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A statistical solution for cost estimation in oil well drilling

Abstract

Drilling operations must be preceded by adequate planning, fulfilling the path to produce hydrocarbons at low and competitive costs. Conventional well planning is based on the personal experience of project engineers, which use information from offset wells to estimate the performances in future wells. This article reviews and discusses a published statistical methodology for planning upcoming oil wells. The statistical approach incorporates uncertainties of the process, reducing the relevance of personal decisions and supporting the staff with more realistic cost estimations. A reliable project can reduce unexpected expenditures in a long-term campaign and shorten the learning time, resulting in improved cost prediction and a better-fitted calendar. An expressive database, containing information from an onshore field in Brazil, yields a case study to demonstrate the benefits of this approach for the development of new drilling projects. The solution presented supports a more precise planning of costs, the improvement of technical limits and the development of different technologies in drilling operations in future wells.

Keywords:
geosciences; cost per meter; least squares; Amorim curve

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