Many times we are faced with the business decision of whether or not to develop a sand which is at the limit of seismic resolution and near the noise level of the data. The critical issue is developing a reasonable certainty that there is enough volume of hydrocarbons to develop. A popular approach is to use Bayesian methods to determine the probability of an economic volume of hydrocarbons being present. A problem with this approach when it is applied for the marginal cases that we have described is a bias to the answer. Often, this comes from a relatively strong prior constraint on the gross thickness and net-to-gross of the sands, imposed to keep the inversion focused on the correct seismic reflector. The data is whispering what the answer should be through the Bayesian apparatus, but this whisper is overwhelmed by the prior constraints. We found a simple solution to this problem – run the seismic inversion several times using the output mean of the previous inversion as the input mean of the next inversion. This methodology made the difference, in conjunction with a bandwidth improvement in the seismic data, in proving that a well should be drilled.


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