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Abstract

We have now reviewed all the necessary considerations by which exploration prospects and plays may be objectively measured with respect to potential reserves, chance of commercial or economic success, and range of profitability given success. The remaining tasks concern how the inventories and portfolios of such opportunities may be managed as business ventures, taking into account the financial and human resources of the firm.

introduction

We have now reviewed all the necessary considerations by which exploration prospects and plays may be objectively measured with respect to potential reserves, chance of commercial or economic success, and range of profitability given success. The remaining tasks concern how the inventories and portfolios of such opportunities may be managed as business ventures, taking into account the financial and human resources of the firm.

Dealing with Risk and Risk Aversion

Practical Expressions and Applications

The term “risk” implies the threat of loss. A proposed project becomes a risk venture only when we assign economic consequences—gains and losses—to the various possible outcomes. The fundamental attribute of all risk ventures is that the threat of loss outweighs the prospect of gain—people will take a greater chance to avoid a loss than to make a gain of the same size. This is the essence of utility theory. Except for compulsive gamblers and those who purposefully remain ignorant, the normal human condition is to be risk-averse whenever a proposition involves things that are precious—life, health, money, reputation, human relationships, social status, and so on.

Accordingly, we try to “hedge” our position in such ventures by finding ways to increase our safety, either by giving up some interest in the deal or by delaying our commitment until the probable outcome of the venture is more apparent.

Biases Affecting Risk Decisions

Pioneering work by Tversky and Kahnemann (1974) provided good examples of common biases affecting our everyday judgments about risk ventures. Table 18 outlines seven such biases, all of which tend to cause our evaluations of such ventures to be inconsistent. One of these biases is especially important to understand: the fear of anticipated criticism that may impede individual-enterprise decisiveness. This is just an organizational expression of risk aversion, in which the perceived threat jeopardizes status, position, even one's continued employment. In especially authoritarian companies, such bias may effectively paralyze the organization, thus shifting even the most trivial decisions upward to upper management.

It is important for geotechnical staff, as well as exploration management, to be aware of such biases and to know how to detect and correct for them, as shown in the following section.

Risk-adjusted Value, Risk Tolerance, and Optimum Working interest

The economic parameter risk-adjusted value (RAV) was defined in Chapter 4 (p. 55) and shown to be a modification of the expected value (EV) equation, in which the function that expresses the risk preferences of the decisionmaker is exponential. The relative degree of risk aversion expresses itself as variations in “r”—larger r's indicate an increasing degree of risk aversion.

Calculated values for RAV have been intuitively hard for planners and decisionmakers to deal with because they combine objective economic values with subjective behavioral responses. Subsequent developments made applied utility theory more useful to exploration management:

  1. Walls (1993, personal communication) found that characteristic r's of oil and gas firms approximated 5/(annual exploration budget), rather than 1/(annual exploration budget). In other words, exploration firms actually behaved in a more risk-aversive way than Cozzolino had anticipated (p. 55).

  2. Following Cozzolino (1977 and 1978), Lerche and MacKay (1999) showed a more comprehensible and useful form of r, called risk tolerance (RT) (Equation 7, p. 55).

    Risk tolerance was intuitively easy to grasp as that threshold value whose anticipated loss is unacceptable to the corporation. Pragmatically, RT could be thought of as the investor's choke-point—the value that motivated the investor to find a co-investor with whom to share the risk of loss—even at the prospect of giving up some of the gain.

    The EV concept (p. 54) ignores the pervasive, powerful force we call risk aversion. Table 19 compares two dissimilar projects that happen to have the same EV ($6.0 million) but vastly different front-end costs ($30 million vs. $3 million).

  3. Again, following Cozzolino (1977), Lerche and MacKay (1999) showed that, for every venture, RAV would be maximized at some specific working interest, through a trial-and-error process. They then transformed the RAV equation to allow direct calculation of the optimum working interest (OWI) for any venture, given that the firm's RT is known.

 
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Table 18

Biases affecting risk decisions (modified after Tversky and Kahnemann, 1974).

Type of BiasCommon Example
Framing effectsDecision makers will take a greater gamble to avoid a loss than to make an equal gain.
Existence of a prior accountDecision makers are more inclined to take a risk at the beginning of a project than later in the project's life.
Maintaining a consistent reference frameDecision makers are most likely to invest during a “run” of good fortune, and less likely to invest during a “run” of bad fortune.
Probability of successA venture having a perceived high chance of success is preferred over a second venture having a low chance of success, even though the expected value of the second venture is clearly superior.
Wrong action versus inactionManagers prefer to take a risk by not making a decision, rather than taking action that could result in the same loss.
Number of people making decision Workload and venture sizeGroups are more prone to take risks than individuals. Large-volume ventures are preferred over smaller ones, especially when decision makers are busy.
Personal familiarityThe “comfort bias”-decision makers are more risk-prone in deals or environments with which they have good experience.
Type of BiasCommon Example
Framing effectsDecision makers will take a greater gamble to avoid a loss than to make an equal gain.
Existence of a prior accountDecision makers are more inclined to take a risk at the beginning of a project than later in the project's life.
Maintaining a consistent reference frameDecision makers are most likely to invest during a “run” of good fortune, and less likely to invest during a “run” of bad fortune.
Probability of successA venture having a perceived high chance of success is preferred over a second venture having a low chance of success, even though the expected value of the second venture is clearly superior.
Wrong action versus inactionManagers prefer to take a risk by not making a decision, rather than taking action that could result in the same loss.
Number of people making decision Workload and venture sizeGroups are more prone to take risks than individuals. Large-volume ventures are preferred over smaller ones, especially when decision makers are busy.
Personal familiarityThe “comfort bias”-decision makers are more risk-prone in deals or environments with which they have good experience.
Table 19

EV implies “risk-neutral.”

The power of the OWI calculation is that it allows the most common response to unacceptable risk— reduction of one's share—to be optimized for each venture, consistently throughout the company. That is, the firm can behave consistently in its response to risk propositions, by taking appropriate shares of the diverse ventures in its portfolio. This is particularly important where companies seek to spread risk by participating widely in many joint ventures and thereby broaden their exposure, but they do not have the luxury of assembling a full inventory of opportunities, more than a year in advance, from which to select the optimum combination and share of ventures for the upcoming year's drilling program. Using OWI offers a legitimate alternative for converting the common process that many companies use to determine their share—management's intuition—to a valid and consistent procedure that optimizes value to the firm.

Common Business Conventions for Mitigating Risk

The petroleum exploration business has developed many different procedures and devices for alleviating excessively risky ventures. Basically, all such conventions, as they apply to individual ventures, involve one of three key elements influencing risk ventures:

  1. improve the odds;

  2. reduce the capital at risk; or

  3. alleviate risk through diversification.

improving the Odds

The most common method of improving the odds is to acquire additional geotechnical information such as seismic or geochemical data, either by purchasing or trading data. But other more imaginative methods also are used, such as bottom-hole or dry-hole contributions, which involve the acquisition of additional geo-technical information illuminating your own prospect, by encouraging another operator to drill a well near your leasehold and then share key well data (logs, cores, tests, etc.) that bear on your own prospect, in exchange for some agreed-upon monetary benefit. This benefit is ordinarily paid on reaching the necessary depth and/or if the well proves to be a dry hole. Another way to improve the odds is to contract for terms that allow you to enlarge your interest in the venture in the event it appears to be successful. Receiving a larger share after the venture pays out, or purchasing additional interest at preestablished favorable terms after additional information is available, are common examples.

Reducing the Capital at Risk

There are two main approaches to reducing the front-end costs of any venture. The first method is to obtain especially beneficial terms through effective negotiations, or by leverage, because of an inherent advantage stemming from (1) available funding, (2) favorable leasehold relative to the prospect, or (3) proprietary knowledge, tools, or skills without which the prospect is unattractive.

The second method by which cost can be reduced involves the voluntary surrender of some share of the venture in exchange for a proportional reduction in front-end exposure. Common examples of the second method are provided by conventions such as farm-outs, where the leaseholder exchanges a substantial share of the interest in the leasehold for the commitment of another company to test the acreage by drilling an exploratory well. Companies also carry out joint ventures with other firms, often cross-assigning interests in several deals.

All such conventions are perfectly legitimate methods of mitigating risk, with one important caveat: it is essential that dealmakers understand clearly just how much value they are giving up in exchange for the desired financial safety. Many times the tradeoff is, in fact, inappropriate, and the value surrendered is much greater than the incremental safety warrants. This is especially true where a diversified portfolio provides additional risk protection.

Alleviating Risk through Diversification

Diversification is a well-known concept in the securities investment business, leading to the wide employment of portfolios of common stocks, bonds, precious metals, and other securities. The same principle applies to portfolios of exploration ventures, which are covered later in this chapter.

Common Methods for Acquiring Petroleum Rights

Staged Exploration

Theoretically, the most efficient economic process for petroleum exploration and development is staged, where capital is invested over time in a series of systematic risk decisions, each decision weighing investment level against the risk and reward that are perceived to attend the project at that stage of its evolution (Figure 40).

But pure, staged exploration is rare. In trends where many companies are competing simultaneously for acreage, high front-end payments—caused by competitive leasing or sealed bonus bidding—force firms to make early investments that are commonly larger than pure, staged exploration could justify. Also, companies properly use geotechnology, such as seismic, reservoir studies, and geochemistry, to acquire knowledge bearing directly on the risk-reward question. For reasons of competitive advantage, such geotechnical knowledge is held confidential. Unfortunately, such competitive advantage is fleeting, so companies have learned to act quickly on their confidential findings of geotechnical information. “The secret is, there are almost no secrets—and they don't stay secret very long.”

Figure 40

Staged exploration.

Figure 40

Staged exploration.

In large international contract areas within which the operating company has no competitors, staged exploration is compromised because large signature bonuses and/or work commitments are ordinarily required before the operator can even begin to acquire critical geotechnical data that address the risk-reward questions. Once a large block is acquired, the freedom from competition within the acreage block may induce a certain amount of complacency, thus encouraging delays that reduce exploration efficiency from the optimum. In some cases, however, there may be real benefits in such delays, as suggested by option pricing theory (p. 52). Finally, unique contract terms may distort and impede efficient decision making.

Conditions of Acquisition

Except for most of the U.S. and parts of Canada, minerals are ordinarily owned by the state rather than by private individuals or companies. Rights to explore for and produce such minerals are acquired in at least six different ways, as discussed previously. However, except for some uncommon situations where mineral prospectivity is seen to be quite unpromising or state representatives are in collusion with favored firms, private companies usually compete for mineral rights. Such competition takes many forms, but it ordinarily involves proprietary data and/or interpretations as to (1) resource size, chance of project success, and profitability; (2) terms designed to appeal to the grantor of the license; and (3) some specified timeframe for offers and decisions. In one form or another, companies bid for mineral rights, but the particular method of acquisition itself has substantial impact on the overall profitability of the venture.

Sealed Bonus Bidding

Sealed bonus bidding is common in the U.S. and Canada, as well as in some international theaters such as Venezuela. It is the method that is most detrimental to operators and most advantageous to mineral owners. Sealed bonus bidding has two main drawbacks— the “Winner's Curse,” and the “Ubiquitous Overbid.”

The Winner's Curse

The phenomenon of the Winner's Curse, first recognized and discussed by Capen, Clapp, and Campbell in 1971, has been incorrectly characterized as, “If you won the bid, you paid too much.” A more accurate articulation is, “If you won the bid and the tract turns out to be productive, you probably overestimated the value, expressed as net present value (NPV), and therefore you probably won't make your anticipated return. If the tract turns out to be dry, you probably overestimated expected value and paid too much for it on a risk-reward basis.”

The uncertainty surrounding prospect reserves is the primary cause of the Winner's Curse: given the high variance of the lognormal reserves distribution, and the likelihood of several unintentional overestimates among any group of competitive bidders, it follows that the firm that overestimates by the most is likely to be the highest bidder (Figure 41). Because of the award procedure and competitive secrecy, group wisdom about the tract value doesn't prevail. In fact, the bidder who most exceeds group wisdom usually wins the bid. Moreover, firms can't average-out their estimates with overestimates and underestimates on other tracts because underestimates usually generate bids too low to win tracts!

Figure 41

Sealed bidding for uncertain reserves leads to the winner's curse.

Figure 41

Sealed bidding for uncertain reserves leads to the winner's curse.

What are the effective remedies to counteract the Winner's Curse? Most important is to revise the criterion for success: The goal is not to win the tract; the goal is to add value—to make money. Secondly, limit the bid to some deep discount of the tract expected net present value (ENPV): the more uncertainty, the deeper the discount. Naturally, this presupposes that anticipated competitive bid levels for the particular sale are expected to rise above threshold trend per-acre prices of, say 5-10% of ENPV or anticipated minimum bid levels, as they did in the 1996-98 Gulf of Mexico sales. Third, bid widely: recognizing the large uncertainties inherent in exploration, firms should bid on all blocks perceived to have positive expected value. Fourth, encourage a detached, disciplined bidding attitude, to wit, “If we can't get this tract for our price, we don't want it.” Fifth, as our industry was able to do in 1983, encourage the state to reduce the intensity of competition by offering very many tracts, as the U.S. Minerals Management Service (U.S.M.M.S.) does through area-wide sales. Finally, seek other ways to acquire mineral rights, such as with private treaties and through farm-ins, trades, or acquisitions.

Adoption of the area-wide leasing procedure by the U.S.M.M.S. in 1983 reduced the intensity of competition for Gulf of Mexico leases. Before 1983, competing companies like Shell, Arco, and Chevron were using deep bid discounts and bidding widely (Figure 42). They were bidding efficiently—acquiring their acreage for fewer dollars than others like Exxon, Mobil, Gulf, Tenneco, and Texaco, who were concentrating their bids and paying top dollar.

After area-wide sales began, overall bid prices dropped to 12.5% of their former level.12 Some companies, such as Shell, Chevron, and Amoco, continued to bid efficiently and kept acquiring offshore acreage for proportionately fewer dollars (Figure 43). Others, such as Exxon, Texaco, and Mobil, had apparently learned from their prior bidding experience and switched to efficient bidding. On the other hand, a few firms, notably Arco/Vastar and Unocal, apparently lost their corporate memories and now became inefficient bidders. Some latecomers, such as Kerr-McGee and Amerada, bid very aggressively but inefficiently.

The Ubiquitous Overbid

The second operative drawback of sealed bonus bidding is the Ubiquitous Overbid of Megill and Wightman (1984), defined simply as “the money left on the table”—the difference between the winning bids and the second bids, as a percentage of the winning bids. From the company's point of view, the overbid represents a totally wasted investment.

Figure 42

Net purchases by company: Gulf of Mexico sales, 1972-82 (figure courtesy of Robert Clapp). Compare with Figure 43.

Figure 42

Net purchases by company: Gulf of Mexico sales, 1972-82 (figure courtesy of Robert Clapp). Compare with Figure 43.

Figure 43

Gulf of Mexico bidding efficiency (1988-95). Compare with Figure 42.

Figure 43

Gulf of Mexico bidding efficiency (1988-95). Compare with Figure 42.

Figure 44

High bids and second bids; GOM lease overbids averaged about 50% pre-1983 (from Megill, 1984).

Figure 44

High bids and second bids; GOM lease overbids averaged about 50% pre-1983 (from Megill, 1984).

Figure 45

High bids and second bids; area-wide GOM lease overbids averaged 75% post-1983.

Figure 45

High bids and second bids; area-wide GOM lease overbids averaged 75% post-1983.

Although counterintuitive, the fact is that with less competition the average percentage overbid tended to increase, from about 50% pre-1983 (Figure 44) to about 75% post-1983 (Figure 45). When we deal only with multiple-bid tracts, the percentage overbid becomes smaller—45% pre-1983 and 57% post-1983. Now, overbids are characteristically large, simply because bids—based mostly on reserves potential—are log-normally distributed, hence the difference between the first and second bid is generally large, compared with, say, the fifth and sixth bids, because of the log scale. As Megill and Wightman pointed out, prospectors and their managers must understand that the overbid is intrinsic to the sealed bid process. Overbidding is part of the mathematics and can't be eliminated.

It is instructive to compare levels of overbidding before and after the adoption of area-wide sales: Figure 44 was made by Bob Megill in 1983 and shows that the average overbid before area-wide sales was about 50%, whereas Figure 45 (Rose, 1999) shows that the average overbid rose afterward to around 75%. However, since the entire bidding level had been so greatly reduced, as it was starting in 1983, the pain of the increased overbid could be accommodated more easily.

Summary

Thus sealed bonus bidding has these two main drawbacks: the Winner's Curse and the Ubiquitous Overbid. However, their negative effects can be ameliorated by substantially discounting the tract's expected value to determine appropriate bid levels, and by reducing the intensity of competition on individual tracts so the net impact is economically tolerable. Nevertheless, even after area-wide sales began, the key to success in bonus bidding remains to persuade executives that their intuition cannot beat the effects of the Winner's Curse and the Ubiquitous Overbid.

The actual effect of the Winner's Curse and overbidding on the overall profitability of U.S. oil companies operating in the Gulf of Mexico is chilling—Lohrenz (1988) reported that the total industry investment in the Gulf had not yet paid out and likely would not ever achieve actual profitability. Furthermore, if area-wide bidding had not been adopted, it is quite possible that the economic development of deep-water discoveries in the Gulf of Mexico during the late 1980s and 1990s would never have been possible.

Serial, Time-constrained Auctions

The second common method for acquiring petroleum rights is the serial, time-constrained confidential auction, in which a deal is shown individually and privately to several potential buyers over a short period, with an announced deadline in the near future. Such deals function like sealed-bid sales, with the same drawbacks to purchasers and advantages to the deal seller. Whichever potential buyer values the deal the most is likely to submit the best offer, and confidentiality discourages the outside input that might indicate overestimation. Near-term deadlines promote similarity to sealed bonus bidding. However, if the deal seller sells a fractional share, a limit is thus set on the upside potential, and the inherent advantages of competitive confidential bidding have been eliminated.

Oral Auctions

The third common method is the oral auction, which is still used by some U.S. states and onshore federal lease sales, and in privately managed sales of producing properties. Theoretically this method should be more attractive to deal buyers because there is no need for more than a fractional difference between the high bid and the second bid, thus eliminating the overbid and the inherent waste associated with it. However, competitive egos often seem to produce the same effect as the Winner's Curse, generating bids that indicate greatly overvalued tracts. So success in oral auctions requires disciplined bidding, as well as the recognition that the behavior of other bidders may provide useful on-site information about your own valuation of the tract— whether it may be too high or too low.

Performance Contracts

Performance bidding (or so-called work-contracts) should eliminate both the Winner's Curse and the Ubiquitous Overbid because, theoretically, operators should limit their bids to whatever a prudent explorer would spend to explore any given block, based on tract size, geology, and geophysics, not on perceived reserves potential. This sounds good in principle; in practice, however, the competitive desire to obtain the block often translates into extra wells or better terms. Such measures are not necessarily bad, as long as decisionmakers recognize that the Winner's Curse is operating on all such overages and extras. Obviously, the worst of both worlds is represented by acquisition procedures combining performance bidding as well as competitive sealed bonus bidding.

Private Treaties

The best method for the deal buyer to acquire petroleum rights is through private treaties or simple bilateral negotiations, where a given deal is shown to only one buyer at a time and multiple buyers are never looking at the same deal simultaneously. This is the method traditionally employed in conventional onshore U.S. exploration. It is best for the deal buyer because it avoids the Winner's Curse as well as the Ubiquitous Overbid, and it's worst for the seller for the same reasons. Such deals may approach staged exploration if the deal involves a new concept or tool and competition is as yet minimal. Such situations, however, don't last long.

Corporate Acquisitions

Our final method for acquiring petroleum rights is through corporate acquisitions—buying another company's reserves by buying the company. Friendly takeovers function like private treaties, generally being most favorable to the buyers. Unfriendly takeovers that lead to bidding wars function more like sealed-bid sales—the more bidders, the more favorable to the company being bought. However, the impact of the Winner's Curse may be relatively less because there is generally less variance surrounding a company's true worth than there is around an offshore exploration block.

Sanctity of Contracts versus Subsequent Renegotiations

All of the observations and comments have assumed the sanctity of contracts—“a deal's a deal.” If it's possible to renegotiate a deal later, after disappointing results have been confirmed, then all bets are off and advantages and disadvantages of the previous six methods are obviated. This by itself may suggest a seventh method of acquiring rights through subsequent renegotiations. Such methods are anathema to most Western corporations, perhaps because when such subsequent renegotiations took place in the past they represented violations of existing contracts. However, perhaps this is a limiting Western cultural value—suppose we approach international exploration, from the start, as an uncertain business that should logically be carried out through agreements that expressly allow for changes in terms, depending on what the results of exploration turn out to be?

This may represent the last, best way to improve exploration profitability—to develop new, flexible types of contracts that allow us to approach the effi-ciency of staged exploration. Of course, such contracts presuppose that an informed landowner or state must be able to verify the legitimacy of the critical geotech-nical expenditures and findings that impact the changing risk-versus-reward picture, and thus, the changing terms. Some aspects of production-sharing contracts contain such flexibilities.

Conclusion

Small companies or independent operators especially should realize that the method of sale itself plays a big part in the profitability of the purchase or sale. Stated simply, when you're selling, try to utilize the sealed bid or auction model. When you're buying, buy through private treaty or performance bidding.

Prospect and Play Portfolios

Requirements

A prospect portfolio (Rose, 1992a) is selected from an inventory of exploratory prospects. The portfolio listing displays their respective costs, chances of commercial success, estimated mean reserves and mean NPVs, risked mean reserves and risked NPVs (the latter are derived by multiplying estimated mean reserves and NPVs each by chance of commercial success), and preferred economic ranking measures such as ENPV and risked investment efficiency.

Each of the prospects in the inventory may be effectively compared and ranked with the other prospects because the same processes for estimating reserves, chance of success, and profitability have been used for all. Consistent corporate hurdles and discount rates have been applied to each prospect, and meaningful economic measures have been consistently used to rank the various ventures in the inventory. So the inventory represents those prospects that the firm is considering; the portfolio represents the exploratory wells that will actually be drilled.

Inventories become another selective screen in choosing prospects for the company's annual or semiannual exploration portfolio, but only if the various candidate ventures considered for entry can be evaluated quickly and efficiently, both geotechnically as well as economically.

Similarly, a portfolio of exploration plays may be selected from an inventory of candidate exploration plays. Ordinarily, however, play inventories and portfolios are considerably smaller than prospect inventories and portfolios; moreover, prospects and plays are segregated into separate inventories and portfolios. Because of their inherent differences in scope and time-frame, plays and prospects should not be included and compared in the same inventory. It is far better to maintain two separate inventories, one for plays and another for prospects.

Benefits

If these conditions are met, the assembly of a prospect or play portfolio from an inventory of qualifying prospects or plays can significantly improve corporate exploration performance, for at least six reasons:

Optimizing Capital Allocation

If the selected portfolio contains those projects that rank highest, using risked investment efficiency (see p. 54), it will produce the highest possible capacity to cre-ate value for the firm. A ranking based on ENPV will produce a portfolio having the highest ENPV, but because investment costs may vary among ventures, that ranking may ignore venture risk; at the same time it may not maximize value. Any economic measure that includes a provision for risk aversion, such as calculation of OWI, will necessarily reflect value reduced from optimum, in consideration of the reduced vulnerability to loss.

Forecasting Performance

Prospect portfolios (Table 20) are one of the most effective tools to improve exploration performance. Objective professional estimates of an individual prospect's chance of commercial success, in combination with reliable forecasts of mean reserves (and thus prospect mean ENPV), provide the basis for predicting the following:

  1. approximate number of discoveries from a given multi-well program;

  2. approximate total new commercial reserves added (p. 33) and their present value; and

  3. approximate program cost-of-finding, using project cost forecasts.

Naturally, the accuracy of such program forecasts is keenly sensitive to (1) average prospect discovery probability; (2) variance in individual prospect-reserves distributions; (3) the predictive skill and lack of bias of the geoscientists; and (4) the number of prospects in the inventory. Accordingly, the predictive ability of the play portfolio is much inferior to prospect portfolios. However, play inventories are quite useful because they facilitate the comparison of different exploration plays.

Guiding Geotechnology

Provisional risk analysis may be carried out on emerging prospects and plays before they are ready for drilling to identify those ventures that seem to have the greatest economic promise. To maximize cost-effective use of geoscientists and their tools, specific exploration technologies should then be focused on the highest-ranked anomalies, leads, and trends, and especially on the critical geologic chance factors (see p. 38).

Assessing Predictive Performance

In order to construct an inventory (from which are selected the best ventures for the company's drilling portfolio), estimates of reserves, chance of success, critical risk, initial production rates, percentage declines, and drilling and completion costs must already have been estimated for each venture. Thus half the task of geotechnical performance evaluation has already been carried out—and preserved! After the results of each venture are known—successful or unsuccessful—the actual results can be assembled by the exploration team from drilling and completion reports and postdrill reviews and compared with the predictions. So the inventory/portfolio process helps promote systematic performance review. This approach is not as readily applied to play analysis, however, simply because of the long time elapsed between forecasts and discernible results common to play development.

Eliminating Predictive Bias

Motivational bias expressing overly optimistic or overly conservative estimates of reserves, chance, and profitability, can, with a reasonable number of trials (wells), be detected, analyzed, and corrected through feedback and subsequently modified procedures by geotechnical staff. By reducing such bias we can improve portfolio performance and create added value for the company.

Scheduling Future Work

The selected portfolio forms the basis for planning and scheduling the work necessary to carry out the constituent ventures over the period of the portfolio.

Lognormality and Performance of Prospect Portfolios

Most knowledgeable explorationists and many of their managers now accept the principle that prospect-reserves distributions are lognormal, reflecting natural processes of multiplication [area (acres) χ average net pay (feet) × HC-recovery (bbl/acre-foot)]. Accordingly the distribution of most corporate balanced portfolios is also approximately lognormal.

What is remarkable is that many corporate officers and high-level exploration managers have not grasped the implications of this principle as it impacts the magnitudes and timeframes of corporate exploration results. In particular they do not seem to understand the expected natural pattern of annual portfolio outcomes: predominantly mediocre annual results punctuated occasionally by exceptionally good years and bad years. It can be demonstrated that such fluctuations may have nothing whatsoever to do with geo-technical or managerial skill; rather, they may be the natural consequence of repeated sampling from natural lognormal prospect-reserves distributions.

A common manifestation of management's misunderstanding of the lognormal principle is their continual and excessive reorganization of ongoing exploration programs, in the well-intentioned but mistaken belief that such adjustment and interference (= “tweaking”) will improve year-to-year exploration results. But exploration is inherently a sustained, long-term process plagued in most corporations by short-term interferences. There are indeed effective criteria by which exploration performance can be judged, to distinguish luck from skill; however, prediction of annual discovery volumes is not an effective criterion unless the exploration portfolio contains 60 to 100 or more trials. Accordingly, assessing exploration performance based on annual portfolios may require 1-5+ years, depending on the size and aggressiveness of the firm and the number and character of ventures in the annual portfolio.

Table 20

A model prospect portfolio (prospects are ranked in this list by ENPV).

Reserves (MMBOE) If SuccessfulEconomic Measures For Ranking
ProspectDry-Hole Costs ($MM)Chance Of SuccessP10%/P90%MeanP90%/P10%Mean NPV ($MM)Risked Mean Reserves (MMBOE)Investment ($MM)OWIENPV ($MM)Investment EfficiencyRAV
A6.20.055.050.0112.5275.02.515.00.037.867.86/15.0 =0.520.103
B5.40.102.424.054.0120.02.48.80.077.147.14/8.8 =0.810.224
C3.20.202.28.016.032.01.66.00.263.843.84/6.0 =0.640.445
D4.00.151.010.022.545.01.57.20.143.353.35/7.2 =0.470.214
E1.80.150.66.013.524.00.93.30.332.072.07/3.3 =0.630.305
F2.00.201.14.09.014.00.82.00.351.201.20/2.0 =0.600.197
G0.80.250.32.04.46.00.51.81.000.900.90/1.8 =0.500.516
H1.50.200.53.06.69.00.66.10.390.600.60/6.1 =0.100.111
I0.50.300.21.02.22.50.30.81.000.400.40/0.8 =0.500.309
J0.40.400.10.51.01.00.21.01.000.160.16/1.0 =0.160.137
N = 1025.802.00108.5528.511.352.04.57 = .4627.52IE program =0.532.56
Avg.=.2Avg.=.46
Reserves (MMBOE) If SuccessfulEconomic Measures For Ranking
ProspectDry-Hole Costs ($MM)Chance Of SuccessP10%/P90%MeanP90%/P10%Mean NPV ($MM)Risked Mean Reserves (MMBOE)Investment ($MM)OWIENPV ($MM)Investment EfficiencyRAV
A6.20.055.050.0112.5275.02.515.00.037.867.86/15.0 =0.520.103
B5.40.102.424.054.0120.02.48.80.077.147.14/8.8 =0.810.224
C3.20.202.28.016.032.01.66.00.263.843.84/6.0 =0.640.445
D4.00.151.010.022.545.01.57.20.143.353.35/7.2 =0.470.214
E1.80.150.66.013.524.00.93.30.332.072.07/3.3 =0.630.305
F2.00.201.14.09.014.00.82.00.351.201.20/2.0 =0.600.197
G0.80.250.32.04.46.00.51.81.000.900.90/1.8 =0.500.516
H1.50.200.53.06.69.00.66.10.390.600.60/6.1 =0.100.111
I0.50.300.21.02.22.50.30.81.000.400.40/0.8 =0.500.309
J0.40.400.10.51.01.00.21.01.000.160.16/1.0 =0.160.137
N = 1025.802.00108.5528.511.352.04.57 = .4627.52IE program =0.532.56
Avg.=.2Avg.=.46

NOTES:

  1. Dry-hole cost includes exploratory drilling & completion, land, G&G, and overhead.

  2. Firm's r=5/50MM=.1.

  3. Firm's RT=1/r=1/.1=10.

  4. Order of prospects changes if ranked on investment efficiency (IE) or RAV.

ANTICIPATED RESULTS: This portfolio of 10 exploratory wells is a balanced program including three lower-risk extension wells (G, I, & J), five medium-risk trend wildcats (C, D, E, F, & H), and two high-risk new-field wildcats (A & B). The most probable outcome of this program is: two discoveries, totaling 11.3 MMBOE reserves, having a total mean program expected value of $27.52MM. Cost of finding should be about 25.8/11.3 = $2.30/BOE. Program EPV/lnvestment = 27.52/52 = 0.53.

Table 21

Simulation of results for a prospect portfolio.

Predictability versus Portfolio Size

Assuming that the staff's estimates of prospect reserves and chance of success are geotechnically responsible and unbiased (utilizing the estimating concepts and procedures described previously), the number of prospects in the portfolio influences the precision and reliability of forecasts about portfolio results. The average chance of prospect success and the prospect-reserves variance also influence portfolio predictability.

But understandably, management commonly wants to know how many wells are required to make useful forecasts of portfolio outcomes. However, in providing a proper answer, management must be asked, What level of confidence do you require?—50%? 68%? 80%? 90%? 95%? or 99%?

A useful answer can be provided in at least two different forms:

  1. A range of new reserves or NPV added, such as “80% confidence in new reserves of 3.5 to 18.5 million BOE (barrels oil equivalent)”; or

  2. 50% confidence (or some other probabilistic confidence level) that “at least 8 million BOE or $25MM NPV will result.”

Figure 46

Spinner for simulating chance of success and reserves discovered.

Figure 46

Spinner for simulating chance of success and reserves discovered.

Table 21 represents a model 20-well exploratory portfolio for a domestic U.S. firm. Prospect discovery probabilities are 10%, 20%, 30%, 40%, and 50% (four prospects in each chance class), with a portfolio average chance of success of 30%; all chance categories are represented by a mechanical spinner (Figure 46). All prospect-reserves distributions are lognormal, with estimated prospect mean reserves of 11.5 MM bbl and an 80% range (P90%-P10% estimates) of 3.0 MM bbl to 22.6 MM bbl. Median (P50%) is 8.8 MMBOE.

All prospects have P10%/P90% ratios of 13, as established by the outer multiplier ring on the spinner (Figure 46). This represents a minor inconsistency because variance typically increases among high-risk, large-potential prospects. To operate this simulation, each prospect is first tried for success or failure, using the graduated inner ring. If a prospect is a discovery, the next spin determines the amount of new reserves found (outer ring). If the prospect is a dry hole, the next spin determines success or failure on the next well. Obviously, employing a spinner is a visually satisfying alternative to a computer-driven Monte Carlo simulation, which may not be understood.

Figure 47 shows that as such a portfolio increases from 20 wells to 100 wells, the confidence in forecast results improves, the P10%-P90% range becoming relatively narrower with respect to the mean.

Practically speaking, as many as 80 trials (four successive Table 21 portfolios) may be required to provide 80% predictive confidence in new discovered reserves volumes equal to ±50% of the predicted mean of 4 χ 11.5 = 46 MMBOE, if that is the level of confidence management desires. If a more conservative portfolio were selected, one in which the wells had lower-variance reserves and higher chances of success, perhaps as few as 40 wells would be enough to deliver an equivalent level of predictive confidence. At the other end of the scale, for a company involved in high-risk (Pc = 10%), large-reserve (100 to 500 MMBOE), high-variance prospects, an inventory of 250 wells or more might be required to provide adequate confidence in the forecast outcomes (Schuyler, 1989).

Figure 47

Predictive accuracy of portfolio performance improves with the number of wells in the portfolio.

Figure 47

Predictive accuracy of portfolio performance improves with the number of wells in the portfolio.

If the portfolio's size is inadequate to deliver the confidence in forecast outcomes that management expects, at least six possible solutions exist:

  1. Add more wells to the portfolio (which of course will increase exploration expenditures proportionately);

  2. Expand the portfolio by drilling more joint-venture wells (this increases sample size without significant increase in total exploration expenditures);

  3. Consider the portfolio over a multi-year period, i.e., the forecast might cover a 3-year or 5-year prediction with running averages;

  4. Modify the character of the portfolio by including more low-risk wells at the expense of some high-risk wells (of course this usually also entails substantial reductions in reserves potential);

  5. Focus geotechnical exploration tools on high-risk prospects, to either:

    • improve confidence in critical risk geologic factors and raise Pc; or

    • condemn such prospects in favor of other, more attractive ventures; or

  6. Management may revise its expectations for the level of confidence required in portfolio forecasts, i.e., they may accept a more realistic, increased level of risk consistent with real exploration variance.

The key point for management to realize is that any portfolio can be routinely analyzed by Monte Carlo simulation to provide various confidence levels associated with corresponding reserves outcomes. Then management can decide how the portfolio should be adjusted to provide the predictive confidence they require. Obviously, if prospect parameters are biased, the portfolio will lose much of its effectiveness.

For companies operating in a variety of exploration theaters, especially those desiring a diversified, balanced portfolio, it is important to recognize that divisions operating in mature provinces may be expected to provide prospects for the smaller-reserve, low-risk end of the overall portfolio, whereas divisions exploring in frontier basins may provide ventures for the high-potential, higher-risk part.

Principles of Exploration Portfolio Management

It is far beyond the scope of this book to review the principles of modern portfolio management (Bern-stein, 1996; Markowitz, 1952). The key point here for both explorationists and their managers to realize, however, is that the same principles of risk-reward optimization apply to an exploration portfolio that apply to portfolios of various common stocks and to other financial ventures.

Figure 48

The efficient frontier.

Figure 48

The efficient frontier.

Exploration management can be provided with a risk-reward diagram showing many possible portfolios in which the mix of constituent prospects is varied (Figure 48). The horizontal axis expresses risk, usually as the variance or standard deviation of each possible portfolio combination, or more pragmatically, as the chance of some unacceptably low program outcome. The vertical axis expresses reward, usually as the expected mean reserves added (or equivalent NPV). Management can then select the portfolio that best balances their need for value addition with their need to minimize risk.

For example, combination A would represent a portfolio that maximizes ENPV but also represents an unacceptably high level of risk. Combination B would minimize risk but would also reduce ENPV to only about one-third the ENPV of combination A, which also might be unacceptable. Combination C might be a choice that maximizes value consistent with acceptable risk. However, portfolio combinations such as D or E should never be chosen; instead, selected portfolios should always lie along the “efficient frontier” whose value is maximized consistently with acceptable risk.

However, it is essential for both exploration management as well as the professional geotechnical staff to realize that a portfolio selected exclusively to maximize value added (one using prospect risked investment efficiency) may be associated with risks unacceptable to management. Such a portfolio may need to be modified in favor of another mix of prospects that provides the desired safety and accepts the accompanying reduced value.

Problems with Exploration Portfolios

Most modern oil companies try to construct and maintain prospect portfolios. Nevertheless, characteristic difficulties must be addressed.

Obligatory Wells

Prospect selection for portfolio optimization is the guiding principle in inventory and portfolio management, and this requires ranking, selecting, and rejecting individual ventures. However, many exploration contracts require that certain wells be drilled regardless of how those wells compare with other prospects in the portfolio.

Most firms include such wells in the portfolio for purposes of forecasting portfolio performance and for assessing staff performance in making geotechnical predictions. If they include such obligatory wells in the ranking process, it is only for purposes of general comparison and to allow them to drill the better obligatory wells earlier rather than later. Skillful employment of play-analysis principles and proper sequencing of exploration tasks will greatly reduce the number of obligatory wells that rank low in the inventory rank order.

Maintaining Geotechnical Consistency

In order for the portfolio to function properly, the geotechnical staff must be confident that the ranking of prospects from all divisions and theaters is equi-table and consistent, because they correctly recognize that such a portfolio system causes competition for corporate capital. Such equity can be ensured by various means:

  1. use of a consistent, geotechnically valid evaluation process and software, by all groups in the firm;

  2. annual comparison of predictions versus results, to reveal any groups that consistently demonstrate bias in their prospect forecasts, and whose geotechnical performance therefore needs improvement;

  3. deployment of a risk-normalization team of respected senior professionals (geologist, geo-physicist, engineer, economist) that reviews all new major prospects and randomly reviews smaller ones;

  4. annual exploration conference where each group presents one or two prospects to peer groups from all other units, thus demonstrating a broad application of consistent standards and procedures; and

  5. management that demonstrates its commitment to the process by rewarding professional accu-racy and integrity of predictions.

Static versus Dynamic Portfolios

All companies would like to have the luxury of selecting their annual exploration portfolio from an inventory of identified, drillable prospects. Such a portfolio would allow them to maximize risk, in part through the discriminating determination of venture shares. As previously discussed, however, portfolios tend to be dynamic rather than static, and prospects are commonly drilled as they are identified. In order to achieve the benefits of portfolio management, companies may identify several classes of exploratory prospects they wish to include, and then try to secure such a model portfolio as the year unfolds. The result is to diminish some of the theoretical advantage of portfolio selection. Another aspect of dynamic portfolios is to preselect preferred participation levels in cer-tain classes of prospects, or to employ OWI to indicate the appropriate share for the company (pp. 55 and 92).

Table 22

Uncertainty leads to common underperformance of exploration portfolios (after Horner, 1990).

Timing Considerations

A second possible goal of portfolio management has to do with optimizing timing of cash flows. Ideally, projects should be timed so that excess cash from production revenues will be available when large development projects are expected to begin, and large-scale exploration projects are available when the company has cash flows to use in increasing asset value. Such timing may require precision beyond our present levels of geotechnical and predictive skill, however, and some companies endorse a simpler procedure: rank the portfolio to maximize value, then if money is needed for development, it can be borrowed or derived by selling existing, less profitable properties.

An alternative approach to the dual corporate needs of (1) cash flow and (2) growth could be to set up two noncompeting portfolios, one composed of low-risk ventures that could generate needed cash flows near-term; and the second, composed of higher-risk, large-potential projects that could provide growth. Then the question is, What is the appropriate relative level of funding for the two portfolios?

“Theory of Inevitable Disappointment”

Identification of this fascinating phenomenon is ascribed to Dr. Dennis Horner of Royal Dutch Shell. He recognized that companies assemble portfolios of drilling prospects on the basis of some form of predicted economic ranking, such as investment efficiency (IE), ENPV, or even discounted cash-flow rate of return (DCFROR), and he realized that actual performances of the individual constituent ventures would vary, both up and down, from predicted mean performance because of the substantial uncertainty that attends exploration ventures (Horner, 1990). That is, some estimates would turn out to be too high and some would be too low. To model what may actually happen in nature if estimators are unbiased, he constructed a table comparing estimated rates-of-return (ROR) with actual rates-of-return for a portfolio in which the economic cutoff was 15% ROR (Table 22).

As Horner pointed out, the portfolio cutoff (vertical line) must be made under conditions of uncertainty, where prospects estimated as less than 15% ROR are excluded. Because predictions vary from actual results, however, some included ventures will inevitably underperform expectations, and some excluded ventures would have outperformed expectations. Thus the vertical cutoff is wrong, but inevitable, whereas the horizontal cutoff is correct but unattainable. So those ventures shown in bold type in the northeast and southwest quadrants of the diagram will be incorrectly dealt with. The consequence is that the actual performance of the original portfolio will inevitably be lower than the estimated performance— even if estimates are unbiased. The prevalent tendency of explorationists to overestimate prospect reserves (optimistic bias) has the effect of aggravating this problem.

Although Horner indicated this to be a problem without a practical solution, there may be at least a partial solution that can be described as the “pilot-fish” concept (pilot-fish are small fish that accompany sharks, deriving their living off the crumbs and morsels not swallowed by the shark during feeding). If large companies can identify small exploitation firms that may be willing to develop small or marginal fields, and can prenegotiate basic deal structures with them, then a discovery that is recognized to be below standard may be promptly conveyed to the smaller, more efficient firm. Such business practices allow the large company to avoid the development cost of a marginally profitable field, and may allow it to recover some incremental cost as a transfer payment from the small firm.

Managing Exploration Plays

Matching Play Attributes to Business Strategies

Successful exploration is the lifeblood of the international oil and gas business. New fields must be found on a regular basis in order to replace the firm's steadily depleting producing fields. But petroleum accumulations usually occur in geologically related families, which we call plays, and modern petroleum exploration is characteristically carried out at play scale rather than prospect-scale. Accordingly, the critical exploration business decision concerns which new play to enter, not which prospect to drill. It follows, therefore, that any dedicated modern oil and gas company should have a strategy and process under which it systematically and continuously identifies and evaluates candidate new plays.

Business Consequences of Play Choices

Competent exploration play analysis and play selection involve not only the synthesis of petroleum geo-science, statistics, and economics but also require consideration of (1) present and future business conditions (local and international), and (2) business patterns and requirements that are unique to the firm.

It is clear that successful development of new exploration plays generates a steady supply of new and attractive prospects, which in turn lead to the successive discoveries of profitable oil and gas fields to sustain and even increase the company's reserve base. But there are consequences of participating in a bad play:

  1. poor return on invested time, staff, and capital (often an actual loss of capital);

  2. the company may miss out on good profits from an alternative play in which it did not participate; and

  3. competitors benefit from a successful play in your company's absence.

For unsuccessful plays, there are two polar end-members: every company should fervently wish that play failure will occur quickly and unambiguously, leaving geoscientists and management content that a promising idea has been evaluated and disproved efficiently and relatively cheaply. The alternative negative outcome is correctly dreaded—the play that was poorly chosen and improperly negotiated, requiring unnecessarily long and expensive efforts and with tantalizing but ultimately fruitless results.

Negative Impact Is Inversely Proportional to Firm Size

Generally, the negative impacts of a bad play choice are inversely proportional to company size. To very large firms like Exxon-Mobil, Shell, or BP/Amoco, which evaluate dozens of new plays each year and enter perhaps five or ten, a bad play can be shrugged off and balanced against other successful plays, which are expected to carry the cost of unsuccessful ventures so that the overall annual new-play portfolio creates substantial new value.

To intermediate-sized firms, which may evaluate five to ten new plays each year and enter perhaps one or two, a bad play choice usually causes a long-lasting reduction in the company's annual production stream and puts more pressure on the organization to find and enter successful plays or even to purchase existing pro-ducing properties. Thus the consequences are inconvenient or even serious, but ordinarily can be tolerated.

For small firms, which may evaluate only a few new plays each year and actually enter a new play every two to five years, the consequences of a bad play choice can be disastrous. As a result, smaller companies tend to choose new plays in more established petroleum-producing areas, participating as minority partners, or choose simply to drill a series of independently submitted individual prospects in areas where they already have expertise, thus foregoing the efficiencies of regional exploration, as well as the likelihood of making large new discoveries (see the discussion on creaming curves, p. 68).

Of course, the consequence of a successful new play is to add a new core producing area, which can then be expected to provide a significant and long-lasting incremental increase to the company's production revenues. Because large new fields are typically found early in the exploration cycle, large firms have usually placed a high premium on exploration in new trends and basins. Unfortunately, during the 1980s overall industry participation in such high-risk, high-potential new plays did not add to corporate net worth—it actually destroyed value.

Learning to Make Money Finding Smaller Fields

Incorporation of exploration statistics and the principles of exploration risk analysis into decision making has had a substantial, positive impact on the selection of new plays by modern petroleum companies. Especially compelling are data indicating that, despite continuing development of superb new geotechnical tools and concepts that have kept average exploration success ratios constant at about 25% (Figure 22), annual volumes discovered worldwide have been decreasing since about 1965 (Figure 49a). Moreover, the new fields being found by the international industry are steadily decreasing in size (Figure 1), so that the chances of making a very large discovery are getting very small indeed (Figure 49b). The message is clear: Given that (1) most of the world's possible petroleum basins are increasingly well-known, and (2) the rate of discovery of super-giant fields (“elephants”) has been decreasing since the 1960s, successful oil companies must organize themselves and conduct their E&P business to make money by discovering and developing oil and gas fields in the 10-100 MMBOE categories. They must become more efficient in order to find and produce smaller fields profitably.

Figure 49a

Post-1900 BBOE discovered by

Figure 49a

Post-1900 BBOE discovered by

Figure 49b

Discovery data, 1990-1999 (excluding U.S. and Canada).

Figure 49b

Discovery data, 1990-1999 (excluding U.S. and Canada).

Figure 50

Six generalized planning steps.

Figure 50

Six generalized planning steps.

Fortunately, the new principles of exploration risk analysis (and especially play analysis) provide methods by which a firm's entire exploration effort can be made more efficient, greatly reducing the likelihood of selecting a bad play and providing a greatly improved basis for predicting reserves, chance, costs, and profitabilities of new ventures being considered for entry.

Special Business Requirements May Dictate New Play Attributes

Different companies have differing financial circumstances and business constraints. These special conditions may place special limitations on their requirements of play choices. However, it is important to distinguish between short-term (one to three years) and long-term (four to eight years) constraints, remembering that the time required to identify, evaluate, secure, prove, execute, and develop a new play is usually not less than three years and often as much as six to eight years. Obviously, the astute exploration firm will not allow short-term constraints to prevent it from taking part in a play that is likely to be entirely compatible with the business circumstances expected to exist when the play actually comes to fruition.

Nevertheless, here are some special business conditions that may influence new play choices:

  1. A company with legal contracts that require it to deliver specified volumes of natural gas to cus-tomers may attach higher priorities to gas plays capable of increasing deliverable gas in the short-term, especially if the company fears a possible shortfall.

  2. A company with a limited exploration budget may give preference to plays located near producing infrastructure, or to those whose primary objectives are relatively shallow. Alternatively, such a company may choose to invest in specialized professional staff and state-of-the-art geo-technical tools and methodologies, which can be expected to develop new play concepts that can then be leveraged into substantial shares of multiple new-play ventures. The problem with the latter approach, however, is the substantial time required to build such staff and generate the necessary new concepts.

  3. Some companies may be constrained from operating in certain countries or geographies, either by internal organizational restrictions or limitations or by external circumstances. Similarly, any limited geotechnical skills of the professional staff may prevent consideration of some plays. Sometimes a previous negative experience by senior management in a given location or in a play of a certain type may prejudice them against objectively considering an otherwise valid play venture.

  4. For smaller companies that typically generate new plays, promote them, and thereafter operate as minority partners, certain types of plays may be currently in or out of favor in the marketplace. For example, it is currently very difficult to sell a play or prospect in the U.S. Gulf Coast unless it involves wide 3-D seismic coverage.

  5. Given that taxation of oil and gas production has substantial impact on project profitability, and that tax ramifications may apply to a firm's other ventures, certain plays that offer special tax cir-cumstances may be preferable to other equally valid plays that do not. In the U.S., there has been an unfortunate tendency for firms to pay more attention to such “if-success” tax benefits than to the geotechnical and economic merit of the play itself. Working rule: First priority should go to geo-technically sound, economically superior plays; then consider ancillary tax benefits.

Concurrent Geotechnical, Economic, and Business Evaluations of New Plays

In order to achieve efficient, thorough, and objective assessments of new exploration plays, many geoscien-tists have recognized the need to adopt a consistent procedure that uses either a manual flow-sheet or computer software to perform all the geotechnical tasks and attendant calculations needed to carry out a risk analysis of a new exploration play.

However, a common and unfortunate industry pattern has been to conduct the geotechnical evaluation first, and perform an economic assessment only at the end of the investigation. This often leads to poor and/or delayed business decisions. A much better approach is for the geotechnical, economic, and business assessment to proceed simultaneously, with frequent and detailed integration of such information among team members. This approach results in more reliable estimates and more innovative business plans. It is also more efficient because proposed plays that have severe economic or business limitations may be detected early, and expensive but unpromising geo-technical work may be curtailed, allowing scarce manpower and a limited budget to be used in more promising projects elsewhere. An excellent general summary of long-range exploration planning is provided by Megill (1985).

Specific business circumstances that should be explored and assessed include:

Product Transportation

Are there pipelines in the areas? Do they have available capacity? Will their owners allow your product to be shipped in the areas? Are there transportation tariffs? Are there calendar restrictions? If a pipeline must be constructed, what is the lead time? cost of construction? minimum new reserves to justify pipeline construction? Can you make additional profits by shipping gas for other producers as well as your own? What is the cost and capacity for temporary transportation (truck or ship)? hazards?

Markets

Especially for natural gas, you must consider market volumes, lead times, stability, and growth potential. Always explore the possibilities of ancillary profitable businesses connected with other aspects of oil and gas production.

Contract Terms

Understand in detail the terms of the typical E&P contract in the area and their ramifications regarding different types and patterns of production. Look for negotiating topics that offer positive tradeoffs acceptable to the host government and favorable to the geo-technical character of the play and the specific economic and business attributes of your company. Consider when unleased prospective areas may become available for acquisition of E&P rights. Moran (1992) and Johnston (1997a, 1997b) offer excellent treatments of this topic.

Government Tax Law, Legislation, Regulations, and Incentives

You should have extensive knowledge of the existing and impending tax laws, legislation, regulations, and government incentives, all of which may exert substantial influence on the value as well as conduct of a proposed new play. Such knowledge should be available before making final play valuations or entering into contract negotiations. Johnston (1997b) provides guidance on this topic.

Personnel Needs and Availability

What professional expertise will be needed (and when) to carry out the play? Where should they be located? What about support staff? lead times? What about geotechnical services, such as seismic crews, logging and completion capabilities, and production services? costs? lead times? government permits?

Political and Economic Stability

The traditional approach to political and economic stability addresses the likelihood of a political or economic crisis in the host country sufficient to result in substantial loss of monetary value or property during the life of the project. However, a more realistic approach focuses the question of political/economic risk on the two- to four-year period when substantial capital investments have already been made, but before project pay-out, i.e., recovery of invested capital. Mar-lan Downey (1993, personal communication) has outlined another approach to assessing political risk: Using experienced international petroleum experts, assess the degree to which the real infrastructure of the host country (not just politicians) really wants the firm to participate in the long-term economic development of their country, as opposed to just wanting the firm's money.

Expected Terms and Reputations of Potential Partners

For later-stage entry into existing contract areas, the firm should consider carefully any previous experi-ences with the company holding the license, and discreetly explore its reputation as a competent operator and reliable business partner. Terms of any participation agreement should be evaluated as outlined earlier under Contract Terms.

Likelihood for Renegotiated Contract Terms

One of the most significant potential impacts on play profitability concerns the likelihood that the original contract terms agreed upon with the host government may be renegotiated, either because the play has proved to be much less profitable than first thought or because the host government wishes to modify the contract terms because of changed circumstances.

Let us first consider such contract changes initiated by the company. These arise most commonly from new geotechnical information indicating that the area has a smaller petroleum resource endowment than originally thought—fields are smaller, fewer, or less profitable than expected. Sometimes the host country is willing to renegotiate terms to encourage the company to develop and produce these smaller, less profitable fields and to continue exploration. Sometimes, such changes may be mandated because of new regulations, economic conditions, or political situations. In all cases the tradeoff for the host country involves its genuine desire for the operating company to remain and continue to produce (under the changed terms), versus the consequences to the country's international business reputation if the operating company decides to exit.

In some cases, the proposed contract changes may be initiated by the host country. Common motivations for such renegotiations include:

  • a change of governments, where the incoming government has different priorities for petroleum development. This can include different tax structure, different regulation schemes, different ownership proportions, and the like. Confiscatory government actions risk rejection by the world petroleum community and deterioration of international relations;

  • substantive changes in the world price of oil, either through external market forces, political developments, or new technologies;

  • a perception of excessive profits by the company, in which production potential of the contract area turned out to be much greater than originally anticipated; and

  • a desire by government to keep the company in the host country, in hopes of developing more extensive petroleum resources.

Comparing Plays and Planning Exploration Campaigns

Assumptions

Most substantial, long-lived international oil companies recognize that they must add new core producing areas as their existing large-producing properties deplete. Regardless of whether such new core areas are generated internally through original prospecting skills or by joining into a partnership venture generated by another company, all firms should have a systematic basis by which they can identify, analyze, select, and execute profitable new exploration plays on a continuing basis. This book has previously enumerated five principles of modern exploration play analysis:

  1. The most critical decision in petroleum exploration is the choice of which new play to enter (pp. 3, 57, and 60);

  2. Exploration plays may be analyzed systematically with respect to geotechnical risk and economic profitability, as full-cycle business ventures (pp. 3, 57, and 61);

  3. Successful play analysis requires thorough integration and iteration of diverse geotechnical, economic, and business skills, through multi-disciplinary professional teams (pp. 62, 113, and 114);

  4. Play recognition, analysis, and ranking should be an ongoing, centrally coordinated corporate activity that generates an evolving, dynamic play inventory, from which desirable plays should be selected to form an annual play portfolio (pp. 99 and 113); and

  5. Economic evaluations and business considerations should be linked with geotechnical play analysis from its inception, with special emphasis on contractual negotiation strategies, whether such negotiations are with host governments or companies offering partnership participations (pp. 109 and 111).

The following discussion assumes that all of these five principles are being utilized by the firm.

Constructing a Framework for Comparing Prospective New Plays

The problem in choosing new plays is that many significant criteria must be assigned in order to optimize the selection process. The most important criterion, however, is to estimate the likely profitability of the play venture, given discovery. Other criteria then should be considered:

Ranking by Risked Investment Efficiency

Ideally, new exploration plays should be ranked on one criterion only—risked investment efficiency (RIE) (p. 54)—if the firm is constrained by available capital for investments and the only criterion is to maximize economic value (Capen et al., 1976; Clapp, 1995). In practice, however, many other factors commonly turn out to be great influences in play selection. Often it pays to conduct a quick review of all attributes of the candidate play just to ensure that some requisite attribute is not absent, thus making even a profitable play unwise to pursue further. Such secondary factors may include:

  1. expected net present value;

  2. front-end costs and/or development costs;

  3. chance of economic success;

  4. corporate risk aversion and optimum working interest;

  5. finding cost;

  6. political risks;

  7. critical geotechnical risks;

  8. special business needs;

  9. present value and actual value of net cash-flow stream (the mean-reserves case);

  10. preferred partners; and

  11. portfolio requirements unique to the company.

Play-ranking Matrix

Accordingly, most firms employ a matrix for comparing and ranking plays, in which plays are listed in horizontal order and the various selective criteria are arrayed vertically. Appendix G is an example of such a matrix, which in effect serves as an efficient and practical inventory. All candidate plays in the inventory can be ranked by different criteria, as selected by management; however, companies are well advised to rank candidate plays first on the basis of value as indicated by risked IE.

Optimum Working Interest

For companies whose standard mode of operation is to participate in many international ventures as minority working-interest partners, it is desirable to rank projects based on their actual working interest in the various plays under consideration. Unfortunately, because the choice of the working-interest share is usually made subjectively, this constitutes one of the largest sources of inconsistent corporate decision making (pp. 55 and 93).

Designing Exploration Campaigns

The most practical publications dealing with the design of exploration campaigns—how to plan and carry out successful play exploration—have been written by Megill (1985), Downey (1992), and St. John (1992).

Well-planned plays save money by identifying unsuccessful ventures quickly and efficiently. They make money by identifying potentially successful plays with high probability, optimum participation, and minimal investments, before success can be claimed with certainty. Successful play exploration represents the ultimate geotechnical leverage. But good play-planning starts with:

  1. discriminating, reliable geotechnical work, investigating petroleum systems;

  2. sound play risk analysis; and

  3. integrated concurrent business assessments.

The writer has already pointed out the common, counterproductive industry pattern of waiting until the end of the geotechnical play evaluation before carrying out the economic assessment of the venture. Alternatively, the most efficient way to generate a properly evaluated exploration venture is to periodically perform provisional risk analysis, economic evaluation, and business planning as the new play evolves from concept to provisional play to commit-ted venture. In this way, large geotechnical uncertainties can be related to economic and business circumstances, to highlight critical business issues and negotiating strategies. For any new play that is finally selected by the firm for participation, a series of provisional economic and business assessments should have been carried out, which attached values to the new play during its emergence as a valid busi-ness venture.

This calls for close, ongoing, and effective liaison and integration among geoscientists, engineers, plan-ners, economists, negotiators, and decisionmakers, considering especially the topics raised in the previous sections of this chapter.

The planning process is graphically represented by Figure 50, originally developed by Megill (1985). It begins with sound geotechnical work and objective risk analysis of the prospective play as a full-cycle economic venture. A provisional economic evaluation of the emerging play is carried out, often using rough estimates and based on the play's projected means-reserves case. Simultaneously, the availability of contractual rights to the play area is assessed and integrated with:

  1. the play risk analysis;

  2. play economics for different reserves outcomes; and

  3. probable methods and tactics for lease acquisitions.

Concurrently, the integrated exploration team should identify critical or sensitive factors that may affect play profitability (or demonstrate the need for early exit), for early use by negotiators and business agents, and for additional geotechnical studies that provide cost-effective ways to clarify the risk-reward ratio of the project.

Using reasonable assumptions, the emerging play then takes its place in the existing play inventory. If it appears to compare favorably with the firm's other contemplated or actual plays, the next stage of geotechnical, economic, and business studies should be initiated following the most cost-effective paths for project improvement by reducing geotechnical risk, reserves uncertainty, and project costs, or by improving profitability through more efficient development, streamlined business arrangements, and favorable contract terms. Economic evaluations should be carried out periodically as critical new geotechnical and business information is acquired.

If the play appears clearly to be inferior to other ventures being considered, it should be filed for later review (one to two years). If the play appears to be marginal, a brief analysis should be carried out to indicate those factors that could be improved and the likely degree of improvement.

Superior plays should be selected from the play inventory to form the annual play portfolio. This selection should give strong weight to the risked investment efficiency of the constituent projects, but it is also appropriate to consider other criteria as well. Required investments will be apparent at this stage.

Once the play portfolio is selected, budget allocations must be made. These allocations should be planned provisionally over at least a five-year period, covering several possible outcomes. Decision points should be clearly denoted in the five-year budget plan, following contingent developments.

The final step in the planning process involves manpower planning, which has three essential aspects:

  1. What skills are likely to be needed, for what time periods, and where?

  2. Who are the existing staff members who represent the required expertise? What vacancies must be filled by recruitment, and when?

  3. Construct a provisional plan for staff succession and promotion.

The final step involves management's decision to carry out the new play, with early priority given to both advantageous negotiating tactics and the formation of a play team based on the previous manpower considerations.

Overview of Successful Play Management

Successful, cost-effective play development is a continuously evolving, multidisciplinary staff effort that requires dedicated professional skill, unselfish cooperation, thorough communication, objective evaluations, and courageous execution. Properly organized and managed profitability, play selection, and development provide—on a regular basis—new prospects to populate the firm's annual drilling portfolio, and therefore new discoveries of economic reserves to replace produced reserves. Orderly new play development is impeded by frequent reorganizations or personnel instability. Properly executed, the exploration play is the ultimate form of leveraged geotechnical risk venture. But an essential aspect of successful play generation and analysis is another ongoing process—the rigorous assessment of geotechnical as well as economic performance. That is the subject of the final section of this chapter.

Assessment of Exploration Performance

Most of the critical parameters that influence valuation and ranking of exploration plays and prospects are, in fact, estimates made under varying degrees of uncertainty. This places a heavy professional burden on the corporate technical staff to consistently generate responsible, unbiased estimates, and on exploration decisionmakers to utilize such estimates wisely and consistently. When technical estimates are overly optimistic, the firm is encouraged to invest in inferior projects. Overly conservative estimates discourage the firm from realizing the full profit potential of underestimated projects. Thus either error has the potential to cause loss; either error reduces staff credibility. When company decisionmakers do not know the relative reliability of technical estimates, they are encouraged to rely on their intuition (which usually causes great inconsistency) and to improperly use expensive geotechnical data bearing directly on project risk versus reward.

The only way for corporate decisionmakers to improve the overall exploration performance of the firm is to monitor and preserve, on a systematic and routine basis, the technical and economic predictions made by their professional staff, and to compare them against actual outcomes. Without such ongoing calibrations, technical and economic forecasts are analogous to one-way rockets launched into outer space—there is no feedback! Without comparisons, exploration companies continue to make the same mistakes year after year, and performance of neither staff nor decisionmakers can be measured properly; accountability is thus greatly diminished. What gets measured, gets done.

Technical Performance versus Economic Performance

It is important to recognize that positive results from excellent technical predictions can be nullified by inept economic forecasting, and vice versa. Technical staff should not be penalized for the poor performance of the economic staff and managers. Accordingly, for both plays and prospects, two different aspects of performance should be monitored. Technical performance compares all geotechnical, engineering, and cost/price forecasts with actual outcomes. Some examples are reserves; chance of completion; initial production rate; decline percentage; drilling, completion, and operation costs; and wellhead prices. Economic performance measures forecasts of project profitability in relation to actual profitability; both forecasts and actuals must be related to preselected corporate standards. Some useful economic measures adaptable as success criteria include predicted project ROR in relation to actual ROR and to corporate hurdle rates; projected venture NPV and IE compared with actual NPV and IE; actual early-term investment costs compared with predicted investment costs; projected exploration cost of finding (COF, expressed in $/BOE) compared with actual COF and established corporate COF goals. Making economic comparisons on the basis of actual monetary value (rather than present monetary value) may facilitate the process. Also, cost-of-finding results should be normalized by distinguishing between increased drilling efficiencies, stimulation and completion efficiencies, and exploration skills. Finally, try to separate economic influences that lie within the purview of professional staff and managers from external influences over which technical and management staff had no control.

For all prospects, scenarios outlining various technical and economic outcomes and their consequences should accompany any project recommendations. For possible economic events external to the project (world price fluctuations, international political developments, new technologies, etc.), project planners should also outline scenarios, impacts, and possible responses.

Measuring Performance: Plays versus Prospects

Papers by Rose (1987), Clapp and Stibolt (1991), Capen (1992), Otis and Schneidermann (1997), Alexander and Lohr (1998), Johns et al. (1998), McMaster and Carragher (1998), and McMaster (1998) presented different but complementary methods for evaluating and expressing staff performance in geotechnical predictions related primarily to prospects rather than plays. For many corporations that participate in 20 to 100 exploratory prospects each year, such methods provide an acceptable basis for assessing and improving geotechnical predictive performance, either on an annual or multi-year, moving-average basis.

Assessing predictive performance for plays is much more difficult than for prospects. Variance (uncertainty) within plays is generally much greater, and the number of predictions at play scale are far fewer than predictions at prospect-scale. For plays, elapsed time between technical predictions and measurable results is commonly four to eight years; economic forecasts commonly require six to 12 years before useful comparisons can be made. Normal personnel changes over such timeframes reduce staff continuity and preserved histories of projects. Fear of criticism (on the parts of both technical staff and managers) leads to incomplete preservation of key records and reports. Changes in technical and economic definitions produce inconsistent data sets.

Moreover, there is great organizational pressure for early and correct assessments—for example, that an emerging play is mediocre, or that it has great potential. Understandably, companies do not want to wait four to eight years to decide that a given play is not worthwhile. Opposed to this pressure is another truth: Beware the premature exit, the abandonment of a promising play after only one dry hole! Naturally, the key issue here is to focus on what was learned from that dry hole— does it apply throughout the play area (as a shared attribute) or does it apply only to the specific prospect (as an independent factor)?

Criteria Indicating Competence in Play Analysis

Because indirect and subjective criteria must be used to assess the technical performance of play teams, the writer has developed 10 criteria that help to indicate the relative skill level with which such teams are functioning in the critically important activity of generating and evaluating new exploration plays. He has used these criteria for more than eight years in reviewing play development teams for many different international exploration companies.

  1. Some team members have previously been closely associated with discoveries. Successful past experience brings an essential sense of scale and scope to the geotechnical process, especially to keep the effort focused on practical (rather than scientific) problems. Play analysis is best carried out by seasoned, capable professional geoscientists and engineers.

  2. Routine use is made of the petroleum system approach. All geotechnical aspects of hydrocarbon occurrences are routinely integrated, with special emphasis given to understanding the HC kitchen (see Appendix E). Integration of petroleum system thinking with regional tectonic expertise and broad knowledge of basin classification provides additional creative insight and power.

  3. Routine use is made of geostatistics and databases. Thoughtful, thorough acquisition, organization, and regular analysis of critical and current sta-tistical data is necessary, such as:

    • field production catalogs;

    • routine construction of FSDs, including FSD shift studies (see pp. 71-75);

    • success-rate studies in analog trends, including show-holes, economic discoveries, and dry-hole causes; and

    • field number and density studies (including creaming curve data) for analog trends.

  4. Staff has easy access to comprehensive petroleum references. Staff must have ready access to the international literature on petroleum exploration, production engineering, economics, finance, and law. Many data are free, in the public domain. Proprietary reports and databases provide additional information. Successful play analysis requires efficient sifting through of copious quantities of data. A competent technical librarian is a valuable member of any play-generating group.

  5. A consistent process is routinely used for formal play analysis. Routine use is made of a simple, consistent flow sheet or of software to estimate chance of economic play success and reserves potential.

  6. There is demonstrated continuous integration of provisional economic criteria and business considerations with the emerging geotechnical picture. It is important that each play group have a modicum of economic and business expertise, or have routine access to (and interactions with) such expertise.

  7. An open, dynamic play inventory is maintained. A continuously changing inventory of new and existing plays should be ranked consistently by investment efficiency and show status of the projects. Appendix G is an example. The constituents of the inventory should include plays having reserves potential that is appropriate to the company's needs, in diverse geologic settings, and of an adequate number to ensure a satisfactory annual flow of new trends into the firm's exploratory effort.

  8. Technical work is organized and orderly. There are visible planning calendars and evidence of:

    • efficient and timely work performance;

    • accurate forecasts of costs;

    • geotechnical costs that are competitive with industry standards; and

    • systematic preservation of regional geologic compilations, in a usable format.

  9. Systematic criteria are used for measuring the accuracy of technical forecasts. There is an ongoing, open process for recording forecasts of emerging data focus in the areas and comparing them with actual results, as well as periodic review of predictive performance and sharing of lessons learned.

  10. Routine group procedures are used for peer reviews and the generation of new ideas. There is an open, interactive working atmosphere where professionals informally review each other's emerging work and stimulate new ideas through routine group interactions.

Attributes of Good Play Managers

Good managers of the process of exploration play generation and analysis are by nature generalists and integrators. They must be able to motivate individuals of diverse technical expertise and personality types, to listen and communicate effectively, and to keep pro-jects on schedule and within budget. They must strike a working balance between accepting large, irreducible uncertainties and using expensive state-of-the-art technologies to reduce risk where they are cost-effective. Good play managers must be willing to make decisions on imperfect information, being cognizant that some of their decisions may turn out to be wrong. They must understand clearly that early rejection of a considered play for technical and/or economic reasons does not constitute failure. Such managers know that money can be made in two ways: by finding profitable new plays and by staying out of unprofitable ones. Such managers must have an inherent sense of:

  1. the known facts that are critical;

  2. the unknown facts that need to be determined; and

  3. the acceptable level of irreducible uncertainty and risk, given project costs and potential rewards.

Play Analysis: Organizational Patterns and Principles

Common Patterns and Procedures

The writer has observed and noted several common biases, patterns, and useful procedures of corporate risk analysis that are practiced by capable explo-rationists around the world:

  1. Most geoscientists with medium to large companies tend to overestimate the reserves sizes of future discoveries, especially in onshore plays.

  2. Conversely, they tend to underestimate the number of future fields, especially in onshore plays.

  3. Pmefs for new plays commonly lies between P30% and P70%. As Pmefs rises above 50-60%, the chance of economic play failure increases rapidly.

  4. If the required geotechnical data are available and organized (see pp. 65 and 84 and Appendix E), a discriminating play analysis can be carried out in one or two work days.

  5. Many of the critical supporting data on exploration plays are in the public domain and therefore are quite inexpensive—use them!

  6. Reasonable estimates of future field numbers can be derived from analog producing areas and verified using discovery process modeling or other pragmatic methods (pp. 69-70).

  7. Intelligent manipulation and utilization of FSDs (combined with estimates of field numbers) allow useful forecasting of play reserves.

  8. Items 4 through 7 demonstrate the importance of having, in every play-analysis organization, qualified technical staff—especially a librarian and statistical technician—to assist in data acquisition, organization, and analysis.

  9. Full-cycle economic analysis of exploration plays allows discriminating business decisions to be made early in the exploration cycle.

  10. Play analysis does not provide perfect answers, but it will prevent serious mistakes at either extreme, both the positive and the negative, and that level of precision is usually sufficient.

  11. The play only works where all the geologic chance factors coincide. Your job as play analyst is to delineate the area of coincidence (and possibly the more apparent prospects in it). Make overlay maps showing degrees of confidence in the various elements of geologic chance.

  12. Pay very close attention to the kitchen—and recognize that “shows are the footprints of migrating oil.”

  13. Using the petroleum system concept, think critically and imaginatively about potential reservoir/seal couplets to help recognize potential new plays.

  14. Identify and focus on the critical data that will prove or disprove the play.

  15. “The early bird gets the worm”—usually, the larger fields in a new play are found early in the exploration cycle.

  16. Play exploration requires routine application of geotechnical analogs, but be sure your analog is valid!

  17. Try to nurture creative and/or unconventional ideas in the face of contrary opinions, especially in older trends.

Tips on Basic Working Principles for Exploration Play Analysis

Following are some pragmatic and even philosophic tips for explorationists involved in play generation and analysis.

  1. Don't be afraid of “quick and dirty” methods (pragmatic rules of thumb)—sometimes such approximations are all you can do anyway, and they are often reasonably accurate and cost-effective.

  2. Accept the necessity of making subjective decisions, using uneven and qualitative data.

  3. Honor nature's envelopes—lognormality, known limits of parameters, and reality checks.

  4. Remember the power of independent multiple estimates.

  5. Hydrocarbon generation/migration is important—pay attention to the kitchen and what's in it when.

  6. The Earth is trying to speak to us, and geology and geostatistics are her language—listen for the message (see item 7).

  7. Don't get lost in the technical forest; the details may be complex, but the basic message is usually simple.

  8. Geoscientists behave as if they know more than they really do, usually stating uncertainty sub-stantially—widen your ranges!

  9. There are two kinds of unknowns—the good unknown and the bad unknown. Allow for both.

  10. Control front-end costs vigorously—don't overpay for opportunities, and evaluate proposed data acquisitions for cost-effectiveness (see item 11).

  11. Remember that the objective is to make a reasonable profit. Accomplish this by limiting your losses on failures and making large profits on your successes.

  12. The expected value concept is always a useful yardstick for consistency. When EV is positive, you're investing—when it's negative, you're gambling. Invest!

  13. There are two simultaneous and interactive evaluations: geotechnical and economic—don't ignore either one.

  14. In competition, the Winner's Curse always looms. Know how to avoid it—above all, avoid blind competitiveness.

  15. It is not as if you know nothing—you usually know more than you think you do!

12This compares average bid prices on a nominal dollar basis; on a “real” basis, i.e., taking inflation into account, the average per-acre reduction of bids is much greater, probably to about 4% to 5% prearea-wide sales average.

Figures & Tables

Figure 40

Staged exploration.

Figure 40

Staged exploration.

Figure 41

Sealed bidding for uncertain reserves leads to the winner's curse.

Figure 41

Sealed bidding for uncertain reserves leads to the winner's curse.

Figure 42

Net purchases by company: Gulf of Mexico sales, 1972-82 (figure courtesy of Robert Clapp). Compare with Figure 43.

Figure 42

Net purchases by company: Gulf of Mexico sales, 1972-82 (figure courtesy of Robert Clapp). Compare with Figure 43.

Figure 43

Gulf of Mexico bidding efficiency (1988-95). Compare with Figure 42.

Figure 43

Gulf of Mexico bidding efficiency (1988-95). Compare with Figure 42.

Figure 44

High bids and second bids; GOM lease overbids averaged about 50% pre-1983 (from Megill, 1984).

Figure 44

High bids and second bids; GOM lease overbids averaged about 50% pre-1983 (from Megill, 1984).

Figure 45

High bids and second bids; area-wide GOM lease overbids averaged 75% post-1983.

Figure 45

High bids and second bids; area-wide GOM lease overbids averaged 75% post-1983.

Figure 46

Spinner for simulating chance of success and reserves discovered.

Figure 46

Spinner for simulating chance of success and reserves discovered.

Figure 47

Predictive accuracy of portfolio performance improves with the number of wells in the portfolio.

Figure 47

Predictive accuracy of portfolio performance improves with the number of wells in the portfolio.

Figure 48

The efficient frontier.

Figure 48

The efficient frontier.

Figure 49a

Post-1900 BBOE discovered by

Figure 49a

Post-1900 BBOE discovered by

Figure 49b

Discovery data, 1990-1999 (excluding U.S. and Canada).

Figure 49b

Discovery data, 1990-1999 (excluding U.S. and Canada).

Figure 50

Six generalized planning steps.

Figure 50

Six generalized planning steps.

Table 18

Biases affecting risk decisions (modified after Tversky and Kahnemann, 1974).

Type of BiasCommon Example
Framing effectsDecision makers will take a greater gamble to avoid a loss than to make an equal gain.
Existence of a prior accountDecision makers are more inclined to take a risk at the beginning of a project than later in the project's life.
Maintaining a consistent reference frameDecision makers are most likely to invest during a “run” of good fortune, and less likely to invest during a “run” of bad fortune.
Probability of successA venture having a perceived high chance of success is preferred over a second venture having a low chance of success, even though the expected value of the second venture is clearly superior.
Wrong action versus inactionManagers prefer to take a risk by not making a decision, rather than taking action that could result in the same loss.
Number of people making decision Workload and venture sizeGroups are more prone to take risks than individuals. Large-volume ventures are preferred over smaller ones, especially when decision makers are busy.
Personal familiarityThe “comfort bias”-decision makers are more risk-prone in deals or environments with which they have good experience.
Type of BiasCommon Example
Framing effectsDecision makers will take a greater gamble to avoid a loss than to make an equal gain.
Existence of a prior accountDecision makers are more inclined to take a risk at the beginning of a project than later in the project's life.
Maintaining a consistent reference frameDecision makers are most likely to invest during a “run” of good fortune, and less likely to invest during a “run” of bad fortune.
Probability of successA venture having a perceived high chance of success is preferred over a second venture having a low chance of success, even though the expected value of the second venture is clearly superior.
Wrong action versus inactionManagers prefer to take a risk by not making a decision, rather than taking action that could result in the same loss.
Number of people making decision Workload and venture sizeGroups are more prone to take risks than individuals. Large-volume ventures are preferred over smaller ones, especially when decision makers are busy.
Personal familiarityThe “comfort bias”-decision makers are more risk-prone in deals or environments with which they have good experience.
Table 19

EV implies “risk-neutral.”

Table 20

A model prospect portfolio (prospects are ranked in this list by ENPV).

Reserves (MMBOE) If SuccessfulEconomic Measures For Ranking
ProspectDry-Hole Costs ($MM)Chance Of SuccessP10%/P90%MeanP90%/P10%Mean NPV ($MM)Risked Mean Reserves (MMBOE)Investment ($MM)OWIENPV ($MM)Investment EfficiencyRAV
A6.20.055.050.0112.5275.02.515.00.037.867.86/15.0 =0.520.103
B5.40.102.424.054.0120.02.48.80.077.147.14/8.8 =0.810.224
C3.20.202.28.016.032.01.66.00.263.843.84/6.0 =0.640.445
D4.00.151.010.022.545.01.57.20.143.353.35/7.2 =0.470.214
E1.80.150.66.013.524.00.93.30.332.072.07/3.3 =0.630.305
F2.00.201.14.09.014.00.82.00.351.201.20/2.0 =0.600.197
G0.80.250.32.04.46.00.51.81.000.900.90/1.8 =0.500.516
H1.50.200.53.06.69.00.66.10.390.600.60/6.1 =0.100.111
I0.50.300.21.02.22.50.30.81.000.400.40/0.8 =0.500.309
J0.40.400.10.51.01.00.21.01.000.160.16/1.0 =0.160.137
N = 1025.802.00108.5528.511.352.04.57 = .4627.52IE program =0.532.56
Avg.=.2Avg.=.46
Reserves (MMBOE) If SuccessfulEconomic Measures For Ranking
ProspectDry-Hole Costs ($MM)Chance Of SuccessP10%/P90%MeanP90%/P10%Mean NPV ($MM)Risked Mean Reserves (MMBOE)Investment ($MM)OWIENPV ($MM)Investment EfficiencyRAV
A6.20.055.050.0112.5275.02.515.00.037.867.86/15.0 =0.520.103
B5.40.102.424.054.0120.02.48.80.077.147.14/8.8 =0.810.224
C3.20.202.28.016.032.01.66.00.263.843.84/6.0 =0.640.445
D4.00.151.010.022.545.01.57.20.143.353.35/7.2 =0.470.214
E1.80.150.66.013.524.00.93.30.332.072.07/3.3 =0.630.305
F2.00.201.14.09.014.00.82.00.351.201.20/2.0 =0.600.197
G0.80.250.32.04.46.00.51.81.000.900.90/1.8 =0.500.516
H1.50.200.53.06.69.00.66.10.390.600.60/6.1 =0.100.111
I0.50.300.21.02.22.50.30.81.000.400.40/0.8 =0.500.309
J0.40.400.10.51.01.00.21.01.000.160.16/1.0 =0.160.137
N = 1025.802.00108.5528.511.352.04.57 = .4627.52IE program =0.532.56
Avg.=.2Avg.=.46

NOTES:

  1. Dry-hole cost includes exploratory drilling & completion, land, G&G, and overhead.

  2. Firm's r=5/50MM=.1.

  3. Firm's RT=1/r=1/.1=10.

  4. Order of prospects changes if ranked on investment efficiency (IE) or RAV.

ANTICIPATED RESULTS: This portfolio of 10 exploratory wells is a balanced program including three lower-risk extension wells (G, I, & J), five medium-risk trend wildcats (C, D, E, F, & H), and two high-risk new-field wildcats (A & B). The most probable outcome of this program is: two discoveries, totaling 11.3 MMBOE reserves, having a total mean program expected value of $27.52MM. Cost of finding should be about 25.8/11.3 = $2.30/BOE. Program EPV/lnvestment = 27.52/52 = 0.53.

Table 21

Simulation of results for a prospect portfolio.

Table 22

Uncertainty leads to common underperformance of exploration portfolios (after Horner, 1990).

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