Decision Making in Upstream Oil and Gas Industry - An Integrated Approach Mr. Prakash Deore, Fujitsu

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1 SPE Making in Upstream Oil and Gas Industry - An Integrated Approach Mr. Prakash Deore, Fujitsu Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Oil and Gas India Conference and Exhibition held in Mumbai, India, March This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract The research presented in this paper is based on existing decision theory and literature used in the oil and gas industry. The outcomes of the study would provides an evidence that in oil and gas industry there is a strong linkage between the use of integrated decision making approach, informed decisions and hence good process performance. The existing state of decision making in industry is being limited, in terms of both user and its functionality per se. Also it is commonly acknowledged that organizations have not really used as it was predicted at its conception. Allthough, there are initiatives under smart oilfield programs, where organizations are considering integrated approaches of decision making, and that would be the way forward to optimize process time, efforts and cost. The bottleneck for lower attention to integrated approach is that there is no study or experience captured on improved performance metrics or parameters. Some of the recent surveys indicated from different industries, that making use of integrated approach, efficient tools and standard methodologies in decision making process can help individuals and organizations to meet their objectives. Initial part of this study introduces decision making and its standard process flow componants. Subsequent part of the study elaborates existing state of decision making in the industry, and integrated decision making approach to new investment analysis in upstream. Lastly, it ascertains the importance of process, method, tool selection for making an informed decision and further optimization. Introduction With the increasing business complexity in oil and gas industry, making right and informed decisions are becoming vital to improve business and operational performance. In these dynamic situation organizations are curiously looking at improving their responsiveness, agility and reliability using decision support systems and tools. Despite of increasing spending on these tools and technologies related to decision making, analytical tools, people training, organizations were really not able scale up total return on investments. Identification of critical business processes, selection of right process, using efficeint tools and standard execution methodologies were identified as a critical componants of making successful decisions.

2 2 SPE What is Analysis? The decision analysis identifies a collection of methodolical techniques and technologies for assisting individuals and organizations in the performance of difficult inferences and decisions. Probabilistic inference is a natural element of any choice made in the face of uncertainty. No single discipline can lay claim to all advancement made in support of these technologies. Operations research, probability theory, statistics, economics, psychology, artificial intelligence, and other disciplines have contributed valuable ideas now being exploited in various ways by individuals in many governmental, industrial, and military organizations. As the term decision analysis suggests, complex inference and choice of tasks are decomposed into smaller and presumably more manageable elements, some of which are probabilistic and other preferential or value related. The basic strategy employed in the decision analysis is divide and conquer. The presumption is that individuals or groups find it more difficult to make holistic or global judgment required in unrecompensed inferences and decisions than to make specific judgments about identified elements of these tasks. In many cases we may easily suppose that decision makers are quite unaware of The entire ingredient that can be identified in the choices they face. 1 What is Making? making is a process undertaken by an individual or organization. The intent of this process is to improve the future position of the process, operation or organization in terms of one or more criteria. Most organization initiatives defines decision making as one that culminates in an irrevocable allocation of resources to affect some chosen change or the continuance of the DATA BASE MODEL ALGORITH MS DATABASE MANAGEM MODEL BASE MANAGEME Analytics CONCEPT BUILDING OPTIMIZATION Implementation status quo. The most commonly allocated resource is money, but other scarce resources are goods and services, and the time and energy of talented people. Taking a look at a standard and fundamental decision making process considred in the idnsutry, there is a strong co-relation between process, people and technology integration for decision being made. Therefore building an integrated approach towards decision making processes, have been considered as an important aspect for creating a strong decision support system. making in oil and gas industry The oil and gas sector is highly capitalistic oriented industry and investment decisions in the industry are absolutely crucial. Use of standard procedures, tools, and methodologies to determine the broad lines of their strategic orientation are very important from their investment decisions point of view. In so doing, oil companies are using a range of well established concepts and methodological tools [4] 1

3 SPE Before on to consider briefly how operating company should built its decision making process and supporting infrastructure, it is very critical to understand the environment in which the company is operating. The data, business process mapping, people, tools, and internal/external dependenicies. To list key componants of decision making process and supporting structure, it includes: Role of Data Analytics & Probability Function When a decision needs to be taken in regards of any investment or to extend of any upstream oil and gas operation. It is desirable to introduce notions of probability. And drawing up decisions based on probability of event occurrence depends on base data models and analytical algorithms. The decision maker has to contend not only with the uncertainity about the data but also the end result of the decision made. In such scenarios having strong control on database managmente system, models and algorithms plays an important role, allowing decision maker to make an informed decision. For example - The decision-maker not only deals with uncertainity of volume of oil reserves, but also with whether or not hydrocarbons are present at all. Once the preliminary geological and geophysical studies have been completed, the decision to drill is generally taken on the basis of an exploration datasheet. Companies ask geologist to make probabilistic estimates: probability of success and probabilities related to the reserves allowing the net present value to be described as the probability distribution function. The main criterion used to summarise a probabilistic future is the expected value of the net present value, i.e. the wighted average of possible values of the NPV, the weights corrosponding to their probabilities. This is the value to which the average would tend if the company were able to repeat the experience a large number of times. So far we have considered a single decision, sometimes a series of decisions have to be taken. Those could be because of interdependency, where the later decision being a function of the (random) outcomes of earlier ones. The analysis therefore has to take account the subsequent chain of decisions; these are more frequently represented under decision tree. [4] Business Process Mapping The Four Major Steps of Process Mapping: 1. Process identification: Attaining a full understanding of all the steps of a process. 2. Information gathering: Identifying objectives, risks, and key controls in a process. 3. Mapping: Understanding the point of view of individuals in the process and designing actual maps 4. Analysis: Utilizing tools and approaches to make the process run more effectively and efficiently. The first step is process identification. Many upstream companies think they know their processes landscape vendors, equipment s, budget, people, operational processes, manufacturing, sales, accounting, admin services etc. Instead of defining processes based on the company's understanding, they must be defined by the end objective of the process improvements. Once the processes are identified, the second step begins -- information gathering. There is a large volume of information that should be obtained before trying to learn the intricacies of a process. Primary among these is identifying who the true process owners are, what are their inter-dependencies?, what is change impact etc. In order to effectively record and maintain this information, some important database systems should be developed. Two of the most important are the Process Profile Work Sheet, and Work Flow. While Analysis is considered the fourth step, analysis must really occur throughout the review. While defining the processes, the reviewer may determine that objectives are not in line with the processes in place. In gathering information, it may become apparent that measures of success do not correspond to department objectives. These are just some of the examples of ongoing analysis.

4 4 SPE Methods and Frameworks This section represents the a few key decision analysis techniques and concepts that are used in upstream companies for economics analysis and investment appraisal. Quantitative analysis: This is used here to refer to the calculation by analysts of decision-making criteria such as payback, rate of return or discounted profit to investment ratio. Discounted cash flow techniques: Recognition of capital expenditure time frame to first production and of the time value of money means that DCF techniques must be used by upstream companies. Monte Carlo for prospect reserves: Monte Carlo simulation to generate a probabilistic estimate of recoverable reserves. Simulation has been applied to reserve evaluation in the literature for many years and software now exists to make this process relatively simple. EMV via decision tree analysis: The value of calculating an EMV through a decision tree is widely acknowledged in both the industry and decision theory literatures.the decision tree is usually read from left to right, or sometimes from top to bottom. The connecting lines of the graph represent either possible decisions (continuious lines) or random outcomes (broken lines) of the decision taken. The nodes corresponding to decisions are represented by a square (decision points) while the probablistics nodes, associated with random events, are represented by circles. A B Oil Discovery No D E F G Develop A Failure Small Field Medium size field H I Failure L Develop Small field M N Medium size field Unfavorable Favorable Unfavorable Favorable Tools & Applications The concept of improved decision making for economic and operational business processes has become widely accepted in the oil and gas industry. The revolution in information technology has enabled oil companies to churn huge amount of structure and unstructured data to provide strategic insights before making important capital investment decisions. Corporate and operational department of oil companies are able to employ increasingly advance DBMS and BI software solutions to vastly improve the quality control and the speed of the investment decision process. However, the actual use of decision and risk analysis tools remains limited, due mostly to complexity of these tools. Therefore, selection of software or analytical tool has been considered an important aspect of decision making process. Below mentioned areas critical IT specific tools and systems are considered to be backbone of integrated decision making infrastructure. Database Management Systems Business Intelligence Business Process Modeling Process Simulators support systems Totalizers and Visualizers KPI& Dashboards

5 SPE Business Rules & Key Performance Indicators After business/process decision, monitoting effectiveness and performance becomes an important step for optimization. A business rule defines process behavior based on historical trends and end business objectives, which allows identifying anomanlies occurrence in the process and hence process improvement in a continuous manner. Key performanace indicators ensure realibility of supporting process componants and help link business decision strategy to dependent business processes, business role players and business products and services. Conclusion: Based on above discussions it is evident that decision making is not only matter of having right data or right tool, it is the integrated process where all componants has equal weightages The key success factors associated with the decision making in E&P industry requires a focused approach and adoption of best practices. Data, Methodology, Process Modelling, Support System, and flawless implementation and execution methodologies are critical for making informed decisions. References & Sources 1. Encyclopedia Operations Research and Management Science; By Bu Soul & Carl 2. International Petroleum Accounting; By Charlotte J. Wright, Rebecca A 3. Business Process Mapping, John Wiley & Son 4. Project Cost Estimating Principals and Practices, by Jack Sweetin 5. Refining Operations and Management, J P Favennec 6. Oil and Gas Sector Reserves, Cost and Contracts, By Center of Economics and Research France, 7. Oil Company Financial Analysis in Non-Technical Language, By Daniel Johnston 8. Guide to Energy Management, By Barney L. Capehart 9. Journal of Petroleum Technologies, Society of Petroleum Engineers, Archives 10. Journal of Digital Energy 11. Risk, Uncertainty and Investment -Making in the Upstream Oil and Gas Industry, by Fiona Macmillans (University of Aberdeen) 12. Making s in the Oil and Gas Industry, by Ellen Coopersmith Frameworks Houston, Texas, USA; Graham Dean Centrica Slough, Berkshire, England; Jason McVean, Calgary, Alberta, Canada; Erling Storaune, Aker Maritime, Inc. Houston, Texas 13. From Uncertainty Quantification to Making in the Oil and Gas Industry, by J. Eric Bickela,*, Reidar B. Bratvoldb a The University of Texas, Austin, Texas, USA b University of Stavanger, Stavanger, Norway