Статті в журналах з теми "Oil; petroleum; real option valuation"

Abstract Paper discusses issues relating to the valuation of investment efficiency in the oil and gas industry using a real options theory. The example of investment pricing using real options was depicted and it was confronted with the analysis executed with the use of traditional methods. Indicators commonly used to evaluate profitability of investment projects, based on a discounted cash flow method, have a few significant drawbacks, the most meaningful of which is staticity which means that any changes resulting from a decision process during the time of investment cannot be taken into consideration. In accordance with a methodology that is currently used, investment projects are analysed in a way that all the key decisions are made at the beginning and are irreversible. This approach assumes, that all the cash flows are specified and does not let the fact that during the time of investment there may appear new information, which could change its original form. What is also not analysed is the possibility of readjustment, due to staff managment’s decisions, to the current market conditions, by expanding, speeding up/slowing down, abandoning or changing an outline of the undertaking. In result, traditional methods of investment projects valuation may lead to taking wrong decisions, e.g. giving up an owned exploitation licence or untimely liquidation of boreholes, which seem to be unprofitable. Due to all the above-mentioned there appears the necessity of finding some other methods which would let one make real and adequate estimations about investments in a petroleum industry especially when it comes to unconventional resources extraction. One of the methods which has been recently getting more and more approval in a world petroleum economics, is a real options pricing method. A real option is a right (but not an obligation) to make a decision connected with an investment in a specified time or time interval. According to the method a static model of pricing using DCF is no longer used; an investment project is divided into a series of steps and after each one there is a range of possible investment decisions, technical and organizational issues and all the others called ‘real options’. This lets one take many different varieties of modyfiying a strategy while pricing the project. This also makes it possible to react to the changing inner and outer situation and introducing new information while accomplishing the investment project. Owing to those, the decision process is a continuous operation, what is an actual vision of a real investment project management in the petroleum industry.

The most widely used methods of choosing investments are undoubtedly the NPV. This method is often criticized because it does not allow to take into account certain main characteristics of the investment decision, notably the irreversibility, the uncertainty and the possibility of delaying the investment. On the other hand, the real options approach (ROA) is proposed to capture the flexibility associated with an investment project. This article examines whether the value of an undeveloped oil field varies according to whether the ROA or NPV assessment is used. In addition, to value the option to defer, we developed a continuous time model derived from previous work by Brenan and Schwartz (1985), McDonald and Siegel (1986) and Paddock, Siegel, and Smith (1988). The originality of the proposed model gives rise to a simple and uncomplicated method for determining the value of the option. Findings indicate that the two evaluation methods lead to the same decision, the project is economically profitable. In this oil investment project studied, despite the positive value of the option, the importance of projected cash-flows and optimistic forecasts of the price of oil, led us not to exercise the option and to undertake the project immediately.

In this work modern methods of investment project efficiency evaluation were studied, advantages and disadvantages of using the real option model were shown in comparison with the DCF model. It is proved that a rainbow option is an effective valuation tool in conditions of high oil prices volatility and low study of reserves and resource. Two stages may be identified: mineral exploration and maintenance work. Black-Scholes model was used for option pricing.

Oil and gas resources present enormous opportunities for the economic development of low income economies, but poor management of these resources can result in dire consequences for the foundations of the resource-endowed nation. The discovery of oil and gas in Ghana is as significant as the policies and measures to ensure optimum benefits to the nation. This paper evaluates the sustainability of petroleum production in the light of the medium term policy structure, the Ghana Shared Growth and Development Agenda (GSGDA). In particular, the economic contribution of oil and gas to Ghana’s GDP and sustainable investment options for petroleum revenues were examined using ordinary least squares (OLS) regression. The evidence suggests that at current production levels, petroleum is not a significant contributor to Ghana’s GDP after adjusting for the contribution from other sectors of the economy. The consistent appreciation of Ghana’s real effective exchange rate between 2010 and 2013 led to a deterioration of the competitiveness of the non-oil sector and declining contribution of the agricultural sector to GDP; and further eroded the net impact of petroleum production. Investing petroleum proceeds in the non-oil sector and expansion of the export base are a viable option for utilising petroleum revenues.

Wandering of oil prices at lower values and the bitter reality have forced people to look for a more accurate valuation method for overseas oil and gas extraction of China. However, the currently available resource classification method, discount cash flow (DCF) method, and real option method all suffer from their own disadvantages. This paper identifies multiple uncertainty factors such as oil prices and reserves. It then investigates the transmission mechanism of how each uncertainty factor impacts the oil and gas extraction value and quantifies the transmission efficiency. The probability distribution patterns of each uncertainty factor have been determined; the trinomial tree option pricing model is modified, with consideration upon the nonstandardness of the probability distribution. Decision points and strategies space are designed in accordance with the practical oil and gas production; and the Bermuda option is adopted to replace the conventional decision-based tree model with the probability-based tree. Finally, a backward algorithm is developed to calculate the probability at each decision point, which avoids difficulties in determining the asset volatility ratio; and a case study is presented to demonstrate application of the proposed method. Results show that decision rights for overseas investment are valuable. The value of extraction does not yet necessarily grow with higher uncertainty, and instead, it is under joint effects of the cash flow and strategy space. So, valuation should incorporate the composite value of future cash flow and decision rights. Volatility of the value of extraction is not solely dependent on the oil price, but affected by multiple factors. Similar to the Bermuda option, the decision-making behavior for oil and gas extraction occurs only at finite decision points, to which the trinomial tree option pricing model is applicable. The adoption of probability distribution can to a great extent exploit the uncertain information. Replacement of the decision-based tree with the probability-based tree provides more accurate probability distribution of the calculated value of extraction, and moreover the disperse degree of the probability can reflect how high risks are, which is conducive to decision-making for investment.

Abstract Based on the Sino-foreign petroleum cooperation project, the benefit evaluation algorithm of real economy based on big data analysis is proposed. The investment payback period, net present value, internal rate of return, discounted profit after investment and option value are selected as the benefit evaluation indicators of the real economy. The benchmark yield, discount rate and oil option parameters are defined as the benefits evaluation parameters of the real economy. Through the Delphi method and the analytic hierarchy process, the weight of each factor is specified. The method of expert independent scoring is used to construct the judgment matrix, and the consistency check is performed on the sort. The feature quantity matrix of the evaluation indicator is established to perform dimensionless processing on the original data. The project’s economic benefit indicators are divided into positive indicators of “ideal economic benefits” and negative indicators of “negative economic benefits”, the grey correlations are calculated, and real economic benefits are assessed. The results of project example analysis show that the algorithm not only realizes the whole life cycle management of overseas oil and gas cooperation projects, but also conducts tracking and evaluation of project implementation and economic benefits during the implementation process, and conducts sensitivity analysis on key indicators, that provides effective decision support for managers.

Global environmental pressure dictates that South Africa reduces its greenhouse gas (GHG) emissions, while national objectives focus on economic development. South Africa is faced with the dilemma of simultaneously alleviating poverty, reducing unemployment, growing the economy and responding to international pressure to reduce GHG emissions. As a result, policies that promote energy emissions reduction without being harmful to economic growth and national developmental priorities are needed. Environmental fiscal reform presents one such option. The impact of this is still unclear for South Africa, and this paper explores this issue. Energy balance data on energy consumption, energy emissions and input-output data for South Africa are used to assess the economic and environmental effects of environmental reform in the energy sector. Despite the high reduction in energy emissions, a tax on coal is not selected as the best alternative given the high negative impact on the economy. A tax on oil results in a low reduction in energy emissions, which limits its use as an environmental policy. The scenario using a petroleum products tax results in small decreases in economic growth but it has low energy emissions reduction, hence, this alternative is not selected as an option. Energy subsidy reform offers the second highest reduction in real energy emissions and a low decrease in economic growth, and this scenario is therefore recognised as the best option for carbon dioxide reduction in South Africa. The electricity tax offers moderate reductions in real energy emissions and a moderate decrease in economic growth, and therefore, it is deduced that the electricity tax option could be another option for carbon dioxide emissions reduction in South Africa.

Summary In this paper, we propose an optimization framework for maximizing asset value, both with and without uncertainty. We first present the methodology to treat a general control optimization in the presence of uncertainty, followed by a brief section on the optimization algorithms used. We then describe the field model example used to illustrate the application of the methodology. Through a systematic analysis of various deterministic and stochastic cases, we address the various objectives sought. Using net present value (NPV) as a measure, we also explore the valuation of advanced completions along with the returns gained from expanding surface gas-handling facilities. The method also generates an efficient frontier that can be used for risk and decision analysis. The results clearly demonstrate the value of such a framework for value maximization in planning both near- and long-term time horizons as well as providing the necessary foundation for maximizing asset value. Introduction We consider an existing infill program for a mature real onshore oil and gasfield with the objective of maximizing asset value. We do so by optimizing a history-matched reservoir model, and we provide confidence levels under uncertainty by generating efficient frontiers. Application of search or optimization algorithms has been the subject of numerous studies and articles both inside and outside the petroleum industry.1–14 Following from the work of Raghuraman et al.,1 this paper considers a real reservoir and attempts to maximize its value by analyzing various exploitation scenarios. The paper first describes the main features of the framework: the overall methodology and different optimization schemes. It then applies the optimization process to the field example. While maximizing asset value with and without the presence of uncertainty, the efficient frontier is discussed and its use for risk management and decision making is demonstrated. Methodology The process of optimizing a reservoir, under the assumption that everything is deterministically known, is relatively straightforward. One may want to extract the maximum fraction of oil and/or minimize the water production or maximize the NPV of the oil produced by optimally controlling various operational variables (e.g., individual-completion flow rates), all the while accounting for physical constraints (e.g., single-well production or pump/valve limitations) and economic constraints (e.g., drilling, logging, or stimulation costs). However, the presence of physical and/or financial uncertainties elevates the problem of optimization to the level of a risk-management problem. A framework has been developed that encompasses the necessary elements to perform reservoir optimization under uncertainty and to provide the risk analysis necessary for decision making. A detailed description of the process, with an example on reservoir monitoring and control, is given in Raghuraman et al.1 Fig. 1 shows a schematic of the algorithm for a problem with uncertainty.

Summary Spurred by improvements in reliability, cost, and accuracy, sensors offer a means of increasing expected ultimate hydrocarbon recovery in producing assets as well as in planned and prospective projects. Ultimate hydrocarbon recoveries larger than those currently achieved are possible, especially when sensors are used with advanced recovery methods. However, it is often unclear if the incremental recovery justifies the cost of installing the sensors. This paper proposes a method for estimating incremental values attributable to real-time sensors and provides a demonstration of the method for several production technologies and reservoir settings. The method offers a transparent and practical means of making value of information (VOI) computations to be implemented readily by project teams. An additional benefit of this method is that the process of specifying the inputs to the analysis facilitates a systematic discussion of strengths and weaknesses, and builds consensus regarding assumptions. The method is applied to four scenarios developed by a panel of industry experts to represent generic, but yet realistic reservoirs. The results for these scenarios indicate the value of sensors depends on the market price for product and the type of reservoir and production technology. The greatest absolute economic value for the use of sensors is obtained for a deepwater reservoir, while the greatest economic value per equivalent barrel of oil produced is obtained for a mature onshore reservoir. These expected economic values are intended to be compared to the cost required to implement the sensors to assess whether or not there is an expected net benefit. Introduction Formal methods of valuing information (sometimes called monetizing information) have existed in the research and professional literature for many years. Most publications on VOI have appeared in financial, economic, operations research, or decision analysis journals (Roberts and Weitzman 1981); little has appeared in engineering publications, especially petroleum engineering publications. Recently, a review of VOI in the oil and gas industry was presented by Bratvold et al. (2007). VOI methods are simple at the highest conceptual level: the values for courses of action with and without sensors are estimated and compared. The difference between the expected values with and without sensors is the expected value of the sensors and therefore represents the maximum willingness to pay (WTP) for the sensors. If the WTP for the sensors is greater than the cost of installation (e.g., sensor cost, installation costs, and deferred production) and operation of the sensors, their installation is expected to provide a net benefit. VOI assessments have the following components:They account for uncertainty in the outcome of decisions. The existence of uncertainty is the reason the valuation is based on expected values.They capture the ability of the sensors to change a decision. Typical decisions are an optimization of the current technology, immediate changes in technology, or the nature and timing of future technology changes.They allow for the sensors to change the monetary outcome of a course of action even when a decision is not changed by the information. This paper proposes a method for VOI assessment of real-time sensors and demonstrates the method for four different combinations of hydrocarbon recovery technologies and reservoir settings:CO2 injection in mature oil reservoirs,steam-assisted gravity drainage in heavy oil reservoirs,hydraulic fracturing in tight gas reservoirs, andwaterflooding in deepwater sandstone reservoirs. Drawing on industry experts, significant effort was made to make the cases as realistic as possible so the results can be used to inform the development of project- and corporate-level plans regarding the use of sensors. But, because of project and portfolio idiosyncrasies, the results are not to be viewed as definitive or totally generalizable.

Summary A new genetic algorithm (GA)-based correlation has been developed to estimate the change in MMP when CO2 is diluted with other gases, termed "impure CO2" in the context of this paper. The advantage of this correlation over others is that it can be used for gas mixtures with higher N2 concentrations (tested up to 20 mol%) and with non-CO2 component concentrations up to 78 mol% (e.g., H2S, N2, SOx, O2, and C1-C4) with a higher accuracy. Equally important, it could be a useful screening tool when experimental data are not available and when developing an optimal and economical laboratory program to estimate the MMP. In developing this correlation, the GA software developed in our earlier work (Emera and Sarma 2005a) has been modified to account for various components in the injected-gas stream. The correlation estimates the change in MMP as a function of injected-gas solvency in the oil. The solvency, in turn, is related to critical properties of the injected gas (critical temperature and pressure). In addition, pure CO2/oil MMP is used as an input in this correlation. The correlation has been validated successfully against published experimental data and several correlations in the literature. It yielded a better match with an average error of 4.7% and a standard deviation of 6.3%, followed by the Sebastian et al. (1985) correlation with a 13.1% average error and a 22.0% standard deviation and the Alston et al.(1985) correlation with a 14.1% average error and a 43.2% standard deviation. Introduction CO2 miscible flooding is among the most widely applied nonthermal enhanced-oil-recovery (EOR) techniques. Among gas-injection processes, CO2 is preferred to hydrocarbon gases because of its lower cost and high displacement efficiency. Furthermore, the increasing global awareness of the detrimental effects on the environment of industrial gases containing high CO2 concentrations has also contributed to an added impetus to harness these gases and sequester them into petroleum reservoirs while also enhancing oil recovery. An a priori understanding of the effect of various impurities on the CO2/oil MMP is critical to the design and implementation of a CO2 gas-injection project. Key factors that affect CO2 flooding are reservoir temperature, oil characteristics, reservoir pressure, and the purity of injected CO2 itself. Field case histories from CO2 floods in the Permian Basin, west Texas, suggest that CO2 purity should not be viewed as too rigid a constraint because the use of a low-purity CO2 stream could also be economic and effective in enhancing oil recovery. In fact, certain impurities, such as H2S and SOx, could contribute toward attaining CO2/oil miscibility at lower pressures. The presence of C1 and N2, however, could increase the MMP. From an operational perspective, it is often the remaining low percentages of non-CO2 gases that are more difficult and costly to remove, requiring expensive gas-separation facilities. Safety and compression cost considerations also justify near-miscible CO2 flood applications for some reservoirs. Therefore, the potential of injecting impure gases containing both CO2 and non-CO2 components (H2S, N2, SOx, O2, and C1-C4) could be an attractive option, provided the impure gas composition does not affect the process performance adversely and its overall impact on miscibility with the oil, separation/purification at the surface, and subsequent reinjection is evaluated and well understood a priori. This paper presents a reliable GA-based correlation to estimate the change in MMP when CO2 is diluted with other gases, together with a comprehensive comparison of its efficiency against other commonly used correlations (listed in Table 1). The software designed in our earlier work (Emera and Sarma 2005a) to develop an MMP correlation for pure CO2 and oil has been modified to account for impure CO2 gases with non-CO2 components. The GA software used in this study has been presented in the flow chart provided in Fig. 1. This figure also presents the stopping criterion under which the fitness of the solution is decided and accepted. The GA software uses real numbers coded as chromosomes (problem solutions comparable to chromosomes of the biological system) to encode the correlation in an initial random population (group of solutions) of 100 chromosomes size. Such an encoding technique enhances the GA robustness. Each chromosome is evaluated on the basis of a fitness value, which is designed on the basis of the objective function (minimizing the misfit between observed and predicted values). For the selection technique, the roulette wheel method was used. Also, to produce a new offspring (new solutions), reproduction operators such as one-point crossover and mutation were used. Moreover, the correlation errors could be minimized further through a series of iterative optimization runs using the previous software results as a new initial population.

It might seem incongruous that a research focused organisation such as the International Union for Pure and Applied Chemistry would pay attention to an issue as pragmatic as oil spills. After all, an oil spill tends to be viewed as a very practical matter, its issues characterised by loss of a valuable commercial product, damage to the environment, high costs of clean up, high legal liabilities, and very much media attention. Oil spills are not generally considered a pure or even applied chemistry issue. However, this would be a very short-sighted interpretation. Effectively every element of an oil spill, whether environmental, physical, operational or legal, is related to the complex chemistry of the oil and its breakdown products released to the environment. Indeed, it would be safe to say that if petroleum were a simple chemical product, the difficulties inherent in clean up of an oil spill would be much reduced, no matter what the origin or cause of the spill.The chemical nature of oil is directly related to the fate and environmental impacts of spilled oil, whether on water or on land, and to the effectiveness of the diversity of countermeasures which might be deployed. While evaluation of the effects of spilled oil on the environment receives much attention in forums with a biological or toxicological focus, which often do take into consideration chemical factors, the complex topic of the chemistry of oil spills in direct relation to countermeasures is examined more rarely. The various chapter in this document discuss a diversity of oil spill countermeasures, and target the chemical and consequently physical behaviour of oil which determines its characteristics at the time of the spill. While oil spills occur in fresh and salt waters, and on land, marine oil spills remain the larger issue - there tends to be more oil spilled, environmental problems are more complex, and countermeasures are more difficult to implement. The following papers generally reflect and review the current state of knowledge in their topic area, and are representative of the most recent surge in research and development activities, stimulated particularly by the Exxon Valdez spill in Prince William Sound, Alaska in 1989. It appears that oil spill research undergoes cycles of interest, activity and funding, linked to key oil spills. Previously, the Torrey Canyon spill in the English Channel off Land's End, in the United Kingdom in 1967 provided general incentive for research and development, as did the Amoco Cadiz spill off the coast of Brittany, France in 1978. Other oil spills, such as the 1968 Santa Barbara Channel, California spill, or the Braer spill off the Shetlands in 1993, among others, have also stimulated specific areas of research and development on the basis of issues that arose in their particular spill scenario.The articles in this publication have been contributed by recognised international experts in the spill response field, and have received the benefit of peer review. The articles are representative of the major categories of oil spill response research, spanning a wide range of technologies, supportive knowledge and experience, to include reviews of:This collection of review articles concludes with an evaluation of oil spill response technologies for developing nations, appropriately so since that is where much of the oil development and production currently occurs in the world.One area which has seen much recent expansion is that of the essential linkage between detailed understanding of spilled oil physical/chemical properties and the effectiveness of response countermeasures. Crude oils and oil products are known to differ greatly in physical and chemical properties and these tend to change significantly over the time course of spilled oil recovery operations. Such changes have long been recognised to have a major influence on the effectiveness of response methods and equipment, which increases the time and cost of operations and risk of resource damage. All countermeasures are influenced, whether sorbents, booms, skimmers, dispersants, burning of oil and so forth. The incentive is for a rapid and accurate method of predicting changes in oil properties following spill notification, which could be used in both the planning and early phases of spill response, including an initial specific selection of an effective early countermeasure. In later stages of the response, more accurate planning for clean up method and equipment deployment would shorten response time and reduce costs. An additional benefit would be more effective planning for recall of equipment not needed, as well as potentially decreasing the risk of natural resource damage and costs due to more effective spilled oil recovery. The concept of "Windows of Opportunity" for oil spill response measures has been derived from multiple investigations in industry and government research organisations.Although dispersants have been used to date in almost one hundred large spills world-wide, government approval for dispersant use has long been inhibited by a lack of understanding of the factors determining the operational effectiveness of dispersants, and the environmental trade-offs which might need to be made to protect sensitive areas from spilled oil. Recent advances in chemical dispersant development, formulation of low toxicity dispersants with broader application, and better understanding of dispersant fate and effects have combined to a more ready acceptance of this countermeasure by many, although not yet all, regulatory authorities throughout the world. In addition to the category of dispersants, chemical countermeasures include many diverse agents, such as beach cleaners, demulsifiers, elasticity modifiers and bird cleaning agents, each with a unique and specialised role in clean up activities. However, the concerns for the use of these 'alternative chemicals' relate to the interpretation and application of toxico-ecological data to the decision process. If in the future the ecological issues concerning chemical treating agents can be further successfully resolved, the oil spill response community will have an increased range of options for response. However, extensive laboratory and field testing is required in many instances for new chemical dispersant materials and demulsifiers to improve the effectiveness of these materials on weathered oils and water in oil emulsions. The acceptance of in situ (i.e. 'on site') burning of spilled oil has been limited by valid operational concerns about the integrity of fireproof booms, the limited weather window for burning due to the rapid emulsification of oils, the need to develop methods for the ignition of emulsified and weathered oils, and public concerns about the toxicity of the smoke generated during burning. However, burning provides an option, another tool in the tool-box, for the responder called in to combat an oil spill. Burning decreases the amount of oil that must be collected mechanically, thus reducing cleanup costs, storage, transportation, and oily waste disposal requirements. It also would decrease potential contact with sensitive marine and coastal environments and consequently reduce the potential for associated damage costs. Laboratory and field studies over the last ten years have addressed essential information requirements for feasibility, techniques, and effectiveness, as well as health and safety. The results of research in situ burning has led to its acceptance in a number coastal jurisdictions throughout the world, prompting the response industry to purchase and position in situ burning equipment and train its operators to use this alternative technology in approved regions.Although not a direct recovery measure in itself, the application of remote sensing to oil spill response assists in slick identification, tracking, and prediction, which in many instances is an early requirement for effective response. An inadequate ability to see spilled oil seriously reduces effectiveness of oil spill response operations. Conversely, good capability to detect spilled oil, especially areas of thick oil, at night and other conditions of reduced visibility could more than double response effectiveness and greatly enhance control of the spill to minimise damage, especially to sensitive shorelines. Advances have been made in both airborne and satellite remote sensing. It has become possible to move from large and expensive to operate airborne systems to small aircraft, more widely available and practical for spill response operators. Also, the limitations in delayed data processing and information communication are being overcome by development of systems operating in functional real-time, which is essential for enhanced response capacity. Spill detection using satellites has also advanced markedly since 1989, with the ongoing intention to provide coverage of oil spill areas as early warning, or when flying by aircraft is not possible. An early useful application was an ERS-1 satellite program for detection of oil slicks, launched in 1992. More recently, spill detection capability has been developed for the Canadian Radarsat satellites, ERS-2 and a few other satellite programs.The topic of bioremediation of spilled oil, that is, to use microbes to assist in clean up, is a corollary to the deployment of traditional countermeasures. It had not seen much operational or regulatory support until the Exxon Valdez spill, where it was initiated as a spill mitigation method, establishing bioremediation as a major oil spill R&D area. Bioremediation of oil spills was defined as being one of three different approaches: enhancement of local existing microbial fauna by the addition of nutrients to stimulate their growth; 'seeding' the oil impacted environment with microbes occurring naturally in that environment; and, inoculating the oil impacted environment with microbes not normally found there, including genetically engineered bacterial populations. Research emphasis and regulatory countenance has been predominantly on the first approach. Evaluation of operational utility of is continuing to identify conditions under which bioremediation can be used in an environmentally sound and effective manner, and to make recommendations to responders for the implementation of this technology.The issue of hydrocarbon toxicity has been examined in petroleum refinery and petrochemical workers for more than a decade, and experimentally in test animals for a much longer period. However, there has been little specific information available on the effects of oil spills on human health, neither for oil spill response workers nor for incidentally exposed individuals. More recently, as reviewed in an article on human health effects in this publication, some reports have been published of skin irritation and dermatitis from exposure of skin to oil during cleanup, as well as nausea from inhalation of volatile fractions. Although there are to date no epidemiological studies of exposure by oil spill workers to petroleum hydrocarbons, the matter is drawing increasing attention.One of the more important issues surrounding the choice and extent of application of oil spill countermeasures is knowledge about the ecological effectiveness of such response, that is, the balance point between continuation of clean up activities and letting the environment take care of its own eventual recovery. It is the last point which has driven much of the discussions and research associated with the concept of 'how clean is clean', or, how much cleanup is enough or too much. The results of such diverse research efforts are being used increasingly and successfully to link spilled oil chemistry to countermeasures practices and equipment. The advances are being integrated into more effective response management models and response command systems. In summary, applied chemical research and development has actively contributed to an enhancement in oil spill response capability. Nonetheless, it seems that the pace of oil spill research and countermeasures development is slowing. The decrease is at least temporally associated with a decline in the frequency and magnitude of oil spills in recent years. Spill statistics gathered by organisations such as the publishers of the Oil Spill Intelligence Report, show that world-wide oil spill incidence and volume have continued to decline since the time of the Exxon Valdez spill event (see the Oil Spill Intelligence Report publication "International Oil Spill Statistics: 1997", Cutter Information Corp.). It is probably not coincidental that the amount of funding available for oil spill research and development, from both government and private industry sources, has declined similarly. In that context, the following articles are more a statement of currently accepted knowledge and practice, rather than being a 'snapshot in time' of intense ongoing research activities. The articles serve to capture the applied chemistry knowledge and experience of practitioners in a complex field, application of which remains essential for the development of improved oil spill countermeasures, and their effective use in real spill situations.

Indonesia had become an oil exporter that is recognized by the world for many years and joined The Organization of Petroleum Export Community (OPEC) – an organization that controls petroleum production, supplies, and prices in the global market – in 1962. However, oil production in Indonesia has been decreasing from year to year, one of which is due to the lack of investment in the exploration of new oil wells in Indonesia so the majority of upstream oil and gas work in Indonesia is exploiting old wells which will naturally decline steadily. This resulted in Indonesia becoming a net import oil country in 2003. Therefore, additional operations are needed to maximize oil production from these existing wells, one of which is by conducting Chemical Enhanced Oil Recovery (CEOR). The main objective of EOR itself is to mobilize the remaining oil by enhancing the oil displacement and volumetric sweep efficiency. PT. ABC, a subsidiary of PT. XYZ (a state-owned company under SKK Migas and PT Pertamina supervision) which is engaged in the upstream sector in Indonesia, is assigned by the government to carry out one of the CEOR projects that have been determined by the Government. This research covers the economic feasibility of the CEOR Project based on the conventional Discounted Cash Flow (DCF) and Real Option Valuation (ROV) Model. The revenue-sharing policy used for the project economic calculation is the gross split method. The result of the economic analysis using the DCF method is the project is not economically feasible to run as the net present value (NPV) shows negative which is -2,911 MUSD. However, the real option valuation model helped increase the value to 11,416 MUSD by adopting a strategic option which is an option to delay and time flexibility into the project. As a result, the project could be economically feasible if the operation is deferred to the following year and the oil price is over 85.2 USD/BBL.

The present study is designed to demonstrate the application of the option valuation technique in the field of real assets valuation and in particular – valuation of entire enterprises. The main postulates and assumptions underlying the valuation of options are presented, and in order to derive the most plausible valuation methodology, a key emphasis is placed on the dynamics of the underlying asset. The main probabilistic processes modeling the behavior of asset prices cited in the scientific literature and used in practice are analyzed. In the practical part, the option technique is applied for valuation of an enterprise operating in the field of oil production, distribution and sale, as two parallel comparative estimates of the enterprise value are made depending on the assumptions for the dynamics of uncertainty of the underlying asset.

Purpose: This article focused on the main business insights of the use of Real Options valuation analysis in the eyes of a finance professional. It used a case study of an investment opportunity in the oil and gas field services industry in Latin America to discuss the methodology implementation and its insights. As a secondary objective, it discussed the insights and options embedded in this investment opportunity.Methodology: The investment opportunity was examined using the Real Options Analysis (ROA) framework and the results compared to the traditional methodology of Net Present Value. The valuation technique was performed as if it had been applied at the time the project was approved.Findings: The most important of Real Option valuation is not the results, but how one arrives at them. After the project value is calculated and the project approved or not, the Real Option valuation requires and supports the monitoring of the project. By understanding how the options are created, managers can make better decisions about the project after it was approved.Practical implications: A relevant contribution from the study was the discussion, as a practitioner, of the methodology implementation in a real world corporation. Originality & value: The case study evaluated two types of real options: first, the effect of an option to cancel a contract that was assessed from the perspective of the client contracting the project; and second, the option to abandon and defer, from the perspective of the company that will perform the investment to provide the services. By incorporating the cost of the put option that the company puts forth for the client (cancellation option) it reduces the project value by giving flexibility to its clients.

Abstract. Real options are one of the most interesting research topics in Finance since 1977 Stewart C. Myers from MIT Sloan School of Management published his pioneering article on this subject in the Journal of Financial Economics. Real options are techniques for supporting capital budgeting decisions that adapt techniques developed for financial securities options. The purpose of using this real option is to capture the options contained in projects that cannot be captured by the discounted cash flow model which operates as a basic framework for almost all financial analyzes. The process of valuing real options will be complemented by the stochastic interest rate and stochastic volatility to better capture the flexibility and volatility of the existing economic and financial situation. The valuation will use a Monte Carlo simulation with the MATLAB programming language on crude oil data from the North Sea oil field. Data were obtained from the thesis of Charlie Grafström and Leo Lundquist with the title "Real Option Valuation vs. DCF Evaluation – An Application to a North Sea oilfield".Keyword: real options, stochastic interest rate model, stochastic volatility model, simulation

Abstract Subsea dispersant injection (SSDI) has been implemented as a response method since it was first used in large-scale during the Macondo subsea blow-out in the Gulf of Mexico in 2010. Oil and gas operators have access to SSDI equipment through multiple suppliers of response equipment. This equipment is a crucial part of the capping and containment package offered in the event of a subsea blow-out. The concept is used to ensure access to the spill site (remove surface oil), improve working conditions (reduce exposure to volatile oil components) and finally be used as a response option to reduce environmental impact form the spill (reduce surfacing & stranding of oil and increase natural biodegradation of dispersed oil as small droplets). However, a subsea blow-out of 12 000 m3/day, would require 800–1600 m3 of dispersant for the first week with a dosage of 1–2%. Controlling the dispersant dosage could be critical, especially, since the initial volume of available dispersants could be limited. This paper presents a new system for automatic dispersant dosage control. The system monitors the size distribution of the released oil droplets and gas bubbles. The injected dosage of dispersant is then automatically adjusted to obtain a desired oil droplet size. The dispersant dosage from a hydraulically operated valve is adjusted based on a real-time signal from a silhouette camera (SilCam) positioned in the rising oil & gas plume. The SilCam is used to quantify oil droplet and gas bubble distributions. The SilCam can be held in place by a Remote operated Vehicle (ROV) and all signals are brought to the operator onboard the supply vessel via the ROV's umbilical cord. The concept is tested by down-scaled experiments at SINTEF and verified in full-scale by Oceaneering in a large ROV test pool. This study was headed by Oceanering in close cooperation with SINTEF and funded by the Norwegian Research Council and multiple Norwegian energy companies; Equinor Petroleum AS, Lundin Norge AS, ENI Norge AS, Total E&P Norge AS and ConocoPhillips Scandinavia AS.