The best hyperbolic curve is numerically fit to production decline data from selected oil wells. A non-linear optimization computer program finds the three best values of the general hyperbolic parameters q0, a, and b using least squares regression. By using weighted residuals, better history matching is obtained than with previous least squares methods. The future rate-time behavior of a well with only a few months of production is predicted by an analogy with other similar wells.

This production extrapolation method is superior to graphical or type curve procedures since it does not require engineering judgement until the unbiased curve fit has been calculated from observed production data. The program calculates consistent results based only on production values. Then, the evaluation engineer can use his judgement and experience to modify the prediction.

Keywords:
upstream oil & gas, extrapolation, production control, decline curve, history, oil production, confidence interval, mississippi limestone well, reservoir surveillance, hyperbolic curve
Subjects:
Well & Reservoir Surveillance and Monitoring, Formation Evaluation & Management, Information Management and Systems, Production forecasting, Artificial intelligence
Copyright 1981, Society of Petroleum Engineers of AIME
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