aid visualization of the digitized coastline as against the poor visualiza-tion using ArcGIS software. The rates of change shows that accretion is higher than erosion and erosion is higher than accretion for some of the periods

Impact Of Artificial Intelligence And Big Data On The Oil And Gas Industry In Nigeria

This paper examines the concept of Artificial intelligence and Big Data as a field of study and its Impact on the oil and gas industry. Artificial Intelligence refers to the concept having of Computer systems that can perform tasks that would typically require human intelligence. Some such tasks are visual perception, speech recognition, decision-making and translation between languages, amongst others. “Big data” or Big Data analytics is a term often used to describe a huge or somewhat overwhelming data size that exceeds the capacity of both humans and the traditional software to process within an acceptable time and value. There is a big interface between the two concepts. AI does not stand alone; it requires big data for efficiency. AI and Big Data have brought about great impact across different industries and organizations. In the oil and gas industry, there have been an increasing installation of data recording sensors, hence data acquisition in exploration, drilling and production aspects of the industry. The industry is gradually making use of this huge data set by processing them using AI enabled tools and software to arrive at smart decisions that bring efficiency to operations in the industry. Some of such areas are analysis of seismic and micro-seismic data, improvement in reservoir characterization and simulation, reduction in drilling time and increasing drilling safety, optimization of pump performance, amongst others. Some of the solutions listed above have been successfully implemented in Nigeria, mostly by the international oil companies and some additional areas have also been impacted: managing asset integrity, tubular tally for drilling operations using RFID and the licensing and permit system by DPR. The industry has fully embraced the AI and Big Data concept, the future is very bright for more innovative solutions. However, there are still a few challenges especially in Nigeria. Some of these challenges include lack of local skilled manpower, poor data culture, security challenges in the industry’s operating areas, limited availability of good quality data, and understanding the complexity of the concept

Modelling of Sub-Sea Gas Transmission Pipeline to Predict Insulation Failure

Background: Thermally insulated subsea production and transmission systems are becoming more common in deep-water/ offshore operations. Premature failures of the insulation materials for these gas transmission pipelines have had significant operational impacts. The ability to timely detect these failures within these systems has been a very difficult task for the oil and gas industries. Thus, periodic survey of the subsea transmission systems is the present practice. In addition, a new technology called optic-fibre Distributed Temperature Sensing system (DTS) is now being used to monitor subsea transmission pipeline temperatures; but this technology is rather very expensive. Objective: However, this study proposed a model which will not only predict premature insulation failure in these transmission pipelines; but will also predict the section of the transmission line where the failure had occurred. Methods: From this study, we deduced that in gas pipeline flow, exit temperature for the system increases exponentially with the distance of insulation failure and approaches the normal operation if the failure occurs towards the exit of the gas pipe. This model can also be used to check the readings of an optic-fibre distributed temperature sensors. Result and Conclusion: After developing this model using classical visual basic and excel package, the model was validated by cross plotting the normal temperature profiles of the model and field data; and R-factor of 0.967 was obtained. Analysis of the results obtained from the model showed that insulation failure in subsea gas transmission pipeline can be predicted on a real-time basis by mere reading of the arrival temperature of a gas transmission line

Development and Testing of Sorption Isotherm Equipment for Nigerian Coal

Aim: The aim of the study is to investigate the methane content in Nigerian coal. Study Design: Fabrication of Sorption Isotherm Equipment and Experimental Analysis. Place and Duration of Study: Department of Petroleum and Gas Engineering, University of Port Harcourt Rivers State, between June, 2014 and January, 2015. Methodology: This study includes the Fabrication of Isotherm Adsorption Equipment, Methane Sorption test, Proximate Analysis, Ultimate Analysis, and Estimation of Methane Content. Results: The maximum moisture and fixed carbon was found in Sample D with moisture content of 3.35%, fixed carbon content of 60.41%; and it also has the minimum ash content of 5.61%. The maximum volatile matter was found in Sample B with volatile matter of 33.57%. The estimated methane content from the Meissner’s method differs from those obtained from the adsorption Isotherm equipment by 22%. Conclusion: The adsorption isotherm models obtained, showed that the total organic carbon content is not a significant factor in the adsorptive and dispersive behaviors exhibited by the shale

A MODEL TO OPTIMIZE A CRYOGENIC SEPARATION SYSTEM WITH INNOVATIVE HYBRID DISTILLATION MEMBRANE IN SERIES

The study developed a model for hybrid distillation membrane that optimized the energy usage in binary cryogenic separation. In separating air mixture components, distillation columns are often used and these columns consumes very large energy during operation. From analysis, the exergy efficiency and heat transfer of a cryogenic air separation double diabatic column in the distillation process is greater than that of the conventional adiabatic double columns. There is need to discover alternative separation technologies with lesser energy consumption such as membrane separation. However, use of membrane separation alone is constrained to small separation due to large areas needed with the attendant costs. Thus, a hybrid system comprising of distillation column and membrane separator offers the best compromise. To optimize the process, the overhead product from the distillation column was fed to a membrane separator in series in this study. A mathematical Model approach was proposed to improve a hybrid separation system comprising of a distillation column and a Serial novel membrane separation unit. First, a model was introduced that validated if the hybrid system could optimize the process and the order of magnitude of energy that can be expected. Secondly, a superstructure optimization approach was applied and it uses rigorous models for both the column and the membrane. A process simulator, excel and visual basic were used to solve and program the equations. The result showed that significant energy savings was achieved using a novel hybrid separation system with a material membrane

GAS PROCESS SYSTEM EMPIRICAL TOOL FOR PREDICTING HYDRATE FORMATION

The rapid formation of gas hydrates, promoted by typical high pressure/ low temperature operating conditions in deep water installations, is considered one of the most difficult problems with flow assurance. Understanding the conditions for the formation of hydrates is necessary to overcome the problems associated with hydrates. Ideally, the conditions for the formation of gas hydrates are determined experimentally in the laboratory; but this data is not always available. Therefore, correlation is used to determine the conditions for gas hydrate formation. Several models have been proposed that require more complex and longer computations to predict the conditions for the formation of gas hydrate over the years. In this study, it is crucial to develop a reliable and easy-touse method for oil and gas practitioners’. The proposed correlation extends over a wide range of pressure (2000 to 25000kPa) and molecular weights (16 to 27). Consistent and accurate results of the proposed pressure range, temperature, and molecular weight are presented. Statistical error analysis is used to appraise the efficiency and accuracy of the correlation coefficient for estimating the formation of gas hydrate. This will guide designer and operator to select the optimal correlation for a particular application

Optimizing aqueous drilling mud system viscosity with green additives

Non-governmental and governmental agencies are demanding for environmentally friendly mud systems. This increase in environmental awareness has made the drilling mud service companies to re-evaluate some of the chemicals and materials used as additives for mud systems. In this study, some green materials were considered as possible substitutes for PAC R in water-based drilling fluid systems. The rheological properties of four water-based mud systems with typical compositions were studied at 80 and 150 °F. These two temperature ranges were necessary so as to evaluate the effect of temperature on the viscosity, plastic viscosity and yield point properties of these mud systems formulated with these green materials as viscosifier. These green materials were processed to powder form and sieved to their finest particle sizes to reduce amount of solute that will be present in the water-based drilling fluid formed with the materials. The properties of the formulated mud systems were analyzed using API standard. These green materials behaved optimally as viscosifiers for the formulated water-based mud systems under ambient temperature. Also the mud systems behaviour at 150 °F showed a reduction in the flow properties at this high temperature as recorded in the literatures. From the results of the experiment, we can say that Kian (Averrhoa carambola L.) has the characteristic of being a substitute for PAC R when beneficiated for water-based drilling fluids

Estimation of Flow Capacity in Pipelines Based on the Intrinsic Variation of the Volumetric Properties of the Natural Gas Mixture

In this paper, the Weymouth equation was applied so as to consider the pipeline characteristics, thermodynamic and physical gas properties. From literature, volumetric parameters like the specific gravity and compressibility are mostly assumed to be constants. Since they are related to flow, pressure and temperature values; neglecting their variation during pipeline transportation may lead to significant misleading results in the computation of pipeline resistance. Considering that providing global optimal solutions to instances of considerable size can become time-consuming, thus a mathematical optimization method was applied to find the solution that will satisfy these systems. Critical property correlations (Thomas, Standing and Sulton) and Compressibility correlations (Hall-Yarborough, Danchuk-Purvis Robinson are used mathematically to generate results that will optimize the gas pipeline transportation without assuming specific gravity and compressibility factor of the gas constant. The model proposed in this study showed that specific gravity and compressibility have an effect on gas pipeline flow rate. It was observed that at very low and very high specific gravity, that the gas flow rate is reduced by more than 10% while the gas density increases. It can also be stated from the results that, compressibility is directly proportional to flow rate and inversely proportional to density

Reserve Estimation Using Decline Curve Analysis for Boundary-Dominated Flow Dry Gas Wells

Diverse techniques have been developed to improve the estimated reserves for boundary-dominated flow dry gas wells. The various methods developed and published in various journals on how to estimate reserves range from material balance techniques to decline curve analysis. Among the various techniques, decline curves are found quite accurate in predicting good gas performance in the absence of well-known reservoir parameters. There are basically two issues that practically arise in applying decline curve analysis, particularly in boundary-dominated flow dry gas wells. First, it has been noted that it is difficult to match a decline exponent, especially at an early stage of well depletion, even with worthy quality data. Secondly, decline exponent is not constant from observation, but changes with declining production. So, the study has provided a new method based on numerical curve fitting to accurately match the Arps’ decline curve function, even at the early depletion stage, and account for the changing decline exponent. Once the match objective is satisfied, future predictions can be made with a reasonable degree of assurance. Finally, the study showed that for the Arps’ decline equation to be valid, the decline exponent must be between 0 and 1

Data on shale-water based drilling fluid interaction for drilling operation

The shale dispersion test (rolling test) is a common procedure that is used to measure the interactions between drilling fluids and shales. The shale rolling test depends on the moisture content of the shale, the shale composition, the viscosity of the test fluid, the rotation speed of the rollers, and the test temperature. The rheological behavior of the test fluid has the strongest influence on test results. The data was generated experimentally, shale samples from Agbada formation Niger-Delta was used. These shale samples were cored at a depth of 2000ft and 3400ft. Water based mud that will minimize shaledispersionandswellingofshalewasformulated.Thedispersion test was conducted, and it involves exposing a weighted quantity of sized shale to the formulated mud in roller-oven. This test is used to design fluids and screen the effectiveness of inhibitor additives to maintain the integrityof the cuttings and minimize the interaction of fluids with the shale sections during the drilling and completion operations.Theswellingtest wasconductedandthe linearexpansion adopted because it is the most representative of the increase seen by the wellbore but was measured in the direction perpendicular to the bedding plane as this is the direction of swelling into the wellbore