Saul B. Suslick

Quantifying the value of technological, environmental and financial gain in decision models for offshore oil exploration

Abstract This paper suggests a framework to improve the quality of investment decisions in petroleum exploration. The proposed model enables the decision-maker to consider explicitly three major objectives when evaluating new petroleum ventures—financial, environmental and technological gain. The MultiAttribute Utility Theory (MAUT) provides a logical mean of decision for conflicting objectives. The MAUT is based on the risk preference of the firm, combining the objectives in the unique additive or multiplicative model. A high-dimensional sensitivity analysis technique is used for evaluating the weights of multicriteria decision models. The main advantage of this approach is that it allows a better simultaneous change of the weights and provides indications for a robustness control. The weights are obtained by a random process and are hierarchically adjusted using the analyst preferences. This paper proposes a study case comparing the application of this methodology in exploration projects located at five different offshore oil provinces in the Brazilian Continental Shelf. The MAUT methodology presented in this work demonstrates that, in some mature areas, the advantages of exploration are restricted only to financial gain. On the other hand, other seemingly less attractive areas, such as deep horizons in deep-water basins, may represent attractive targets for new exploration as a result of the interaction of technological advancement, and financial and market factors. The proposed approach allows the investigation of sensitivity for several options and alternatives. It also provides a rational tool for managers to make decisions according to firm preferences and objectives in complex oil prospects.

Identifying potential impacts of bonding instruments on offshore oil projects

Abstract The present paper deals with the potential financial impacts of different bonding instruments on offshore oil projects. Three types of performance bond instruments (corporate surety, leasing-specific abandonment account, and cash) were tested and analyzed for three offshore oil-producing fields under a hypothetical bonding regime. Sensitivity analysis of ‘net present’ and ‘government take’ values indicates corporate surety bonds cause fewer impacts yielding significantly better payoffs. Several related issues are discussed considering government and industry perspectives.

A decision model for financial assurance instruments in the upstream petroleum sector

The main objective of this paper is to deepen the discussion regarding the application of financial assurance instruments, bonds, in the upstream oil sector. This paper will also attempt to explain the current choice of instruments within the sector. The concepts of environmental damages and internalization of environmental and regulatory costs will be briefly explored. Bonding mechanisms are presently being adopted by several governments with the objective of guaranteeing the availability of funds for end-of-leasing operations. Regulators are mainly concerned with the prospect of inheriting liabilities from lessees. Several forms of bonding instruments currently available were identified and a new instrument classification was proposed. Ten commonly used instruments were selected and analyzed under the perspective of both regulators and industry (surety, paid-in and periodic-payment collateral accounts, letters of credit, self-guarantees, investment grade securities, real estate collaterals, insurance policies, pools, and special funds). A multiattribute value function model was then proposed to examine current instrument preferences. Preliminary simulations confirm the current scenario where regulators are likely to require surety bonds, letters of credit, and periodic payment collateral account tools.

Managing Technological and Financial Uncertainty: A Decision Science Approach for Strategic Drilling Decisions

This paper presents a framework to improve the quality of investment decisions in petroleum. The model presented enables the decision-maker to explicitly consider two major objectives when evaluating new petroleum opportunities—financial and technological gain. We utilize MultiAttribute Utility Theory (MAUT) to consider simultaneously the technological challenges of petroleum exploration into the capital budgeting process of an exploration and production firm. The MAUT methodology presented in this work demonstrates that in some mature areas the advantages to exploration are restricted further only to financial gain, based upon the present economic potential of the basin. On the other hand, other seemingly less attractive areas, such as deep horizons in deep-water basins, may represent attractive targets for new exploration as a result of the interaction of financial gain and technological advancement. This advantage reflects the technological gain as a key factor for future operations for oil discoveries in areas with big geological potential. The model presented in this work enables the decision-maker to consider explicitly the risk and rewards associated with both financial and technological payoffs, the decision-makers tolerance for those types of risks, and the relative importance of each of those objectives in the context of ongoing petroleum exploration decisions.

Forecasting of petroleum consumption in Brazil using the intensity of energy technique

Abstract The purpose of this paper is to forecast petroleum consumption in Brazil for the year 2000 based upon logistic models, learning models, and translog models using the technique of intensity of energy use. The models employ a time series of 30 years for projection. An investigation of the evolution of petroleum consumption profile was made based upon three characteristic effects: structural, content and scale effects. Evaluation of forecasting models presented good results, with the translog model showing the best performance in terms of accuracy. The learning and translog models indicated that GDP is the main determinant for petroleum consumption evolution in the future, defining a range of 64 000 and 109 000 thousand of tonnes of oil equivalent on two defined GDP growth scenarios.

Long-range metal consumption forecasts using innovative methods : The case of aluminium in Brazil to the year 2000

Abstract Brazils aluminium consumption in the year 2000 is forecast to be in the range of 800 000 to 1 300 000 tonnes; these bounds correspond to annual rates of growth in GDP of 3.6% and 6.1% respectively. This range of consumption conforms closely to that produced by an extensive translog consumption model which includes GDP, price of aluminium and its chief substitute, copper, and time as a proxy for technical change in aluminium using products and product technology. Analysis of various models by ex post forecast errors on a test period showed the most accurate models to be a simple learning model for cumulative IU and a time varying coefficient consumption model, followed by the extensive translog consumption model. The models with the largest ex post errors included the linear IU, lognormal IU, and extensive learning IU models.

Alocação de recursos financeiros em projetos de risco na exploração de petróleo

With the new changes in the petroleum sector in Brazil, the exploration will enter in an increasingly competitive and risky business environment. The trends of internationalization of exploration and risk reducing recommend the use of standardized techniques of evaluation and comparison of plays and prospects. Under these circumstances, managers have a growing need to employ better and more systematic decisionprocesses that explicitly embody the firm’s objectives, desired goals, and resource constraints. In order to spread risk in major projects, oil companies will continue to engage in joint ventures. This paper describes a theoretical and practical system for decision support based upon the expected utility theory and decision analysis, in order to estimate the best capital allocation and to define the best level of financial participation of a firm in the new ventures in petroleum exploration project.

SERFIT: an algorithm to forecast mineral trends

Abstract A PASCAL computer program, named SERFIT, facilitates the identification of trend model for long-term forecasting and the estimation of model parameters. Model identification is achieved through the computation of slope characteristics from mineral data time series. The trend models generated by the program are: linear, normal, lognormal, and modified exponentials: simple-modified exponential, logistic, derivative logistic, Gompertz, and derivative Gompertz. Parameters of the family of modified exponential models are estimated using Mitscherlichs regression, which is based upon the maximum likelihood method and provides a probability structure for the models. SERFIT is demonstrated on U.S. petroleum production and world copper consumption data.

A method to estimate block values through competitive bidding

The bidding process is a mechanism that has been widely used by different countries to optimally distribute their oil exploratory acreages. One of the big challenges for both companies and government agencies is the estimation of the block values. Considering that the bid value is by and large a fraction of the estimated unknown reserve, the objective of this article is to reach a set of proxies of unknown values of the blocks through the successful bids. The estimation value of the block is calculated through a stochastic simulation of bid fractions using a compound probability distribution. The model was tested and validated using the public data available from the Brazilian seven licensing rounds. For these competitive bids, areas widespread in 22 sedimentary basins were offered to more than 50 oil companies that retained 610 blocks, paying

Geociências: um ensaio preliminar de avaliação e perspectiva

1.4 billion as a cash bonus. The model output was restricted to the Campos Basin because it is one of the most attractive areas for oil and gas opportunities, concentrating approximately 80% of the Brazilian national oil production with a supply of 1.8 million bbl/day. The simulation model indicated that this approach can be used as an auxiliary decision framework by oil companies for new investments and bidding strategies as well as by the regulatory agency to evaluate bid performance in different world regions and geological settings possessing similar competitive bidding schemes.