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Gonzalez, Ezequiel F. (Shell International Exploration and Production) | Gesbert, Stephane (Shell International Exploration and Production) | Hofmann, Ronny (Shell International Exploration and Production)
Using inverted seismic data from a turbidite depositional environment, we show that accounting only for rock types sampled at the wells can lead to biased predictions of the reservoir fluids. The seismic data consists of two volumes resulting from a simultaneous (multi-offset) sparse-spike inversion. As is common in an exploration setting, information from a single well (well logs and petrological analysis) was used to define an initial set of discrete “facies” that characterize both rock type and saturating fluid. Based on our geological understanding of the study area, we augmented this initial model with facies expected in the given depositional environment, yet not sampled by the well. Specifically, the new facies account for variations in both mixture type and proportions of shales and sands. The elastic property distributions of the new facies were modelled using appropriate rock physics models. Finally, a geologically consistent, spatially variant, prior probability of facies occurrence was combined with the data likelihood (per facies) to yield a Bayesian estimation of facies probability at every sample of the inverted seismic data. Accounting for the augmented geological prior in this way, we were able to generate a scenario consistent with all available data, which supports further development of the field. In contrast, using the initial, purely data-driven facies model, Bayesian classification leads to downgrading of the field''s prospectivity. We argue that limited well control in Quantitative Interpretation, especially in an exploration setting, needs to be counterweighted by robust geological prior information, in order to unbiasedly risk geological scenarios.
Harris, Peter (OHM-Rock Solid Images) | Du, Zhijun (OHM-Rock Solid Images) | Soleng, Harald H. (OHM-Rock Solid Images) | MacGregor, Lucy M. (OHM-Rock Solid Images) | Olsen, Wiebke (OHM-Rock Solid Images)
Johansen, Tor Arne (Department of Earth Science & Centre for Integrated Petroleum Research, University of Bergen, Norway) | Spikes, Kyle (Stanford Rock Physics and Borehole Project, Stanford University, USA) | Dvorkin, Jack (Stanford Rock Physics and Borehole Project, Stanford University, USA)
The use of seismic data for estimation of lithology and reservoir properties is important in seismic exploration and reservoir characterization. We present a technique for the estimation of porosity, mineral fraction (lithology) and fluid properties from seismic parameters and density. The method includes a resampling of rock physics constraints, made from some rock physics theory, which result in direct relations between the various rock properties to be estimated and each data parameter. The final estimation is made by comparing the relations obtained for all the data parameters. The method is flexible to the type of rock model considered for linking the rock properties and seismic parameters. It also reveals the non-uniqueness of the rock property solutions in case the problem is underdetermined.