Exploration Portfolios Research Articles

Petroleum exploration portfolios generated with different optimization approaches: Lessons for decision-makers

Petroleum explorers recognize the value of portfolio management, but many have not seen it effectively applied in the industry or do not understand how subsurface assessments by geoscientists link to portfolio analysis and decision-making by managers. Here, we constructed a fictitious but realistic inventory of 50 prospects distributed across plays of various maturity and then generated portfolios with rank and cut, efficient frontier and portfolio filtering approaches. Different analysis and optimization techniques have varying degrees of use and success in aligning portfolio selections with specific strategic goals and available drilling budget. Portfolios ranked and cut by mean risked volumes, economic probability of success (PoS) and expected monetary value can deliver good exploration results. However, they are sub-optimal when compared with similar efficient frontier portfolios optimized for expected total recoverable resource volume and its standard deviation. Portfolios ranked and cut by geological PoS values can deliver the greatest geological success rate among all portfolios, but not much resources and monetary value when the low-risk prospects have relatively small success-case volumes. Portfolio filtering helps find suitable alternative portfolios. Better portfolios include prospects from the emerging play setting characterized by greatest geological and economic PoS values and success-case volumes, but exclude high-risk prospects from frontier play settings. The formal portfolio optimization approaches are blind to the fact that companies have to drill high-risk frontier prospects to de-risk plays and provide access to prospects in emerging plays. Portfolio analysis and optimization techniques must be coupled with good understanding of exploration business and long-term strategy to deliver excellent sustainable exploration results.

Diversification and the Value of Exploration Portfolios

Conventional wisdom holds that dependence among geological prospects increases exploration risk. However, dependence also creates the option to truncate exploration if early results are discouraging. We show that the value of this option creates incentives for explorationists to plunge into dependence; i.e., to assemble portfolios of highly correlated exploration prospects. Risk-neutral and risk-averse investors are distinguished not by the plunging phenomenon, but by the threshold level of dependence that triggers such behavior. Aversion to risk does not imply aversion to dependence. Indeed the potential to plunge may be larger for risk-averse investors than for risk-neutral investors.

‘Ductile v. Brittle’ – Alternative structural interpretations for the Niger Delta

Abstract A wealth of subsurface information gathered from over 60 years of hydrocarbon exploration offshore Nigeria provides a reference study area on the interaction between sedimentation, structure and overpressure in a large delta system. The current geological paradigm is that structuration and synkinematic sedimentation is governed by shale mobility from the deeper parts of the delta. This concept is largely the result of interpretations derived from vintage seismic data and insufficient calibration of the deeper parts of the delta. Long-cable seismic data are providing new insights into this interpretation conundrum. A first-order problem, which is of particular interest here, relates to the linkage between the extensional structures updip with the compressional structures downdip. The translational zone between extension and compression is key to unravelling the nature of this link and any associated structural material balance discrepancies. The primary focus of the current paper is to interrogate seismic data and to provide alternative interpretations to the accepted paradigm. Two end-member interpretations of the Niger Delta regional seismic dip lines – referred to here as the ‘ductile model’ and the ‘brittle model’ – are presented. Aside from their internal geometrical dissimilarities, these interpretations suggest fundamentally different kinematic and geomechanical models. The latter may offer a wider scope for deep – largely neglected – hydrocarbon exploration targets. Ultimately, these ideas could provide the conceptual framework that, in conjunction with improved seismic efforts, could lead to rejuvenated exploration portfolios.

Integrate instead of ignoring: Base rate neglect as a common fallacy of petroleum explorers

When petroleum explorers estimate geological probability of success (POS) and success case volumes for their prospects, they commonly suffer from various biases and fallacies that result in poor assessments. Using a data set of 25 exploration wells drilled by Lundin Petroleum on the Norwegian Continental Shelf (NCS) during the 5-yr period from 2011 to 2015, I demonstrate the base rate neglect fallacy in petroleum exploration. Lundin explorers consistently and significantly underestimated the geological POS and overestimated the success case volumes relative to the available base rate information on historical exploration success rates and sizes of previously discovered fields in the NCS area. These findings are consistent with previous studies of exploration track records of the industry and individual companies. Explorers erroneously tend to ignore the base rates likely because they do not see them as relevant to the evaluation of their specific prospects. As a result, exploration portfolios generally fail to deliver on promise. However, base rate neglect fallacy can be mitigated and eliminated. Explorers should make an effort to learn the base rates relevant to their prospects and integrate them with prospect evaluations, and managers should ensure that modeled portfolio outcomes are consistent with relevant base rates.

Portfolio Management in Double Unknown Situations: Technological Platforms and the Role of Cross‐Application Managers

This article investigates portfolio management in double unknown situations. Double unknown refers to a situation in which the level of uncertainty is high and both technology and markets are as yet unknown. This situation can be an opportunity for new discoveries, creation of new performance solutions and giving direction to portfolio structuring. The literature highlights that the double unknown situation is a prerequisite to designing generic technologies that are able to address many existing and emerging markets and create value across a broad range of applications. The purpose of this paper is to investigate the initial phases of generic technology governance and associated portfolio structuring in multi‐project firms. We studied three empirical contexts of portfolio structuring at the European semiconductor provider STMicroelectronics. The results demonstrate that (1) portfolio management for generic technologies is highly transversal and comprises creating both modules to address market complementarities and the core element of a technological system – the platform, and (2) the design of generic technologies requires ‘cross‐application’ managers who are able to supervise the interactions among innovative concepts developed in different business and research groups and who are responsible for structuring and managing technological and marketing exploration portfolios within the organizational structures of a company.

Creating Efficient Portfolios That Match Competing Corporate Strategies

Summary The process of portfolio optimization provides guidance to decision makers on how to manage an asset base given corporate objectives, market conditions, and organizational capability. Many applications in the oil and gas industry are based upon Markowitz's (1952) efficient-portfolio theory. In the standard implementation of this framework, an efficient portfolio is defined as one that yields the highest value given a specific degree of risk. A corporate decision maker will aim, however, to select a portfolio that meets several often-competing objectives (i.e., maximize portfolio value while minimizing capital expenditure). The optimal portfolio choice given one constraint is typically not optimal given one of the competing constraints. This requires the portfolio manager to identify and select those portfolios that best meet all corporate constraints. Deciding which portfolio to develop is often compounded by there being several portfolios having similar economic characteristics. However, these portfolios can generally be differentiated by strategy, which may depend on nonfinancial attributes such as the geographic location of the assets or on geological settings that might require different engineering expertise. In this study, a large set of exploration portfolios and their attributes have been simulated. Through applying a series of simple and transparent filters, a few portfolios can be identified that meet all the corporate constraints. After a shortlist has been created, the portfolios can easily be characterized by strategy, and the tradeoffs between them can be assessed.

Managing the deep and difficult challenges

Deep and difficult is an often-used euphemism for those petroleum objectives that are continuing to grow into an increasingly large fraction of companies’ exploration portfolios, now the easy conventionals are in their twilight years. Based on six years of experience of such plays and prospects in the likes of Libya, Nigeria, Brazil, the Gulf of Mexico and more, the challenges may be categorised in several dimensions: capabilities for definition; operational well execution; and, the success engineering stretch (which refers to the requirement to envisage development engineering in that uncomfortable zone beyond what is currently deliverable with today’s technology). The ability to define the deep and difficult is addressed in two ways, with the aid of example projects from Shell’s portfolio. The sub-salt seismic imaging revolution in the Gulf of Mexico of the past three years has introduced some interesting paradigm challenges regarding velocity manipulation and image integrity (consciously choosing prospects and well locations that are not on the best image). Staff competencies and the organisational behaviours required to accept such paradigm challenges are also discussed. Operational well execution is discussed with respect to examples of well design challenges in some high cost markets and hostile borehole operating environments. It is demonstrated that ensuring objective depths are reached and gathering sufficient data in borehole evaluation programmes are frequently more difficult than planned. It is concluded that to make the deep and difficult genuinely viable parts of your portfolio, mixing the cocktail of aspiration and stretch with equal parts of technology delivery and flawless execution needs to be in the hands of skilled bartenders.

A Bayesian belief network approach for assessing the impact of exploration prospect interdependency: An application to predict gas discoveries in the Netherlands

Prospect interdependencies, if present and positively correlated, result in a higher standard deviation of the portfolio volumetric expectation curve, compared to a portfolio with independent prospects. This wider uncertainty range offers options for companies to increase the expected cumulative net present value (NPV) of the exploration portfolio. To investigate these effects on exploration portfolios, a methodology has been developed for modeling these dependencies spatially and updating them in time as new information is acquired. The methodology integrates Bayesian belief network techniques into a stochastic exploration business process simulator. Applying this methodology to the Netherlands gas portfolio clearly demonstrates an increase in both the range and expected value of NPV of the expected recoverable volume from the exploration portfolio. Proper tuning of the exploration strategy, using an efficient frontier approach, and regular updating of portfolio economic forecasts increase the probability of realizing the upside at minimum risk when compared to independent prospect portfolios. The staged decision strategy and the value of information underlying the gradual increase of expected NPV can also be calculated and visualized through decision tree analysis techniques.

Facilitating Students' Career Development in Psychology Courses: A Portfolio Project

We describe the use of a career exploration portfolio in an Industrial/Organizational psychology course (n = 22) to address students' career needs and to develop academic competencies. Students independently completed a series of assignments outside of class, which led to the construction of a personalized career development portfolio. Evaluations showed that students were significantly more certain about their career directions at the end of the semester than before and felt better able to implement their career choices. We discuss how career exploration portfolios can be used in other psychology courses.

TOWARDS AN EFFICIENT EXPLORATION FRONTIER: CONSTRUCTING A PORTFOLIO OF STRATIGRAPHIC TRAPS IN FLUVIAL-LACUSTRINE SUCCESSIONS, COOPER-EROMANGA BASIN

In the Cooper-Eromanga Basin, the future of exploration lies in identifying an appropriate exploration portfolio consisting of stratigraphic traps in structurally low or flank areas. A variety of stratigraphic trap prospects in the Moorari and Pondrinie 3D seismic survey areas are identified in the Patchawarra, Epsilon, Toolachee and Poolowanna formations. To identify the stratigraphic traps, an integration of sequence stratigraphic concepts applied to non-marine basins and advanced 3D seismic data visualisation was employed. This paper focusses on estimating the chance of geologic success and the probabilistic reserves size for each prospect within its sequence stratigraphic context (lowstand, transgressive or highstand systems tracts). The geologic chance factors for an effective stratigraphic trap include reservoir, top seal, lateral seal and bottom seal within each depositional systems tract, the seal effectiveness of the adjacent depositional systems tracts and the appropriate spatial arrangement of these factors. The confidence values for the existence of geologic chance factors were estimated according to the distributions of the possible reservoir and seal rocks within each genetic-stratigraphic interval and the chance of geologic success of each prospect was calculated. For probabilistic reserves estimation, geologically reasonable ranges were estimated for each parameter employing Monte Carlo simulation to calculate the reserves distribution. When a series of possible exploration portfolios, including single or multiple prospects from the prospect inventory are plotted in terms of the chance of geologic success vs. the mean value of the reserves estimate, an efficient exploration frontier emerges. The portfolio candidates on the efficient exploration frontier were assessed with regard to chance of economic success and expected net present value (ENPV) using a simple cash flow model. The results indicate that appropriate portfolios include multiple prospect exploration especially with lowstand systems tract plays using single or multiple exploration wells. The portfolio construction approach for stratigraphic trap exploration should ultimately be made consistent with conventional play types, to enable an assessment of all exploration opportunities.

Abstract: Reality checks, performance tracking and calibration of exploration portfolios

Abstract: Reality checks, performance tracking and calibration of exploration portfolios

The Use of Risk Analysis and Strategic Classification to Manage Exploration Portfolios: ABSTRACT

ABSTRACT Risk analysis is critical to successfully exploring and developing oil and gas properties in today's turbulent environment. Risk analysis should go beyond deciding whether to drill a well, however; it also should be used to determine a company's strategy. Strategic planning is needed to set the direction of a company, improve profitability, allow the company to divest itself of unprofitable projects, and concentrate resources where they will do the most good. The strategic classification method matches the quality of an oil and gas opportunity with a company's ability to pursue it. Several types of risk are quantified, including technical, economic, environmental, political, and competitive. These are subsequently benchmarked against historical risk and actual well results. Risk factors fall into two categories: those external to the company environment, which cannot be changed; and those internal to the company, which can. Opportunities and threats are external factors that affect a company's ability to make a profit but cannot be controlled. Strengths and weaknesses, which measure a company's internal ability to pursue a project, can be controlled. External and internal criteria are matched to determine the strategic classification of the project. By strategically classifying opportunities, a company can determine whether to strengthen its position, dilute its interest, or withdraw altogether. It can also be used to determine strategy such as concentrating in frontier areas versus more mature areas or increasing or divesting assets. Use of a strategic project classification will ensure that resources, both human and monetary, are used to maximize profitability and in accordance with company goals. End_of_Record - Last_Page 759-------

Projected Outcomes of Exploration Programs Based on Current Program Status and the Impact of Prospects Under Consideration

Projected Outcomes of Exploration Projected Outcomes of Exploration Programs Based on Current Programs Based on Current Program Status and the Impact of Program Status and the Impact of Prospects Under Consideration Prospects Under Consideration 13783 Summary This paper is concerned with projection of the probable outcome of an exploration program at any time on the basis of the status of committed projects, whether or not their outcomes are known, and the characteristics of available prospects. On the basis of the projected outcome at any time, a course of action can be determined that could decrease exposure to loss or could increase expected return. Risk/return characteristics of additional prospects are identified to meet the appropriate objective. Quantification of the probabilities of various outcomes is limited to reasonably simple computations such as the determination of "gambler's ruin" (the probability that the outcome of the program will be a total disaster). While in some cases this may provide insight, more useful information might be obtained, such as the projected probability of meeting a specific objective or the possibility of breaking even with currently committed, available, and expected prospects. Methods are presented to estimate these probabilities. The Appendix describes the mathematics involved in the procedures. Introduction Management of exploration portfolios concerns selection of prospects and allocation of capital. These decisions are constrained by the amount of capital, the level of acceptable risk, and the availability of prospects. The manager is faced with changing conditions during the period of a program. At the beginning, the total budget for the program. At the beginning, the total budget for the program is known, but only a few of the prospects that will program is known, but only a few of the prospects that will be reviewed are available for evaluation. Eventually, the outcomes of earlier projects will be known and their impact on the outcome of the program will be fixed. Toward the end of the program, the level of remaining capital and the outcomes of earlier prospects will dominate selection and allocation. The purpose of this paper is to present a technique that addresses two shortcomings that are sometimes present in current risk-analysis techniques when applied to allocation of capital in an operating budget. Established goals are monitored with units that are comfortable for the manager (assuming that he has a basic understanding of the quantification of uncertainty with assigned probabilities). Goals can be defined in clear, unambiguous terms. The impact of a project under review on the ultimate outcome of the program can be projected. Similarly, projections can be made of the impact of the collection of currently committed projects on that outcome. In other words, "How am I doing" and "what should I do with my remaining uncommitted capital to do better?" A primary difficulty with risk analysis or risk control lies in the interpretation of the quantities that are generated. The understanding of utiles, risk-adjusted dollars, or certainty-equivalent value is obscure at best and incomprehensible at worst. The quantities compared and the decisions reached by these approaches may be valid and consistent, but do not provide a framework for communication, even within a single organization of managers, accountants, financial officers or analysts, geologists, engineers, explorationists, and other professionals. Management of an operating program involves selection of projects (prospects) and allocation of resources to each. projects (prospects) and allocation of resources to each. Risk Control The control of risk is the reduction of the probability of an unpleasant outcome. The unpleasant outcome can take the form of a total loss of money, failure to break even, failure to meet an established goal, etc. Note that the word unpleasant has a subjective connotation. As with all approaches to risk analysis and control, certain parameters must be defined, either implicitly or explicitly, that reflect the risk attitude of the person or group that is exposed to the possibility of the unpleasantness. In this approach, the parameter is a confidence level required to meet specific goals. Unlike other approaches, notably the preference-theory approaches, this subjective parameter preference-theory approaches, this subjective parameter can be changed as external conditions change without introducing any inconsistency with previous work and analysis. Several tools are available (although limited in use) that provide a readily understandable measure of some of the provide a readily understandable measure of some of the factors associated with management and allocation of capital in situations where uncertainty is a major factor. JPT P. 461