The global economy continues its journey of evolution and progression driven by industrialism as its primary force. With such a fast pace of development and recovery from several recessions over a number of years, dependency on energy sources became inevitable to satisfy the rising demand. This paper represents a proposed global energy price model that has the flexibility of modeling the energy price, using data from specific regions of the world, as well as the global energy pricing equation. The ANM (Alternate Novel Model) is presented here.
The model focuses mainly on oil price modeling, since oil accounts for more than 84% of the current world energy supply. The model duration is 50 years; starting from 1980 to 2030, model matching period from 1980 to 2011, and the prediction period is from 2012to 2030.
The modeling approach used in ANM adopts weighted averaging of individual factors and it relies on line regression technique. Therefore, future trends are being predicted based on the cyclic nature of the market and historical data "the future is reflection of the past??. ANM can then preduct the future oil prices, depending on the factors and variables that have been placed in the process for the output results.
The paper aims to propose a reliable model that accounts for most governing factors in the global energy pricing equation. All steps followed and assumptions made will be discussed in detailto clarify the working mechanism for this model and pave the road for any future modifications.
Guest editorial - No abstract available.
Poor supply chain management can set the conditions for failures of catastrophic proportions, both economically and in terms of safety. It has been the root cause of several of the largest disasters in oil and gas history. Many professionals fail to recognize important gaps due to the complexity of the web of supply relationships and the number of critical interfaces that can be misaligned. Professionals from executive offices, HSE, procurement, logistics, operations, and risk management need to take four major steps to ensure a safe supply chain: 1) Establish governance & organization to ensure organizational accountability for governance and management of supply chain risk, by appointing a supply chain czar and engaging cross-functional stakeholders; 2) Adopt an internationally accepted top-level supply chain risk management framework and articulate first-level principles, including a policy on single sourcing; 3) Universally adopt formal "reinforcing?? metrics and measurement systems, including measurement of supply chain risk, Total Cost methodologies, and quantification of the cost of supplier non-compliance; and 4) Extend supply chain strategy and policies to suppliers by scanning for suppliers that excel in HSE, setting supplier expectations and targets, training suppliers, and establishing mechanisms to hold them accountable including periodic audits.
Classic View of Supply Chain Management
Supply chain management is often perceived as either a synonym for the logistics department, based on its origins 30 years ago, or as a process whose objective is to reduce operating cost and make sure supplies are available when they are needed. Either way its impact is often viewed as minor and incremental compared to much more visible activities in exploration, production, and mid and downstream operations, a perception that fails to acknowledge the significant and continuous evolution that the concept underwent since its origin 30 years ago.
Most typical supply chain challenges are economic, and come into play long after much more strategic decisions are made. Supply chain managers are responsible for avoiding cost overruns by paying suppliers the right amount - not too much, especially to sole source suppliers, and not too little, which could encourage suppliers to shift cost from one bucket to another and could jeopardize creativity and innovation. They must also make decisions that keep projects on schedule, and oil companies are even more concerned about schedule and availability than about price. In our survey (see Appendices A and B for the demographics and results of the survey, respectively), respondents cited the risk of unavailability (including schedule slippage, missed delivery deadlines, and regulatory delays) five times more frequently than price concerns.
This paper presents a new approach developed for high-level scoping analysis, forecasting and scheduling of CO2 EOR projects for multiple reservoirs and fields. The approach utilizes available reservoir simulation, analytical predictions and analog data on a full-field scale and approximates them with analytical functions. This allows for very fast forecasting of oil and CO2 production rates and determines the requirements for make-up CO2 under different potential development scenarios, including piloting phases. Built in MicrosoftTM Excel with VBA code and an advanced solver add-in, this scheduling tool enables the timely use of probabilistic Monte Carlo simulation for estimating the impact of uncertain input parameters on CO2 flood performance from multiple reservoirs. A numerical optimization algorithm searches for the best development schedule by optimizing the start-up times for a number of planned CO2 injection projects subject to allowable oil rate and CO2 supply constraints. Another optimization algorithm matches the estimated CO2 demand with supply from multiple natural and industrial sources and predicts the best time to commission CO2 capture facilities, thus maximizing CO2 utilization by EOR schemes rather than disposing it in depleted reservoirs or saline aquifers.
A major challenge faced by oil and gas production companies is the supply of a reliable, cost effective, low maintenance and renewable source of power supply to the remote wellheads especially in areas prone to vandalization. Strategies deployed to provide power supply at these remote locations range from the installation of diesel generator sets, solar panels, inverters and battery banks among others. These solutions have been found to require constant monitoring and fueling in the case of the diesel generators, been prone to vandalization as in the case of solar panels and batteries. The inline power supply system comprises of a turbine system installed in a branch pipe. The system is inserted on a flow line from the wellhead so that it utilizes the fluid flow to provide the required kinetic energy to turn the turbine which is direct coupled to a gear and a DC generator. The output of the generator is fed to an electronic board which comprises of a regulator and a DC/DC converter. The DC/DC converter is responsible for providing the required DC level for wellhead instruments and communication devices. The system comprises of two identical installations in branched pipes providing 100% redundancy. The main application for this technology is in the provision of safe and vandalization proof power supply to remote oil and gas production installations especially at the wellheads. No oil or gas preprocessing is required as the turbine requires only the kinetic energy in the fluid. The use of an active flow line also guarantees the system protection against vandalization. The 100% redundancy guarantees that the system has negligible impact on the production process once deployed. The system provides a safe and cost effective safe power supply system for wellhead locations and reduces the OPEX required to keep the production facility powered
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Long-term economic viability of unconventional reservoirs is evaluated from the profit-maximizing perspective of a producing company. The case of the liquids-rich production from the Bakken field is considered as a representative of unconventional resources. A profit-margin optimization model is constructed for a company to meet the demand it faces from a stock of conventional and unconventional resources given different sets of exogenously determined prices. The model is parameterized using the different production decline rates of the two sources, physical and economic exhaustibility of the resources, and the ever increasing marginal cost of adding conventional resources into the company portfolio. The optimal extraction path of oil from the conventional and unconventional reservoirs is assessed, and the long-term economic consequence of keeping the unconventional resource in the ground for different oil-price scenarios is predicted. The model reveals the appropriate composition of a portfolio of conventional and unconventional resources. In the case of a high-price scenario, the optimal efficient extraction path is the pursuit of additional conventional resources before using unconventionals to meet the demand. For the reference-price scenario, the decline of the conventional reserves should be substituted with unconventionals from the beginning. The profitability of the enhanced oil recovery (EOR) applications in unconventional reservoirs and when they should be implemented are also determined. Contrary to common expectation, it is shown that the EOR technology is more justifiable in the case of a lower price forecast.
Since the early days of the petroleum industry, prediction of oil prices has been a real challenge. The puzzling question we need to answer when evaluating project's NCF is: how much is the price of a barrel during the life-span of the project? Accordingly, oil price modeling became a vital tool to predict both short- term and long-term prices. Unfortunately, there are many uncertainties associated with the available models and none of them can predict oil prices with acceptable accuracy. Only limited controlling parameters are captured by these models. These parameters are basic and derived from simple assumptions of supply and demand dependency. Nowadays, the need for a reliable oil price model became more critical as a change of oil price is experiencing dramatic fluctuations that affect economic decision parameters a great deal.
This paper presents an oil-price model to project the price behavior in the next 20 years. Different scenarios were examined out of which "Economic-Scenario?? was found to be the best suitable predictor. This model takes into account multiple effects of fourteen parameters that are believed to have the highest impacts on oil price. These factors have been further classified into key categories such as supply, demand, reserve and externalities (political/environmental/social) which is regionally based. Other parameters such as population growth and technology are embedded within these key factors. According to this model, oil price has been found to have strong reliance on the US Dollar and inflation, which has been incorporate into the model to ensure a more reliable outcome.
Market behavior modeling is a continuous process which is planned to be integrated into the proposed model in the near future once consistent data become available. The major obstacle in modeling market behavior is the lack of futuristic behavior that is primarily dependent on accurate historical data. This data should reflect the performance of short-term effects such as lifestyle, human behavior, politics, conflicts, wars, natural disasters, environmental issues and other economies' behaviors. The ultimate goal of this modeling effort is to assist in economic and risk analysis evaluation of petroleum projects.
Oil price prediction is one of the vital processes in every oil producing and operating company for current running projects and future new explorations, the whole different segments of industries and commodities would be also interested in knowing the future of oil prices, and we shall not ignore the interest that each country by itself shows to know the effect of future prices on their development plans. The oil price today is somehow far away from the control of any of the world powers, not under the control of the major consumers like the United States, Europe, Japan, Russia & China, nor the Super Majors like BP, Total, Exxon, Shell and Chevron, and not even OPEC majors like Saudi, Iraq, Iran, Kuwait and UAE for several reasons. The Consumers are not any more controlling the tap of oil as it was before the 1960's. While the Super majors are not any more having the major reserves as it was before the 1970's, while for OPEC the Excess Capacity of oil production that they have during 1970's, 80's, and 90's has diminished with maturing fields and failing to find new reserves. Therefore, the oil price control become mainly in the hand of supply and demand trends, hence the ability to capture the supply and demand trend model and anticipate the future of them, the oil price shall be known with reasonable confidence. Therefore, several attempts have been conducted throughout the years to estimate the oil prices as early as 1960's. In this paper, a new oil price projection modeling is built and called POMVSD (Price of Oil Modeling with Variables of Supply and Demand). A model reflects the new economic changes happening worldwide. The details of this model will be described in this paper in addition to a review and analysis of historical and modern literature that support this new model structure.
On the today's global market it is an important issue to have an adapted management system, due to the fast change of beliefs in social communities and politics. In the last few years a significant change in E&P business could be recognized from conventional sources to unconventional ones. With this extensive change the degree of resistance and possible problems for E&P companies increase, especially in Europe.
To realize an unconventional project in Europe, like shale gas, it is very important to adjust the project management to the given situation. There is a lot of resistance and fear from the population in Europe against shale gas projects, which is somehow unfounded.
To maintain a high acceptance of the communities and governments, the emphasis lies on the adaption of this operation.
The projects have to be operated in a more sustainable way. Observation of economic and technical issues is important, but the management has to look further beyond. To account for the overall sustainability, two further levels have to be considered, especially in shale gas projects. Ecological and social aspects for unconventional projects have to be introduced and interconnected in a higher degree compared to conventional projects in the oil and gas industry.
This paper introduces a 3D matrix, where the three major points of sustainability are imbedded into a workflow chart of a shale gas project. The matrix should act as a sort of subsidiary to the management of a shale gas project in Europe.