A new workflow to reduce uncertainty of hydrocarbon prediction.

Integrating petroelastic modeling, stochastic seismic inversion, and Bayesian probability classification to reduce uncertainty of hydrocarbon prediction: Example from Malay Basin

Exploring hydrocarbon in structural-stratigraphical traps is challenging due to the high lateral variation of lithofluid facies. In addition, reservoir characterization is getting more obscure if the reservoir layers are thin and below the seismic vertical resolution. Our objectives are to reduce the uncertainty of reserve estimation and to predict hydrocarbon distribution more accurately in such reservoir layers by proposing a new workflow that works better than the conventional one.