Probability Of Economic Success Research Articles

Hydrocarbon Field (Re-)Development as Markov Decision Process

Summary Hydrocarbon field (re-)development requires that a multitude of decisions are made under uncertainty. These decisions include the type and size of surface facilities, location, configuration, and number of wells but also which data to acquire. Both types of decisions, which development to choose and which data to acquire, are strongly coupled. The aim of appraisal is to maximize value while minimizing data acquisition costs. These decisions have to be done under uncertainty owing to the inherent uncertainty of the subsurface but also of other costs and economic parameters. Conventional value of information (VOI) evaluations can be used to determine how much can be spent to acquire data. However, VOI is very challenging to calculate for complex sequences of decisions with various costs and including the risk attitude of the decision-maker. We are using a partially observable Markov decision process (MDP) to determine the policy for the sequence and type of measurements and decisions to do. A partially observable MDP (POMDP) is characterized by the states (here: description of the system at a certain point in time), actions (here: measurements and development scenario), transition function (probabilities of transitioning from one state to the next), observations (measurements, appraisal activity), and rewards [costs for measurements, expected monetary value (EMV) of development options]. Solving the MDP gives the optimum policy, sequence of the decisions, the probability of maturation (POM) of a project, the EMV, the expected loss, the expected appraisal costs, and the probability of economic success (PES). These key performance indicators can then be used to select in a portfolio of projects the ones generating the highest expected reward for the company. Combining the production forecasts from numerical model ensembles with probabilistic capital and operating expenditures and economic parameters allows for quantitative decision-making under uncertainty.

Parental transfers under ambiguity

ABSTRACT This note introduces parental uncertainty into parent–child monetary transfers. A parent questions the probability distribution of a child’s future economic success. As a result, the parent endogenously tilts his/her subjective probability model away from an approximating probability model. In this case, parental transfers increase with model uncertainty, thereby reducing the child’s effort and probability of economic success. This theoretical result raises several empirical questions, of which two are as follows. For one thing, informed parents (e.g. those who hold the same job as their child) transfer less money, and their child exerts more effort. Another is that economic uncertainty (e.g. recessions or pandemics) prompts higher parental transfer payments and reduces the child’s effort.

Maximizing the Value of Information of a Horizontal Polymer Pilot Under Uncertainty Incorporating the Risk Attitude of the Decision Maker

SummaryPolymer injection might lead to incremental oil recovery and increase the value of an asset. Several steps must be taken to mature a polymer-injection project. The field needs to be screened for applicability of polymer injection, laboratory experiments have to be performed, and a pilot project might be required before field implementation.The decision to perform a pilot project can be dependent on a value-of-information (VOI) calculation. The VOI can be derived by performing a work flow that captures the effects of the range of geological scenarios, as well as dynamic and polymer parameters, on incremental net present value (NPV). The result of the work flow is a cumulative distribution function (CDF) of NPV linked to prior distributions of model parameters and potential observables from the polymer-injection pilot.The effect of various parameters on the CDF of the fieldwide NPV can be analyzed and in turn used to decide which measurements from the pilot have a strong sensitivity on the NPV CDF, and are thus informative. In the case shown here, the water-cut reduction in the pilot area has a strong effect on the NPV CDF of the polymer-injection field implementation. To extract maximum information, the response of the pilot for water-cut reduction needs to be optimized under uncertainty.To calculate the VOI, the expected-monetary-value (EMV) difference of a decision tree with and without the pilot can be used if the decision maker (DM) is risk neutral. However, if the DM requires hurdle values through a probability of economic success (PES), value functions (VFs) and decision weights according to the prospect theory should be used. Applying risk hurdles requires a consistent use of VFs and decision weights for calculating VOI and the probability of maturation (POM) of projects.The methodology was applied to assess the VOI for a horizontal-well pilot in the ninth Tortonian Horizon (9TH) Reservoir in Austria for a risk-averse DM. The operating parameters (polymer concentration and water injection) were chosen such that the water-cut reduction, which was the most influential parameter of the polymer pilot on the field NPV CDF, was maximized.

Investment Uncertainty Analysis in Eucalyptus Bole Biomass Production in Brazil

Forestry investment projects for the biomass production of the eucalyptus bole can be characterized by uncertain environments, which result in economic risk to the forest producer, however that can be measured by applying probabilistic techniques. This was our motivation and justification for analyzing the economic-financial viability of different silvicultural practices for eucalyptus bole biomass production under conditions of uncertainties, running Monte Carlo method for risk management. The experiment was carried out in the state of São Paulo, Brazil, using 5 treatments with spacings of 3 × 2 m; 3 × 1 m; 1.5 × 2 m; 3 m × 0.5 m; and 1.5 m × 1.0 m, i.e., different spacings between planting lines and plants. These treatments were characterized as investment projects. To develop stochastic models, we relied on technical-economic deterministic variables. We evaluated the investment projects based on the cash flows under conditions of uncertainty, discounted at the attractiveness rate calculated by capital asset pricing model. With the results of these economic flows, the net present value, the modified internal rate of return and the profitability index values were estimated, commonly used in the analysis of investments in projects. The results showed that based on economic metrics, the three-year rotation cycle for forest stands for biomass production of the main bole of eucalyptus, with a spacing of three meters between rows and two meters between plants, had an 83% probability of economic success. The sensitivity analysis showed that the bole biomass of eucalyptus is the most important variable for determining the economic-financial feasibility of the investment project.

EFFECT OF PRODUCTION PARAMETERS ON THE ECONOMIC FEASIBILITY OF A BIOFUEL ENTERPRISE

AbstractIn order to guarantee the success of the nascent cellulose-based biofuel industry, it is crucial to identify the most economically relevant components of the biofuel production path. To this aim, an original stochastic financial model is developed to estimate the impact that different feedstock production and biofuel conversion parameters have on the probability of economic success. Estimation of the model was carried out using Monte Carlo simulation techniques along with parametric maximum likelihood estimation procedures. Results indicate that operational efficiency strategies should concentrate on improving feedstock yields and extending the feedstock growing season.

Minimum economic field size estimation and its role in exploration project risks assessment: evaluation of different methodologies

The E&P business is most often rife with risks and uncertainties. The capability of recognizing and quantifying these uncertainties and associated risks are the key to success. For consistent exploration project risk analysis, a standard discounted cash-flow approach, combining the geological risk, Minimum Economic Field Size (MEFS), resource size distribution, development cost, rate streams, commodity price, discount rate and cash flow estimation, has been used. This task requires highly skilled geoscientists, reservoir, facility, drilling engineers and economists to estimate field development costs, generate the economic indicator to rank the exploratory prospects’ potential success and to support the informed business investment decisions. The ‘Exploration Success’ contains two main variables: (1) Probability of geologic success (Pg), and (2) Probability of economic success (Pe). To remove sub-economic volumes from the volumetric distribution, the industry uses the estimation of minimum required (break-even) resources for the full project life-cycle, considering the most likely development scenario in exploration projects. For appraisal and pre-development projects, the minimum required resources are used to benchmark the confidence level of already discovered resources with their chance of success to be economically viable. Despite several contributions made in the past and available in the literature, to the best of the author’s knowledge, most often a deterministic MEFS value is being used for the exploration project risk assessment. This single MEFS value does not allow for the capturing of the risks associated with the different input parameters uncertainties, which are used for the MEFS estimation. Therefore, in this paper, we are reviewing and systematically describing the appropriate MEFS estimation methodology. The influence of key parameters has been analysed through an example, using different MEFS methods, to demonstrate their importance for MEFS estimation. The comparison of results allows clear judgmental insights into the problem and its related uncertainties, understanding and quantifying the exploration risks and hence the chance of overall economic success.

Establishing minimum economic field size and analyzing its role in exploration-project risks assessment: A practical approach

The upstream E&P industry is one of the riskiest businesses in which to invest and is dominated by different types of uncertainties: political, economic, social, and technical. Many factors can lead to optimistic or pessimistic risk assessment. Overestimation, underestimation, misidentifying critical risks, overselling projects, and underselling projects are some of the problems. For consistent risk analysis of exploration projects, a systematic approach is used that includes geologic risk, minimum economic field size (MEFS), resource-size distribution, development cost, rate streams, commodity price, and discount rate. This approach requires highly skilled geoscientists and reservoir, facility, and drilling engineers to estimate field-development costs, generate the economic indicator, rank the exploratory prospects' potential success, and support the business decisions. The definition of “exploration success” contains two main variables: (1) probability of geologic success (Pg) and (2) probability of economic success (Pe). To remove the risk of subeconomic volumes from the volumetric distribution, the industry uses the estimation of minimum required resources for the full project life cycle, considering the most likely development scenario. An effort is made to describe the appropriate MEFS estimation methodology, which is an essential component for consistent exploratory-project risk analysis. The influence of key parameters on MEFS estimation, including some illustrative examples, also are analyzed to demonstrate the criticality of MEFS estimation and its impact on exploratory-prospect risk assessment and to achieve an overall economic success.

Economic comparison of open pond raceways to photo bio-reactors for profitable production of algae for transportation fuels in the Southwest

As energy prices climb there is an increasing interest in alternative, renewable energy sources. One possible source of renewable bio-fuel is algae. This research uses a multi-year, Monte Carlo financial feasibility model to estimate the costs of production and chance of economic success for commercial size algal biofuel facilities in the Southwest. Capital and operating costs and productivity information from Davis et al. were used to develop parameters to define and simulate two types of algae production systems; open pond and photo-bioreactor (PBR).The financial feasibility of PBRs is substantially lower than for open ponds. In the base case, average total costs of production for lipids, including financial costs, were $12.73/gal and $31.61/gal for open ponds and PBRs, respectively. The chance of economic success for the base situation was zero for both open ponds and PBRs. The financial feasibility analysis showed that the only way to achieve a 95% probability of economic success in the PBR system was to reduce CAPEX by 80% or more and OPEX by 90% or more. For the open pond system there were several options that could return a 95% or greater chance of economic success, for example, reducing CAPEX by 60% and OPEX by 90%.

Measuring The Impact Of 3D Seismic On Business Performance

Three-dimensional seismic has had a major impact on the performance of Amoco's E&P operations. In the last 4 years, 3D seismic has helped improve reserves replacement, improved exploration finding rates and volumes, and had a positive effect on field-reserves revisions. This paper discusses the performance improvements that 3D seismic has brought to the company and suggests ways to measure the impact of emerging technologies. These measures gauge the benefits as well as the easily measured costs when managing technology investments.

Evaluating and managing risk in small‐scale fish farming in a developing economy: An application to Rwanda

Policy makers in developing economies continue to promote small‐scale fish culture as a means of generating stable income and alleviating malnutrition and famine problems. In some places like Rwanda, land previously established with traditional crops has been re‐allocated to small‐scale fish culture. While the income derived from fish farming is a powerful incentive to produce an alternative crop, the lack of information on the risk associated with returns from small‐scale fish farming in Rwanda is striking. This study used the @Risk risk analysis and simulation add‐in for Lotus 1–2–3 to determine the range and the probability of economic success or failure, to identify sources of risk, and to evaluate ways of minimizing risks in small‐scale fish production in Rwanda. The study compared fish farming by cooperatives and by individual farmers. Small‐scale fish farming showed economic potential in Rwanda when evaluated as positive income above variable costs. The event ‘income above variable costs is at least zero’ occurred with a 100% probability for both cooperatives’ and individual farms. When evaluation was based on net returns to land and management, economic failure became a virtual certain event, occurring with 99.8% and 95.5% probabilities for cooperatives and individual farms, respectively. Although, the level of success was sensitive to higher stocking rates, and higher fish producer prices, the amount of labour used in the production‐marketing process was the major determinant of economic success. The upper limit of the efficient level of labour was estimated at 20 person‐days per 100 m2 per growing cycle, Ceteris paribus.

A farm level expert simulation system to aid farmers in selecting among crop insurance strategies

An expert simulation system (ESS) in aid U.S. farmers select crop insurance strategies is presented. The ESS, entitled CIRMAN, relies on stochastic simulation models to analyze the problem and formulates a series of rules to make recommendations. The following lexiographic hierarchy of rules is used to rank the strategy options: (1) risk efficiency; (2) probability of farm survival; (3) probability of economic success; (4) expected value of after-tax net present value of family withdrawals plus the change in net worth over the planning horizon; (5) average expected annual net-cash farm income; and (6) average expected value of ending net worth. CIRMAN presents a recommendation and explanations on why a strategy was recommended and how it compares to specified alternatives.

Probability of Economic Success for Wells Drilled Below 18,000 Ft in Southern Louisiana: ABSTRACT

Probability of Economic Success for Wells Drilled Below 18,000 Ft in Southern Louisiana: ABSTRACT

Ranking South Louisiana Trends by Probability of Economic Success: ABSTRACT

Hydrocarbon exploration is an economic and a probabilistic enterprise. Especially in mature provinces, where the giant discoveries have mostly already been made, we must incorporate probability and economics into exploration if our efforts are to be successful. Not even the largest companies have the resources to be active in all the exploratory plays possible; we find ourselves concentrating on only a small number of the available plays. This choice of where to explore should be made by defining the objective of exploration and then concentrating on those plays which have the highest probability of achieving that objective. For a limited partnership drilling fund, the objective was formulated as a 3:1 present worth return on the money risked by the investors. A trend analysis process was developed which combines the probability of making a discovery with the probability distribution of reserves found to determine the probability of obtaining a desired return. The industry's performance was analyzed for the years 1970 through 1981. For the foreseeable future we will be using the same technology as the 1970s and can reasonably expect the continuation of the trends of physical results (success ratios and the size distribution of discoveries). These physical results were combined with price and cost forecasts for the 1980s to obtain a realistic projection of expected exploratory success. The steps in the analysis are as follows. (1) Geological Classification--A data base was developed containing the well information on 4,800 new-field and other exploratory wells drilled in south Louisiana. Each well was classified as to the objective formation and as to the producing formation(s) if successful. Twenty-nine separate trends were identified and analyzed. (2) Exploratory Drilling Data Analysis--A computer program was written to sort the well data by trend, project and exploratory success ratios for oil and gas, and prepare depth and cost analysis. (3) Reserves Added Analysis--Reserve estimates were made for 858 (557 gas, 301 oil) discoveries by projecting rate-cumulative production decline curves. Discovery sizes for the trends exhibited the expected log-normal frequency istributions. (4) Economic Projections--Using projected costs and product prices, a profile was developed for each trend of present worth profit as a function of discovery size. As usual, many discoveries can be expected to be successes but economic failures. (5) Probabilistic Analysis--Utilizing the Monte Carlo technique, a computer program was written to realistically simulate an n-well exploration program. The result for each trend was a cumulative frequency distribution of the return per exploration dollar. Using the same exploratory budget for all trends allowed us to rank trends based upon the probability of achieving the desired present worth return or better. Examples are presented for trends of varying rank. In summary, computer data banks were used, along with thorough geologic analysis and some common sense, to provide a sound basis for concentrating exploration effort on those trends where we are most likely to achieve our objective. End_of_Article - Last_Page 491------------