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June 2002
Management The Consolidating Oil Business: Technological Solutions to Managing Expanding Diversity and Geographic Breadth
Bill Bartling, Director, Global Energy Solutions, SGI
The oil company and oil services mergers of the recent past have resulted in national and multinational oil corporations of megaproportions. Even as it appears that no further mergers of this scale can be imagined, new announcements sail in over the horizon. Over the next decade, the challenges of oil and oil service companies will transition away from improving exploration success toward production efficiency and optimization. The challenges will be especially keen for these gargantuan new companies formed by mergers.
The benefits of production efficiency--increasing recovery factors by as much as 100 percent--will drive investment strategies. Just as dramatic improvements in exploration success have delivered access to economic reserves in environments and geological settings off-limits in the past, improved production efficiency will allow fields to deliver cash, longevity, and profits never imagined either from existing or future fields. The prospect of doubling recovery factors from fields with incremental capital investment is an irresistible business scenario.
But mergers--and especially megamergers--bring their own set of organizational and management challenges, the solutions of which directly affect the financial success of the merged company. Companies in one stroke of the pen potentially double their geographic breadth, find themselves with a surplus of qualified people, and inherit disparate, conflicting information technology (IT) systems with a broad array of data and application solutions. In many cases, the last include legacy components that, by neglect, financial planning, or design, make up mission-critical business enterprise infrastructure.
Government oversight, especially with the oil industry, is highly efficient at minimizing the accumulation of geographic asset density, pushing companies to extend their geographic breadth through mergers instead. Indeed, the biggest and smallest of the megamergers alike are typified by mandated, aggressive, targeted property divestiture to comply with government restrictions. Thus, the net effect of most mergers is a broadening of geographic distribution rather than an increase in operational density within existing geographies.
At the same time, merged companies find themselves with too many employees to operate an efficient company. Not only do companies look immediately for ways to reduce operational expenses to assist in the pay-out of the merger, but they quickly discover redundancies in roles from an organizational perspective. The most common resolution is to offer aggressive early retirement packages to motivate employees to retire early after noteworthy service to their employers. In years past, this strategy proved efficient, but, since the mid-1990s, the demographics of the industry have changed, resulting in a different and perhaps unwelcome outcome.
The economic perturbations of the past 20 years in the oil industry have painted an increasingly unattractive career world for university students. The population of undergraduate students in key petroleum-oriented majors is waning at a rapid rate, oscillating in near lockstep with the price of oil. This, in combination with severances, both forced and voluntary, caused by mergers and unstable economics, has driven the mean age of the technical work force up to uncomfortable levels. Traditionally, a larger pool of highly skilled talent was available to enter companies from universities to step into important technical management and consulting roles as older experts and managers ended their careers. Today, that pool is limited, causing companies to leverage fewer employees across larger domains.
In parallel with--and, in large part, fueling--the current wave of consolidation, economic standards for the oil industry have been driven toward much more stable, predictable growth and return on investment (ROI) independent of the price of crude. The pressures on cost of finding and production efficiency are exacerbated by the need for 100 percent clean environmental records and a strong push, at least in the United States, to emphasize any strategy that would lengthen the life of existing fields with no increase in environmental impact. In addition, the major players in the world today are supergiant national oil companies, and multinational players must reach a high degree of financial strength to have the investment and operational credibility to enter such historically inaccessible reserves.
The picture we see today involves companies that are combining to meet financial and growth targets, but in doing so are creating new challenges:
- Their geographic breadth has as much as doubled.
- Their IT infrastructure has grown increasingly heterogeneous and outdated.
- Their expert work force has diminished.
- Their need for better decisions and shorter cycle times has dramatically increased.
These situations are antithetical to each other, with one set causing increasing portfolio and infrastructure diversity, the other demanding that fewer people create better decisions in shorter periods of time. For new megacompanies that have just completed a merger, several important tasks quickly rise to the top of the list: reduce headcount to appropriate levels, rationalize asset redundancy, optimize the portfolio of assets, and improve work processes to create a material improvement in overall performance. The first three items are traditional cost elimination; the fourth marks a fundamental change in how companies operate.
Historically, those first three cost-cutting strategies have effectively buoyed the balance sheet for the near term. But, today, managers have a new tool. Changes in operational and, thus, financial performance have been afforded by breakthroughs in the technologies that allow companies to improve the mechanical operations of drilling and maintaining oil wells and the information systems that allow them to better manage these complex subsurface assets, turning highly unconstrained problems into data-driven, statistically managed portfolios.
For example, the advent of 3D seismic data, coupled with advanced imaging algorithms and viewed in powerful graphics computers, has increased the success rate of exploration drilling as much as 80 percent. But even more importantly, these technologies have illuminated prospects that could not be previously imaged (such as complex subsalt plays) and have provided the facilities to manage reservoirs, resulting in a doubling of recovered oil. The work processes that drive this are built on advanced imaging, which leverages large, complex data models in the decision process and enables the company's best multidisciplinary experts to create investment recommendations with much higher returns.
One answer to all the challenges created by megamergers is to re-evaluate the base information technologies that drive the business of oil companies, searching for breakthrough technologies that link people and process their data across more distributed geographies in meaningful ways. Indeed, the virtual company, which has been the target of oil company research labs for more than a decade, is a clear avenue to deliver this. However, the technical problem of discovering and efficiently managing oil fields is complicated by expanding volumes of data, forcing pressures on a workforce using antiquated strategies.
A number of key technologies have proven that vastly greater amounts of data can be manipulated, especially in the seismic analysis portion of the process. There has been a rapid proliferation of large graphical computers in the industry over the past 5 years that house tens of gigabytes of seismic data, reducing analytical processes that formerly took months down to days or weeks. These systems convert data into rich images, taking full advantage of the human brain to rapidly assimilate huge volumes of information graphically viewed in large-capacity graphics computers, unlike more traditional methods (2D displays, spreadsheets, etc.) that require individual, mental assimilation of data.
Not only do the traditional methods extend the analysis timeline by orders of magnitude, they also impart nonstandard assimilated views of the data, since each member of the decision team individually assimilates the data into his or her own mental view. The use of large-format, powerful graphical decision systems has played an important role in delivering improvements in exploration success and is now being adapted to the role of reservoir modeling and management. Companies that have successfully used such systems see that these systems not only affect their exploration business materially and significantly, but they also can improve their production business. They are adapting these methods to manage their financial operations as well. In short, they have discovered that the widest imaginable spectrum of business problems is often solved through the use of graphical decision systems.
The IT goal is to bring any and every key expert into key decisions in real time, regardless of his or her geographic location, be it a field office, the field itself, the corporate office, a drilling rig, or a seismic operation. This is the concept of Distributed Graphical Decision Systems (DGDS), a business process-focused implementation of the Visual Area Network (VAN). DGDS/VAN establishes high-performance graphics as the core of the technical computing enterprise, allowing companies to analyze large, complex data volumes rapidly. The goal is to provide a mechanism by which the entire business process can be accessed and analyzed from a graphical approach, while connecting key decision-makers to the process through remote collaborative methods.
The technology is based on powerful graphics computing at its core, but it also takes into account the fact that data are distributed around the enterprise, so it includes a storage area network that provides a single-image view of a distributed data storage system. For example, adding real-time data streams from actively producing or drilling wells to a centralized decision model would best be suited by, at minimum, staging and, at best, storing data local to its source, while the enterprise would require that these data be accessible through a single file-system view to be incorporated into the decision model.
These technologies are being delivered to the industry at a time when businesses are ready to accept them and when IT infrastructures can be refreshed to leverage modern graphical systems. The ROI on achieving this next level of decision environment is measurable, predictable, demonstrable, and substantial. The delivery of such systems to the oil industry addresses difficult management questions regarding the ways that companies will
- manage a more globally distributed and diverse asset base
- with a declining population of experts broadly distributed around the globe,
- with rapidly expanding data being collected and implemented into the decision process,
- with the advent of real-time data streaming from drilling and producing wells and fields, and
- with a need to improve ROI by reducing costs, improving exploration success and increasing production efficiency.
Today's world of large mergers and an impatient investment community requires rapid adoption of strategies and technologies that keep pace with the changing business climate. The work process of the next decade will be so dependent upon large, complex data models that conventional and traditional approaches will be unable to keep companies competitive. The rapid change in both the business practice and the financial pressures on the business demand that companies find step-function improvements in their operations.
Geologist Bill Bartling is Director of Global Energy Solutions for SGI, responsible for its strategy and position in the oil and gas industry. Before joining SGI in April 2001, he held management posts with Chevron Corp., Occidental Oil and Gas, and other energy companies.
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