Holistic oil field value management: using system dynamics for ‘intermediate level’ and ‘value-based’ modelling in the oil industry

System dynamics has been seen primarily as a strategic tool, most effectively used at the highest level of strategy to identify robust policy interventions under a wide range of scenarios. However, an alternative, complementary and powerful role is emerging. This is at an ‘intermediate level’ in organisations to coordinate and integrate policies across the value chain. It is at this level where business value, as defined by the discounted value of future free cash flow, is both created and destroyed. This paper introduces the need for ‘intermediate-level’ and ‘value-based’ modelling and emphasises the natural role of system dynamics in supporting a methodology to fulfil the need. It describes the development of an approach and its application in the oil industry to coordinate the response of people and tools within operational, financial and commercial functions across the value chain to address a variety of problems and issues.     

Improving harvesting and transport planning within a sugar value chain

Recent economic pressures have forced the Australian sugar industry to achieve better integration and optimization of the cane harvesting and transport sectors of the value chain. The logistical and economic complexity of the harvesting and transport system was captured through the development of a modelling framework that effectively links several component models that describe the parts of the system. Through engaging in participatory research with representatives of a sugar region located at the north-east coast of Australia, we use this modelling framework to address some key industry issues in rationalizing rail track infrastructure and re-organizing harvesting. These issues were addressed by building component models for the modelling framework in the field of location science, namely the capacitated P-Median problem and spatial clustering. By applying the modelling framework and its component models to the case-study region, we explored a range of scenarios with a net cost reduction of up to AU$2?260?000 per year.     

A Language for Policy-Level Modelling

Despite a history of successful applications to operational-level problems, the vale of OR/MS modelling techniques as aids in policy/strategy formulation has not been widely demonstrated. In this paper, we suggest that the language of traditional OR/MS model structures is too restrictive to deal with issues typically confronted in policy-making. Differences between operational-level decision-making processes and policy/strategy formulation processes are discussed; alternative model structures are described and classified; and a modelling language for addressing issues of policy and strategy is proposed. The language is presented in set-theoretic terms, and the resulting structure implies that certain model classes accommodate policy-level management needs better than others. Furthermore, policy-level models must serve a role distinct from the prediction and optimization role typically served by operational-level models.     

Evaluating the Effects of Privatizing Electricity

In this text of the 1993 Blackett Memorial Lecture, a critical assessment of the effects of electricity privatization in England and Wales is Undertaken, with a particular emphasis upon understanding the new economic and strategic forces in the market. This leads to some discussion of the type of modelling approaches that can provide insight into these processes. In particular, a key role for business simulation, alongside optimization methods and economic analysis, is identified as a basis for an effective regulatory framework to manage the transition to more efficient market competition. Emphasis is placed upon recognizing the impacts of risk and competition on the decision-making of the new companies in the market, and upon analysing the ‘short-termism’, the ‘dash-for-gas’, the demise of the coal industry, consumer prices and the nuclear issues in these terms.     

Strategic analysis of technology and capacity investments in the liquefied natural gas industry

Energy plays a fundamental role in both manufacturing and services, and natural gas is rapidly becoming a key energy source worldwide. Facilitating this emergence is an expanding network of ocean-going vessels that enable the matching of natural gas supply and demand on a global scale. This is achieved through the transportation of liquefied natural gas (LNG) for eventual regasification at its destination. Until very recently, only one type of technology had been available for transporting and regasifying LNG: Conventional LNG vessels coupled with land based LNG regasification. But it is now possible to transport and regasify LNG onboard special LNG vessels. Companies such as Excelerate Energy and Höegh LNG are currently developing LNG supply chains based on this new technology. Motivated by these developments, we engaged executives at Excelerate Energy to facilitate an investigation of issues related to strategic technology selection, as well as choices around technology configuration and capacity for the incumbent and emerging technologies. The resulting analysis brings to light managerial principles delineating the impact of alternative LNG throughput models on decisions regarding how to deploy each technology option and how to configure and size their capacity. Our findings have additional potential relevance beyond our industry specific analysis.     

Energy policy modelling in developing and industrializing countries

A large number of models have been developed and used for energy policy planning, in a regional, national or international level, in order to cope with the broad variety of issues related to the energy problem. Energy models belong to the class of policy models, which address fuzzy and complex issues involving many non-quantitative factors, such as political issues, behavioural aspects, etc., as well as many uncertainties and lack of rigorous knowledge concerning the structure of the reference system, and the interrelationships of its elements. The role of energy policy models is very important, since they enhance understanding and communication, and they assist the policymakers to review plausible future configurations of relevant decision variables and parameters. In this paper one of the most important areas of energy modelling is investigated, that concerning the interactions between energy and economy in the group of Developing and Industrializing Countries (DIC's). It is pointed out that energy models used in the DIC's must capture the particular features of energy policy in these countries, such as rapid economic development fueled by expensive, depleting and often imported energy resources; dependence on foreign resources such as energy, capital, technology, etc.; management of indigenous resources, social structural changes, rapid population growth, urbanization and industrialization. In order to improve energy models and enhance their contributions in policy analysis, it is proposed that modelling efforts should be directed towards a better understanding of the energy-economy relationships in the DIC's, as well as towards the development of validated data bases.     

Uncertainty in energy-economic modelling of the electrical power sector

The purpose of the present paper is to investigate what significance, if any, inclusion of uncertainties has for the conclusions of the modelling and analysis, i.e., whether the policy recommendations implicit in the results of the analysis depend on the inclusion or not of uncertainties. We do this within the context of a model of the Northern European electricity sector. The paper considers uncertainties about future states of nature. More specifically, we consider the inflow of water into a hydropower production system, where the states of nature are represented by a “dry”, a “normal” and a “wet” year. The problems may be formulated as non-linear optimisation models where the objective function basically consists of the expected value of the sum of consumers', producers', and authorities' surplus. The models take into account that there are losses in the transmission and distribution of electricity, and that the consumers pay an energy tax on their use of electricity. The consumers are divided into two groups, households and industry. Also, complementarity formulations are used, as these are shown to be more adequate for certain aspects, in particular where risk aversion within a liberalised market context is modelled. For each of eight Northern European countries, the basic results of the models are the installation of new production capacities, the production on old and new production capacities, the electricity prices, and the interchange between the countries. The investment in new production capacity is represented by a single value for each country, while the productions differ in that they depend on natural phenomena, which we refer to as the state of nature and represent by stochastic variables. It was found that in this context it was relatively easy to include stochastic elements in the model. Second, complementarity formulations are preferable to optimisation based modelling for some problem types. Third, results of the stochastic model have natural interpretations, also compared to one or several versions of a deterministic model. And fourth, we have seen that the quantitative results, and hence the implied policy recommendations, may differ significantly from those of deterministic models. We therefore conclude that increased attention should be given to the inclusion of stochastic elements into the modelling of energy systems. This revised version was published online in June 2006 with corrections to the Cover Date.     

The Assessment of Diurnal Storage Requirements for Gas Supply Systems

The British Gas Corporation is preparing for substantial capital expenditure to provide additional gas storage capacity, which is required to balance out the within-day variations of demand, Conversion to natural gas, with its higher calorific value, resulted in a substantial increase in the effective volume of gas storage available. This surplus has been eroded by the rapid growth in demand over the decade since conversion, and new investment in storage will be required if current forecasts of growth are correct. The assessment of the storage requirements has therefore become more important, and more sophisticated methods are being developed. In this paper the factors affecting the need for storage are examined, the methods adopted in incorporating these factors into a simulation model are discussed, and the results from the models are presented. Consideration is given to the national policy aspects of the problem and to the interactions between O.R. and other staff within B.G.C. during the development of the project.     

Mathematical modelling for determining economic batch size and optimal number of deliveries for EPQ model with quality assurance

The classic economic production quantity (EPQ) model assumes a continuous inventory-issuing policy for satisfying product demand and a perfect production for all items produced. However, in a real-life vendor–buyer integrated system, a multi-delivery policy is often used in lieu of continuous issuing policy and it is inevitable to generate defective items during a production run. This study addresses these issues by incorporating multiple deliveries of the finished batch, customer's inventory-holding cost and manufacturer's quality assurance cost into an EPQ model with the imperfect reworking of random defective items. Mathematical modelling and analyses are employed. Convexity of the long-run expected cost function is proved by the use of Hessian matrix equations, and the closed-form solutions in terms of the optimal lot size and optimal number of deliveries are obtained. The research results are demonstrated with a numerical example with a discussion on its practical usage.     

The future of pension schemes

This note introduces the papers that follow in this specialissue of the Journal, devoted to modelling pension scheme assetsand liabilities, and arising from a second IMA conference onthe future of pensions schemes, held in March 2003. It outlinesthe key public policy issues that have developed or arisen sincethe first such conference in February 1998, and summarizes incontext the five papers.     

An Experimental Assessment of Coleman's Linear System of Action for Supporting Policy Negotiations

We report on an experimental assessment of the applicability of Coleman's Linear System of Action (LSA) to policy negotiations. In LSA, policy negotiations are modeled as exchange of control over issues. LSA allows one to compute the equilibrium control distribution for a group of decision makers, based on their distributions of preferences for, and control over, the issues at stake. The LSA theory, however, does not address the process of how the decision makers should exchange control over the issues to arrive at the equilibrium control. We test in an experimental setting partial and full LSA-based support vs. no support, for three different social structures among the decision makers engaging in repeated bilateral negotiation rounds. The results of the laboratory experiment indicate that the level of LSA support affects the negotiation process and the efficiency of reaching the equilibrium, while the influence of the decision makers' social structure is less clear. These results suggest that Coleman's LSA concept can be employed to support policy negotiations in a practical setting.     

Optimization of natural gas production by waterflooding

This paper discusses optimization of natural gas production using waterflooding of a gas reservoir. The functions governing the rate of gas withdrawal and the rate of water injection control the operation of the reservoir. These, together with volume and mass balance and the ideal gas law, give a simple system of ordinary differential equations modelling the reservoir. We use several physical and economic definitions of an optimal production rate. Under each definition, we establish the optimal controls. The relation between prices of water and natural gas and the optimal controls is discussed.Work performed under the auspices of the Energy Research and Development Administration.     

Extending a Gas Pipeline Network

This paper describes the use of a mixed-integer programming model for the problem of determining methods of reinforcing and increasing a natural gas pipeline network. The model considers the options of (i) reinforcing pipes, (ii) building new pipes into the network, (iii) setting up of liquid natural gas tanks at certain points on the network, and attempts to find the best policy for satisfying demand levels. Because of the difficulties of solving the resultant mixed-integer problem, the model can only be used for small networks.     

Energy models for decision making

Since the 1973 oil crisis there has been an explosion in energy modelling activities throughout the world. A bewildering array of models have been or are being developed. The models differ in their geographical scope (local, national, regional or global), their technical scope (a process, an industry, an energy source or all energy industries), their timescale (one to one hundred years) and their systems boundaries (energy, economy, society). In addition there are crucial differences in the level of detail modelled, in the way time is structured and in the way in which decisions are included or perhaps excluded from the model.The natural questions to ask are what sort of models are now available; which models are suitable for which purposes; what has been learnt so far; which are the promising directions for future developments? This paper draws on modelling experience both within the National Coal Board and elsewhere to discuss these questions. The paper contains the following sections: energy models and decision making processes; choosing model boundaries; logic and facts, the basis of the model; choice of energy model; links to the economy; future directions. The subject will be of interest to specialist energy modellers and those interested more generally in strategic modelling for government and industry.     

Strategy,performance and operational research

This paper explores the nature of operational research and its interactions with performance measurement and strategy. It is argued that operational research (OR) is well fitted to handle strategic issues as the modelling approach of OR facilitates understanding and learning, and the evaluation of strategies prior to action. The development of problem structuring methods is also a key aid to strategy and policy formulation. OR is also beginning to play a role in performance measurement and there is an opportunity for OR to lead in the improvement of performance measurement systems.     

O.R. and U.K. natural gas depletion strategy

This paper describes two models using operational research techniques to explore alternative strategies for the depletion of U.K. natural gas reserves. The first is a linear programming formulation of the problem of matching annual supply and demand for gas over the indefinite future. The second evaluates the financial implications of the matches produced by the first. The key variables which affect results from the model are discussed as are some of the ways in which results are used. These results have an influence on decisions ranging from detailed peak shaving policy to considerations of national fuel policy and the balance of energy supplies in the U.K. in the longer term.     

The gas analysis modeling system (GAMS)

This paper gives an overview of a large integrated model of the natural gas industry in the United States. The system described has been used to evaluate the impacts of natural gas legislation before the U.S. Congress. Many common operations research tools such as linear programming, dynamic programming and network flow theory are used at various stages in the model.     

Soft modelling in risk communication and management: examples in handling food risk

Our aim in this paper is to explore the use of soft modelling in an integrated risk communication and management process for managing uncertainties and ‘scares’ in the public domain, particularly in the area of food risk and safety. Much has been written in the past 20 years on the issues relating to the management and communication of food risks and safety issues to the public. Most of this research has been based upon post hoc studies of what went wrong—or, occasionally, right. Here we survey those findings briefly, and draw these into a general framework for risk management and communication. By integrating these into a coherent common framework, we believe that public authorities, food producers and industry may develop more effective strategies for managing and communicating risks which, in turn, will enable the public to make more informed decisions on their diet.     

Response to key issues raised in the Post-14 mathematics inquiry

This article is a detailed response to the issues raised by the Post-14 Mathematics Inquiry in the UK. It aims to debate some of the central issues in mathematics teaching in the UK, including recruitment and retention of mathematics teachers, the curriculum content, national assessment, teaching resources (including ICT) and national strategies and policy (including inspection). Throughout, we have tried to base our recommendations on evidence and experience from the many teachers and tutors we work with as well as on our own experience. We have not hesitated to make what could be seen as controversial recommendations, but we believe a fundamental rethink of education policy and practice is needed if mathematics teaching and learning is to improve. We have also considered the impact that a proposed ‘National Centre for Excellence in Mathematics Education’ might have on the situation, although we doubt that it can have a marked long-term impact in the current UK situation.     

Regional development assessment: A structural equation approach

We propose a multivariate statistical framework for regional development assessment based on structural equation modelling with latent variables and show how such methods can be combined with non-parametric classification methods such as cluster analysis to obtain development grouping of territorial units. This approach is advantageous over the current approaches in the literature in that it takes account of distributional issues such as departures from normality in turn enabling application of more powerful inferential techniques; it enables modelling of structural relationships among latent development dimensions and subsequently formal statistical testing of model specification and testing of various hypothesis on the estimated parameters; it allows for complex structure of the factor loadings in the measurement models for the latent variables which can also be formally tested in the confirmatory framework; and enables computation of latent variable scores that take into account structural or causal relationships among latent variables and complex structure of the factor loadings in the measurement models. We apply these methods to regional development classification of Slovenia and Croatia.