Hydrocarbon resource estimation: a stochastic approach

Abstract

Genetic algorithm has been used in various applications including reserve estimations in oil and gas industry for the last few decades. It is an effective stochastic inversion technique for optimization problems. The oil and gas industry is a risk based industry due to lot of uncertainties associated in each reservoir parameter used during the reserve estimation process. Detailed analysis of input data is very much important, either for the pre-bid evaluation or after the discovery of hydrocarbons. In this paper, stochastic approach in hydrocarbon resource estimation has been discussed. The algorithm starts with development of initial population and evaluation of the same. In the second step a fitness value is assigned to each individual. The best fit parents are then selected and by crossover and mutation of new populations are generated. The same process is continued until the optimum solution is reached. The efficacy of the algorithm is tested on real data set of seismic and petrophysical data from Cambay basin. The outcome is a range of resource estimates with various probability values.