RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

Weiss, William W.

New Mexico Institute of Mining and Technology (United States)

关键词: 02 Petroleum;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;    Petroleum Deposits;    Exploration;    Neural Networks;   

DOI  :  10.2172/824390
RP-ID  :  NONE
RP-ID  :  AC26-99BC15218
RP-ID  :  824390

美国|英语

来源: UNT Digital Library

【 摘 要 】

Incomplete or sparse information on types of data such as geologic or formation characteristics introduces a high level of risk for oil exploration and development projects. ''Expert'' systems developed and used in several disciplines and industries have demonstrated beneficial results. A state-of-the-art exploration ''expert'' tool, relying on a computerized database and computer maps generated by neural networks, is being developed through the use of ''fuzzy'' logic, a relatively new mathematical treatment of imprecise or non-explicit parameters and values. Oil prospecting risk can be reduced with the use of a properly developed and validated ''Fuzzy Expert Exploration (FEE) Tool.'' This FEE Tool can be beneficial in many regions of the U.S. by enabling risk reduction in oil and gas prospecting as well as decreased prospecting and development costs. In the 1998-1999 oil industry environment, many smaller exploration companies lacked the resources of a pool of expert exploration personnel. Downsizing, low oil prices, and scarcity of exploration funds have also affected larger companies, and will, with time, affect the end users of oil industry products in the U.S. as reserves are depleted. As a result, today's pool of experts is much reduced. The FEE Tool will benefit a diverse group in the U.S., leading to a more efficient use of scarce funds and lower product prices for consumers. This fifth of ten semi-annual reports contains a summary of progress to date, problems encountered, plans for the next year, and an assessment of the prospects for future progress. The emphasis during the May 2001 through September 2001 was directed toward development of rules for the fuzzy system.