A simplified version of the Smith and Nau (1995) integrated solution scheme is applied to the valuation of an oilfield project possessing salvage options and both private and public uncertainties. It is shown that the computed valuation is consistent with the definition of the real option price as the maximum value that could be obtained, without market risk, from an ensemble of projects that sample the private uncertainty. The attainment of this value requires an optimal decision strategy and a hedging strategy, both of which are obtained as a byproduct of the valuation. The interpretation of the obtained value is validated by forward simulation over an ensemble of projects, by use of a fully reproducible worked example.
Surveillance in one form or another has been used in oil and gas production almost since the industry began. The initial goal was relatively simple and straightforward: monitoring output against production targets for individual wells and troubleshooting those same wells when problems occurred. The actual scope of what could be accomplished was limited by available resources and lack of tools and technology, so only a very few high-value wells could be monitored closely.
With modern complex oil- and gas-production operations, the goal of surveillance has evolved from ensuring a single well's performance to managing a producing asset against its potential--a much loftier endeavor that must consider each of the system components, the interaction of those components, and the impact of factors external to the system. Traditional approaches to surveillance are no longer adequate to meet the current and continuously emerging and increasingly complex requirements of oil and gas operations. Modern and next-generation surveillance systems must deliver more.
More recently, in both mature fields and green fields, the industry has seen increased implementation of more-sophisticated solutions with richer capabilities (e.g., monitoring centers that feed data into real-time displays; the enabling of operations staff to see the status of all key measurements; and model-based, integrated workflows to automate and facilitate operational excellence). The addition of advanced analytics, expert systems, and process automation (all of which routinely leverage real-time information) has taken surveillance from gathering production data on grease books to sophisticated solutions that combine business or operational intelligence with automated technical calculations. Indeed, these are the types of surveillance solutions expected by forward thinking managers. However, despite these successes, widespread uptake of these types of solutions is slow, as is often the case in our industry.
This paper provides a survey of business practices proven in other complex industries, including management by exception (MBE), business intelligence (BI), situational awareness (SA), model-based decision support (MBDS), advanced process control (APC), and consequential analysis (CA). With learning from use in other industries, these business practices, enabled by state-of the art information technology, can be combined and implemented to build next-generation surveillance solutions that will allow oil and gas producers to manage production assets against their potential in a safe, environmentally responsible way and in support of corporate goals.
Most decision analyses include continuous uncertainties (e.g., oil in place, oil price, or porosity). Analysts are frequently concerned with how to best structure, compute, and communicate decision models under these circumstances. While decision trees are well suited for discrete random variables with a few possibilities, they become unmanageable for a large number of outcomes. To address this concern, analysts frequently use discrete approximations such as Swanson's Mean. Previous work has quantified how well differing discretization methods match the moments (e.g., the mean and variance) of the underlying continuous distribution. More specifically, previous work has not included the decision context in which the discretizations are used. In this paper, we begin to address this gap by comparing different discretizations within the context of an information-gathering decision problem. We find that the best discretization is highly dependent on the decision context, which is difficult to specify in advance. In addition, we contrast the use of discrete approximations to Monte Carlo simulation.
Long-term economic viability of unconventional reservoirs is evaluated from the profit-maximizing perspective of a producing company. The case of the liquids-rich production from the Bakken field is considered as a representative of unconventional resources. A profit-margin optimization model is constructed for a company to meet the demand it faces from a stock of conventional and unconventional resources given different sets of exogenously determined prices. The model is parameterized using the different production decline rates of the two sources, physical and economic exhaustibility of the resources, and the ever increasing marginal cost of adding conventional resources into the company portfolio. The optimal extraction path of oil from the conventional and unconventional reservoirs is assessed, and the long-term economic consequence of keeping the unconventional resource in the ground for different oil-price scenarios is predicted. The model reveals the appropriate composition of a portfolio of conventional and unconventional resources. In the case of a high-price scenario, the optimal efficient extraction path is the pursuit of additional conventional resources before using unconventionals to meet the demand. For the reference-price scenario, the decline of the conventional reserves should be substituted with unconventionals from the beginning. The profitability of the enhanced oil recovery (EOR) applications in unconventional reservoirs and when they should be implemented are also determined. Contrary to common expectation, it is shown that the EOR technology is more justifiable in the case of a lower price forecast.
Most estimates of the resource endowment [original gas in place (OGIP)] reported for world unconventional gas start with Rogner's top-down study (Rogner 1997). That global estimate is most likely quite conservative because the oil and gas industry has discovered enormous volumes of shale gas around the world since the 1990s. The data from these new reservoirs add substantially to our understanding of the unconventional resource base. Furthermore, the uncertainty of Rogner's assessment was not quantified. Thus, considering the uncertainty, a new assessment of original unconventional gas in place worldwide is needed.
The objective of this project was to estimate the probabilistic distributions of original volumes of gas trapped in coalbed, tightsand, and shale reservoirs worldwide. To accomplish this objective, we reviewed published assessments of coal and conventional and unconventional resources and established the quantitative relationship between unconventional gas [coalbed methane (CBM), tight-sands gas, and shale gas] and the conventional hydrocarbon (coal, conventional gas, and oil) resource endowments for North America. Then, we used this relationship to extrapolate original unconventional gas in place worldwide. Our assessment of the world resource endowment established an unconventional OGIP of 83,400 Tcf (P10) to 184,200 Tcf (P90), which is 2.6 to 5.7 times greater than Rogner's estimate of 32,600 Tcf.
Our regional assessments of unconventional OGIP should help industry better target its efforts to rapidly accelerate the development of unconventional gas resources worldwide. The methodology used to assess the distribution of each type of unconventional OGIP may be used to estimate unconventional gas resources at the country or basin level, given knowledge of the coal in place and technically recoverable resources of conventional hydrocarbons.
The Advanced Collaborative Environment Community of Practice (CoP) was formed in March 2009 at the request of BP senior management to share good practice and promote standardization in the area of wells. Its mandate was one of self-help and leveraging scale but working through influence and consensus, with management support rather than by direct authority. The CoP was also required to adhere to company information technology (IT) standards and technology strategy.
At the time of the CoP's formation, collaborative environments had been commissioned in various company locations worldwide, including Aberdeen; Baku, Azerbaijan; Houston; Stavanger; and Tangguh, Indonesia. In the absence of standardized requirements for Wells' collaborative environments and with an emphasis on innovation, each of these centers had been developed independently, strongly influenced by local ideas, needs, and resources. However, it was evident that connectivity between the different locations and with other disciplines was lacking, and that effort was duplicated.
The CoP currently has more than 30 members, including Wells, subsurface, IT, and well technology from 12 locations worldwide. It meets virtually, involving the widest possible membership in different time zones. It has been instrumental in progressing and communicating standards, supporting the introduction and use of common tools and technology, leveraging members' knowledge and expertise, and helping startups in new areas. Overall, the CoP has been a great success. The paper describes the CoP's evolution, from its formation to the present, and critically examines its achievements, shortfalls, and future goals.
In a rapidly changing technical environment, achieving and maintaining alignment between the diverse stakeholders in a medium to large organization can be challenging. The CoP has earned its credibility and has proved to be an effective means of sharing experience and making good use of scarce resources, both keys for adoption at scale.
Many companies operating in the upstream gas industry in the Middle East and North Africa (MENA) are interested in the outstanding technical successes achieved by the US and Canadian tight and shale gas producers. It seems almost miraculous that companies can obtain significant gas-production rates from rocks with permeabilities measured in nanodarcies--so low, in fact, that permeability becomes almost impossible to assess accurately. In North America, the main factor now constraining shale gas production is the historically low gas price. Operators in MENA, who are accustomed to working in formations with permeabilities five or six orders of magnitude greater, have realized recently that they may be sitting on top of huge untapped gas reserves that had been evaluated previously as subeconomic.
In recent years, several major MENA-based operating companies have bought interests in US and Canadian tight and shale gas operations, with the objective of acquiring experience and technology that can be applied to similar formations in MENA and elsewhere. This seems to be an obvious and wise strategy; unfortunately, the problem is not the strategy, it is the tactics ("the devil is in the details"). In many instances, operating companies have been disappointed to discover that they cannot simply transplant an American-style development into MENA. Similarly, many North American independents have viewed the untapped low-permeability gas reserves of MENA as a natural territory for expansion, only to find themselves frustrated at almost every turn.
This paper seeks to highlight the potential pitfalls of trying to use North American development techniques in MENA, and to promote strategies and tactics that are more suitable. In addition, this paper will suggest structural changes that could have a significant positive impact on low-permeability gas developments in MENA.
This study analyzes the typical challenges and opportunities related to unconventional-gas-reserves maturation and asset performance. Volatility in natural-gas prices may lead to downgrading of formerly proved reserves when the marginal cost of production cannot be sustained by the wellhead prices realized. New US Security and Exchange Commission (SEC) rules have accelerated the growth of unconventional-gas reserves, which in a way is an additional but unintended source of volatility and hence risk. Concerns about security of investments in unconventional-gas assets are driven by the effects of volatile natural-gas prices on production economics and by uncertainty about stability of reported reserves. This concern is exacerbated by an unprecedented rise in proved undeveloped gas reserves (PUDs) reported by unconventional-gas operators, arguably effectuated by favorable interpretations of PUDs when applying the new SEC accounting rules. This study includes a benchmark of proved reserves reported by two peer groups, each comprising four representative companies. The peer group of conventional companies includes Exxon, Chevron, Shell, and BP, and the unconventional peer group is made up of Chesapeake, Petrohawk, Devon, and EOG. Possible sources of undue uncertainty in reported reserves are highlighted, and recommendations are given to improve the reliability of reported reserves, especially from unconventional field assets.
The combination of computer technology and decision theory has failed to produce the dramatic improvement in the quality of corporate decisions that some predicted. In this paper, I suggest that this failure comes, at least in part, because too little attention has been paid to the environment in which corporate decisions are made. Specifically, this article proposes that corporate decision processes are not constructivist rationality, but more closely resemble the ecological rationality of biological systems shaped by evolution and natural selection. That is, decision processes in corporations evolve over time to satisfy, although not necessarily to optimize, both stated and unstated objectives subject to complex information cost structures and constraints. To illustrate, examples of persistent information asymmetry and economic signaling in nature and in decision processes are shown. Finally, this article suggests that improved understanding of the forces that impact the evolution of corporate decision processes may allow decision theory to come closer to achieving its potential.
We discuss the two-factor oil-price model in valuation and analysis of flexible investment decisions. In particular, we will discuss the real options formulation of a typical oilfield-abandonment problem and will apply the least-squares Monte Carlo (LSM) simulation approach for calculation of project value. In this framework, the two-factor oil-price model will go a long way in the analysis of decisions and value creation. We also propose an implied method for estimation of parameters and state variables of the two-factor price process. The method is based on implied volatility of option on futures, the shape of the forward curve, and the implicit relationship between model parameters.