Using genetic algorithms for reservoir characterisation

Reservoir characterisation is the process of describing a hydrocarbon reser voir, in terms of the parameters of a numerical model, so that its performa nce can be predicted. We describe the use of a specially designed genetic a lgorithm. to search for the reservoir description that is most likely to ma tch the measurements made on the reservoir. The genetic algorithm uses six separate chromosomes for different types of reservoir parameters. Three of the chromosomes have multi-dimensional real number structures, while the ot her three chromosomes are one-dimensional binary bit arrays. Specially desi gned crossover and mutation operators have been created to work with the no n-standard genome structure. The method has been tested on a realistic, com plex synthetic reservoir model, and compared with a simulated annealing (SA ) algorithm. We have shown that our genetic algorithm produces better resul ts than the simulated annealing algorithm and results which are comparable to what might be achieved by hand, Also, we have shown that the performance of the genetic algorithm is robust to the details of how it was set up. Gi ven the ease with which the method can be cheaply parallelised, its robustn ess to lost or corrupted solutions, and that it returns a suite of good sol utions, it is an ideal method to implement as an automatic reservoir charac terisation algorithm. (C) 2001 Elsevier Science B.V.. All rights reserved.