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Article Excerpt
Schlumberger and its competitors use seismic surveying, the process of mapping subterranean rock formations with reflected sound waves, as an important first step in identification and recovery of oil and gas reserves. This complicated logistical operation commonly lasts two to six months, covers hundreds of square miles, employs scores of people, and utilizes a large variety of equipment. To win these jobs, Schlumberger participates in a closed bidding process organized by the oil companies. To succeed, it must quickly and accurately estimate the costs of seismic surveys. We developed a simulation tool to evaluate the impact of crew sizes (people and equipment), survey area, geographical region, and weather conditions on survey costs and durations. Schlumberger uses it to obtain and profit from a larger portion of the global seismic survey market. We demonstrated cost savings to clients of about $2 million on four surveys. Based on the number of surveys that Schlumberger conducts each year, it should save about $1.5 to $3 million each year.
Key words: industry: petroleum, natural gas; simulation: applications.
History: This paper was refereed.
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Schlumberger (www.slb.com) is the leading oilfield services company supplying technology, project-management, and information solutions to customers in the international oil and gas industry. Operating in more than 100 countries and employing over 50,000 people, it has annual revenues around US$10 billion. It provides various services (evaluation, development, and management) to oil companies throughout the life cycle of the reservoir. For reservoir evaluation, it uses wire-line and seismic services. For reservoir development, it supplies the services relevant to well construction and well productivity. For reservoir management, it provides software products, datamanagement services, and consulting services to help oil companies get the most out of oil wells. Schlumberger comprises two primary business segments, Oilfield Services and WesternGeco. WesternGeco, which it owns jointly with Baker Hughes, is the world's largest land seismic-surveying company.
Seismic surveying is a method of investigating subterranean rock structures and is an important technique in exploring for oil, gas, and ore deposits. In an unexplored or underexplored area, seismic surveying usually follows field geology to infer where the hydrocarbons may be located or originated and how these hydrocarbons may have moved up or sideways through subterranean rock layers, finally being trapped by some sort of cap rock or other containing structure. In addition, seismic surveying is often preceded with magnetics and possibly with gravity surveys to identify the existence and broad character of basins. Oil and gas almost always collect in sedimentary basins, and this is where the surveys are conducted.
Oil and gas companies usually initiate seismic surveys and contract them out to oilfield service companies, such as Schlumberger. The oil and gas companies control when the oil is extracted from the ground. They normally award contracts for seismic surveys using a sealed-bidding process with two to six participants. Participation in the bidding is usually tied to capabilities, and only a half dozen companies in the world are capable of handling the large-scale jobs on which Schlumberger bids. Schlumberger bases its bidding decisions on the client, the competition, its own capabilities, its available capacity, and the perceived difficulty of the job. The perceived difficulty, which is a measure of operations risk, was the main focus of our work. For Schlumberger to succeed, it must predict, quickly and accurately, the cost of performing the survey. A bid that is too high will result in its losing the contract, whereas a bid that is too low may result in its winning the contract but eventually losing money in the endeavor. In addition, a recent decline in the seismic-surveying business worldwide has caused a glut in surveying capacity, making the bidding process highly competitive. Under these circumstances, Schlumberger has lost some lucrative contracts by making bids that were considered too high and it has won some contracts on which it realized losses because of factors that were inadequately represented in constructing the bid.
Senior management of Schlumberger's seismic-surveying division decided it had to develop an improved system for determining bid amounts. Its current process of estimating costs was developed over two decades and is very simplistic (Morrice et al. 2001). Managers start by estimating costs per square mile based on past experience and modify them using multiplicative correction (or fudge) factors to represent other survey characteristics, such as terrain (for example, mountains, marshland, or desert), weather (frequent rain or snow, extreme hot or cold), and other hazards (rivers or streams, thorny bushes, and so forth). They establish these factors in an ad hoc manner based on data from surveys performed over 20 to 30 years. While this approach makes intuitive sense, it does not capture the complex logistics and the risks associated with uncertainty in a survey. Senior management recognized it needed an improved bidding-support system that would provide a competitive advantage for Schlumberger by quantifying the costs and risks associated with land seismic surveying.
A seismic survey is an intricate logistical operation that requires coordinating a large number of people and equipment. In these surveys, a paved road in the right place can shave a few days off the survey, while an unexpected wetland in the wrong place can add days. In estimating bid amounts, managers must account for these possibilities, especially since most of the information about terrain, weather, and other factors is readily available from geographical information systems (GIS) data providers. We developed an approach using discrete event simulation (DES) (Law and Kelton 2000), and Schlumberger is now using it successfully to maintain its leadership position in the seismic-survey business.
From the beginning of the project, we realized that DES would be the best technology for developing an improved bidding system (Morrice et al. 1997). DES is well suited for...
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