Nigerian Gas Transmission Tariff Framework Study

Pipe-in-Pipe technology is a pipeline system consisting of two coaxial pipes. The inner pipe carries the fluid and is encased within a larger diameter outer pipe which seals the annulus between the two pipes. The annulus can be filled with a wide range of thermal insulating materials such as fiberglass, glasswool, microporous materials, aerogel, polyurethane foam, ceramics etc. This is seen as a solution to the effective management of the long problem of flow assurance in subsea fields. The pipe-in-pipe technology is thought to be extensively ideal for the transportation of well bore fluids from a subsea field, as it is capable of withstanding the difficult conditions of the ocean with its low overall heat transfer coefficient (OHTC) of less than 1 W/m2K, but this it does achieve at added cost. The aim of this paper is to economically analyze the pipe-in-pipe technology using a case study of Rosa field, an offshore field off the coast of Angola relative to offshore Gas Development in Nigeria. The following profitability indices; Net present value (NPV), internal rate of return (IRR), Profitability index and Payout or payback period were used to compare the cost of a pipe-in-pipe technology and that of a conventional pipeline system for an oil and gas field. For the pipe-in-pipe technology, a real NPV of $5.5 billion, IRR of 65.7%, PI of 3.22and payback period of 1.46 years and a money of the day NPV of $10 billion, IRR of 82.1%, PI of 5.0 and payback period of 1.19 years were achieved while for a conventional pipeline, a real NPV of $5.6 billion, IRR of 66.5%, PI of 3.28 and payback period of 1.49 years and money of the day NPV of $10.1 billion, IRR of 83%, PI of 5.1 and payback period of 1.16 years were achieved.

Alliance Pipeline operates an integrated Canadian and U.S. high-pressure, rich natural gas transmission pipeline system. Rich natural gas pipelines are unique in that the product transported in these pipelines contains greater amounts of higher molecular weight hydrocarbons than would be transported in a dry natural gas pipeline. The specifications for gas quality however are very similar and require the product to contain less than sixty five mg/m3 water, no free liquids and/or objectionable materials such as bacteria, ashphaltene, gum, etc. The acid gases, carbon dioxide and hydrogen sulphide, are also required to be below certain values (see Table 1). Corrosion is not expected to occur under these conditions due to the lack of free water available for the development of an electrochemical corrosion cell. However, there are instances where the gas quality may vary and this gas enters facility piping for short periods of time. A method has been developed by Pipeline Research Council International (PRCI) to determine the internal corrosion susceptibility for dry gas natural gas pipelines but there are currently no industry accepted models which determine the internal corrosion susceptibility for high energy natural gas (HENG) pipeline systems. Accordingly, it is important for operators of pipelines with high energy natural gas (HENG) to collect and analyze these off specification events and develop a method to determine the relative impact on internal corrosion susceptibility. It is perhaps more important for operators to use this method to develop a strategy to prioritize facility piping for inspection and confirm the absence of internal corrosion. An Internal Corrosion Susceptibility Assessment (ICSA) method has been developed for HENG which considers off specification water, carbon dioxide, and hydrogen sulphide contents in the HENG. The analysis has been enhanced to also consider low temperature operation and hydrocarbon dew-point variations. The model has been effectively trialed over the last number of years to prioritize inspections and has been further tested against PRCI research and models developed for dry gas internal corrosion susceptibility. All internal corrosion models need to identify free water as prime contributor to susceptibility, thus the subject model is considered adaptable to other gas pipeline systems. This paper discusses the methods used to develop the model, the challenges encountered and results of the field inspections conducted.

Evaluating the economic sustainability of a vertical greening system: A Cost-Benefit Analysis of a pilot project in mediterranean area

Increased demand for natural gas in Venezuela has led to an intensified search for additional supply from mature oil fields in Eastern Venezuela. The search has involved the ranking of oil reservoirs that could be converted to gas producing reservoirs. Unreliable reservoir and historical production data introduced high uncertainties to the ranking based on gas reserves only. A fuzzy model was therefore constructed and used for ranking 45 reservoirs. Eight input variables were used to evaluate each of the reservoirs. The variables included remaining petroleum reserves, remaining gas reserves, gas cap volume, oil production per psi, gas production per psi, flow capacity, storage capacity and the distance to existing gas transmission lines. Membership functions were developed for each variable and 20 fuzzy rules were used to capture the non-linear relationship amongst the input and output variables. The output variable was represented by 5 membership functions and presented in a 0 - 1 range after defuzzification. The reservoirs were then ranked on the basis of their output range values. The results from the fuzzy model were compared to those obtained from a conventional methodology using a Decision Tree - Monte Carlo model. In this conventional model, the 8 input variables were normalized and represented as events in a decision tree. The variables were then weighted by using Monte Carlo simulation to generate the mean probability of each event occurring. A rolling netback calculation produced an output value for each reservoir. The output values were used to rank the 45 reservoirs. The paper concludes that although the two models handled the uncertainties of the impact of the 8 input variables on the output variable, the fuzzy model best capture the vagueness in the non-linear relationships between these variables. Introduction Venezuela has 147.5 TCF of gas reserves with 91% as associated gas and the remaining 9% as non-associated gas. In the Eastern part of the country, gas reserves are about 105 TCF with over 94% as associated gas. Gas demand is 1.92 BCF per day with a 7.5% annual growth rate. There is an on-going intensive search for gas to enhance the national gas supply. This search involved the conversion of mature oil reservoirs to gas producing reservoirs. Budget constraints limited the number of mature reservoirs that could be converted. Therefore, the reservoirs were ranked on the basis of Remaining Gas Reserves and the top ranked reservoirs were assumed to have the best gas opportunities. However, there was a high degree of uncertainty with the gas data. Furthermore, some of the reservoirs with large Remaining Gas Reserves had very low reservoir pressure and flow capacity. Others were located very far from any gas pipelines and surface infrastructure. There was therefore a need to use more sophisticated methods to rank the reservoirs. Conventional ranking techniques include the Net Present Value (NPV), the Internal Rate of Return (IRR), the Expected Monetary Value (EMV), Value of Information (VOI) and hydrocarbon volume such as the Remaining Gas Reserves. 1 Moore and Tucker 2 used NPV and the Economic Chance Factor to rank exploration opportunities. Zammerilli 3 used the EMV to rank horizontal well locations in tight, naturally fractured reservoirs. Variables such as reservoir pressure, net thickness, success ratio, well length, drainage area, azimuth, well radius and topography were fixed at the beginning of the project. Variables like gas price and drilling costs were allowed to vary. Kelkar 4 also used EMV to rank independent projects in the presence of uncertainties. Demirmen 5 used Decision Tree and the Value of Information (VOI) analyses for screening and ranking subsurface appraisal projects. VOI captures uncertainties arising from volumetric parameters and hydrocarbon quality parameters. Gottardi et al 6 gave a good summary of the new conventional tools for ranking R & D projects using multivariate analysis.

Historically LNG projects have been established to monetise large gas finds in remote areas with little existing gas demand. The development of gas supply to the LNG project generally stimulated demand growth in the domestic gas market. As the supplying fields depleted, the LNG projects faced competition with domestic producers for declining gas supplies, but this was late in the project life when LNG plant capital had already been recovered. Recently, LNG export projects have been established within existing mature gas markets, most notably in Australia and North America. These plants now face competition with domestic gas consumers for access to feed gas from the beginning of their operational life when strong revenue has the greatest impact on the return earned on capital invested, with the greatest stress felt in Australia. This paper considers the underlying causes of domestic price rises experienced in Australia following the start-up of LNG export supplied from gas fields linked to the domestic market and the response by both plant developers/operators and the government. This historical view is used to inform forecasts of how the east coast gas market will react to the interplay between domestic and LNG plant demand, declining Bass Strait production, maturing CSG operations, LNG imports and completion of the Northern Gas Pipeline. In particular the ability of gas supply and pipeline capacity to meet the strongly seasonal domestic demand in Victoria and to a lesser extent NSW will be examined, together with the linkage to counter-cyclical seasonal demand for LNG from the Queensland LNG export plants in the key north Asian markets.

Global LNG pricing outlook Liquidity in the global LNG spot market is increasing and the industry is seeking price diversification in its supply contracts. The rationale for oil linkage is being challenged. Short-term trade now accounts for a quarter of the total market, and the US’ Henry Hub, the UK’s NBP, and global LNG spot indices are all used in LNG price indexation. Growth in LNG supplies, short-term trade, and operational flexibility will drive global price connectivity and increase transparency. The US will begin exporting LNG, tightening the price differential between Atlantic and Pacific basins. The LNG industry will continue to question the validity of oil-price linkage as it seeks a reliable reference capable of reflecting supply and demand fundamentals in the gas markets themselves. It is, however, important to recognise that gas-to-gas pricing will not automatically deliver cheaper LNG than equivalent oil-index formulas. East coast Australia gas pricing outlook Dynamics in Australian east coast gas markets are changing rapidly, with LNG at the heart of this revolution. The east coast gas industry seeks a deeper, more liquid and transparent market, while looking to international gas hubs for lessons in boosting market efficiency. The industry must address challenges such as gas storage and pipeline capacity if it is to have the flexibility needed to build a vibrant market. Oil-indexed LNG netback pricing is starting to work its way into east coast gas supply contracts; however, as the European gas industry moves away from oil indexation, Australia’s domestic gas market needs to look at alternative pricing structures.

Aquaculture in Floating Net Cage (FNC) is one of the reliable aquaculture technologies that is used to optimize the utilization of waters on rivers, lakes and reservoirs. The types of fish that is usually preserved in Floating Net Cage are Gold Fish ( Cyprinus carpio ) and Nile Tilapia ( Oreochromis niloticus ). Survey method is applied in this research and data sample is drawn from the farmer population of floating net cages in Kecamatan Pinoh Utara. The objective of this study is to determine the financial feasibility of aquaculture with Floating Net Cage (FNC) system. This achieved by considering Net Present Value (NPV), IRR (Internal Rate of Return), Net Benefit-Cost Ratio (B/C Ratio), Analysis of PP (Payback Periods) and Sensitivity Analysis. The result indicates that aquaculture of Nile Tilapia and Gold-Fish with Floating Net Cage (FNC) system was financially significant shown by Net Presents Value (NPV) 227.246.769,84 rupiahs, Internal Rate of Return (IRR) 190,97%, Net Benefit Cost ratio (B/C Ratio) 4,34 and Payback Periods (PP) 0,53 years (6 months 10 days). The sensitivity analysis indicates that if there was an increase in operational costs, the amount should not be more than 304,19% and if there was a decrease in profits, the amount should not be more than 44,11%. Keywords: Financial Analysis, Aquaculture, Floating Net Cage, Net Present Value (NPV), Internal Rate of Return (IRR), Net Benefit-Cost Ratio (B/C Ratio).

Techno-economic evaluation of small hydro power plants in Greece: a complete sensitivity analysis

During the long-term operation of oil and gas pipeline network, it is often affected by construction quality, external environment corrosion, natural disasters, third-party construction and other factors, which can easily cause leakage, even explosion, fire and other safety accidents, endanger casualties and economic losses, and also bring certain impact on the surrounding environment. Modern UAVs have the ability of high altitude, long distance, fast and self-operation. They can quickly patrol oil and gas transmission lines through mountains and rivers. They can take full-spectrum fast camera and fault monitoring for oil and gas leakage, environmental pollution and material damage of pipelines. Based on the professional analysis of UAV data acquisition, it provides technical support for the management and maintenance of oil and gas pipeline network. This paper discusses the design of the information operation and maintenance system of high availability and long distance oil and gas pipelines with the characteristics of safety, reliability and economy from the aspects of technical principle, system composition and system function, and focuses on the introduction of the information operation and maintenance data of oil and gas pipelines. Long distance oil and gas pipeline information operational system application aviation remote sensing[1], geographic information technology, data transmission, information processing and large data, for the transport of oil and gas industry to provide aerial vehicle (UAV) + + Internet data center of integration solutions, selection of unmanned aerial vehicle (UAV) platform with visible light, infrared detection, such as load as a means of oil and gas pipeline inspection, supported by UAV measurement and control system based on Internet, to develop more types of unmanned aerial vehicle (UAV) daily and emergency patrol, access to oil and gas pipeline monitoring data, based on a high-precision geographic information platform to carry out the integration analysis, forming oil and gas pipeline operation situation and the underlying database, Provide information handling and command decision data support to relevant business personnel.

Summary Discounted cash flow methods for evaluating investment opportunities enjoy wide use in the petroleum industry. The two most popular measures are net present value and internal rate of return. While these two measures are generally suitable as accept/reject criteria, they are not so useful in capital rationing situations, where a ranking of projects is required. Decades ago authorities suggested that the net present value divided by the initial outlay is a better measure for ranking projects. This kind of measure becomes more difficult to apply correctly when ail the capital costs in a project are not incurred up front, but are spread over a number of years. It is common practice to discount these future capital outlays back to the present and include them in investment (the divisor in the index). Simple examples demonstrate, however, that some obviously erroneous rankings can result from this procedure. By using an alternative definition of project investment, based only on the project net cash flows and the discount rate, we can avoid these pitfalls and obtain a better profitability measure for ranking projects.

Accepting as a basic premise the importance of capital investment decisions for the firm and the significance of risk and uncertainty in forward planning, the research study reviews investment decision theory and examines alternative modifications to this theory to accommodate risk and uncertainty. Recommended modifications to data input, methods of project evaluation, and reporting produce a programme which varies significantly from generally accepted investment theory and practice. Risk and uncertainty is explicitly recognised through their influence on input variables: investment outlays, lifespans, volume of project outputs, selling prices and variable costs per unit of volume, period fixed costs, reinvestment opportunities and residual benefits. In the programme, a range of values (with subjective probabilities for each value) is determined for each input variable. Uncertainty is converted to a risk-equivalent situation. Input data is analysed initially using a Monte Carlo technique to simulate profitability and each range of data is further reduced to an expected value to form the basis for profitability calculations and an evaluation of investment sensitivity to changes in input variables. In both the simulation and sensitivity analyses, four indexes are used to measure investment profitability - internal rate of return, internal rate of return modified to incorporate explicit reinvestment opportunities, accounting rate of return, and the payback calculation. In reporting the results of simulation and sensitivity analyses, extensive use is made of graphs. After illustrating the programme of analysis with a theoretical investment project, the programme is evaluated on the basis of eight case studies - investment projects currently under consideration by executives of Australian manufacturing companies. Experience with the case studies leads to the following conclusions:1) The significance of investment risk and uncertainty is identified for decision-makers if projects are evaluated with a programme incorporating simulation and sensitivity analyses.2) The investment analysis programme provides valuable information for management not currently available from methods in use by accounting executives of Australian manufacturing companies.3) Ranges of values for input variables are readily obtainable from accounting, production and sales executives. Little difficulty is found in assigning subjective probabilities to ranges of values.4) An internal rate of return analysis which explicitly considers reinvestment opportunities, and rule-of-thumb methods of analyses have an important role in identifying risk and uncertainty for investment decisions. When the results of analyses are presented as graphs, management interpretation of these analyses is assisted and subsequent decision-making is most effective.5) Widespread acceptance and implementation of the recommended investment analysis programme by members of the accounting profession must depend on current and future educational policies of professional bodies producing financial executives with a sound knowledge of computer mathematics, statistics and financial analysis.

Abstract: Whereas Spain used to have one of the most restrictive photovoltaic self-consumption (PVSC) regulations in the world, the new regulation (RD-L 15/2018 & RD 244/2019) improves the economic conditions of PVSC systems, simplifies administrative procedures and allows shared self-consumption. We analyze the impact of the new PVSC regulation on residential, commercial and industrial prosumers’ profitability (internal rate of return). We provide a wide range of results that allow us to explore future profitability depending on the evolution of installation costs, the opportunities of shared self-consumption or storage, and even the potential emergence of new business models. We find that all segments obtain now positive profitability in average conditions. Whereas the residential segment has the lowest profitability level, it has the highest potential by decreasing installation costs and increasing the share of self-consumption, given its higher retail prices. Finally, we identify potential new business models by exploiting the prices and costs differentials across segments and maximizing the share of self-consumed electricity. PVSC systems with industrial costs exploiting residential markets could achieve 35% profitability by reaching 75% self-consumption, and even higher than 40% when self-consumption exceeds 85%.

Oil and gas pipeline failure prediction system using long range ultrasonic transducers and Euclidean-Support Vector Machines classification approach

Optimization problems in natural gas transportation systems: A state-of-the-art review

Investment decisions for offshore wind-to-hydrogen (W2H) projects are often framed as “better forecasts reduce uncertainty,” but it is less clear when higher-fidelity scenario modelling meaningfully changes a financing decision versus merely narrowing outcome ranges. We address this question using a decision-coupled evaluation that scores forecast skill on propagated economic distributions and links it directly to financeability metrics.Using 61 years of ERA5 wind data at 150 m hub height, we generate 1000 synthetic 23-year hourly wind scenarios per method and propagate them through a techno-economic model of a 375 MW offshore W2H project (development in 2024, operation in 2026-2050, base hydrogen price €8/kg, discount rate 7%). We compare three probabilistic scenario generators: historical bootstrapping, parametric Weibull fitting, and a calibrated probabilistic long short-term memory (LSTM) sequence model (used as a benchmark rather than architectural novelty).We evaluate (a) continuous ranked probability score (CRPS) of levelized cost of hydrogen (LCOH), net present value (NPV), and internal rate of return (IRR), (b) decision bandwidths W(Y) = P95(Y) – P5(Y), (c) threshold-crossing probabilities Pr(NPV>0) and Pr(IRR>10%), and (d) a local elasticity E(Y) = dW(Y)/dCRPS that maps marginal forecast skill to risk-band compression. Finally, we run a financing price sweep to identify the minimum hydrogen offtake price that achieves a 90% probability target for NPV > 0 and the joint target NPV > 0, IRR > 10%.Results show that improved scenario modelling can substantially reduce economic distribution error and compress risk bands: the LSTM lowers CRPS by 30% for LCOH and NPV and by 25% for IRR versus the best bootstrap/Weibull configurations. However, under base assumptions the financeability thresholds are nearly invariant across methods: the 90%-target required hydrogen price is €7.76-7.78/kg for Pr(NPV>0) and €9.16-9.18/kg for Pr(NPV>0 and IRR>10%), with cross-method spread below €0.02/kg indicates a threshold-saturated regime where better modelling mainly narrows uncertainty rather than shifting the decision boundary. Sensitivity analysis indicates decision value is highest in moderate-margin regimes (roughly €5.5-8/kg) and diminishes at high profitability where models converge.This work reframes “better scenarios” into an investment-relevant diagnostic: use elasticity and threshold behaviour to identify when modelling improvements will shift financeability versus only compress risk bands, supporting more defensible screening and policy design.