Hierarchical Bayesian lithology/fluid prediction: A North Sea case study

@article{Rimstad2012HierarchicalBL,
  title={Hierarchical Bayesian lithology/fluid prediction: A North Sea case study},
  author={Kjartan Rimstad and Per Avseth and Henning Omre},
  journal={Geophysics},
  year={2012},
  volume={77}
}
Seismic 3D amplitude variation with offset (AVO) data from the Alvheim field in the North Sea are inverted into lithology/fluid classes, elastic properties, and porosity. Lithology/fluid maps over hydrocarbon prospects provide more reliable estimates of gas/oil volumes and improve the decision concerning further reservoir assessments. The Alvheim field is of turbidite origin with complex sand-lobe geometry and appears without clear fluid contacts across the field. The inversion is phrased in a… Expand
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References

SHOWING 1-10 OF 39 REFERENCES
Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 1 — Methodology
The focus of our study is lithology/fluid inversion with spatial coupling from prestack seismic amplitude variation with offset (AVO) data and well observations. The inversion is defined in aExpand
Bayesian lithology/fluid prediction and simulation on the basis of a Markov-chain prior model
A technique for lithology/fluid (LF) prediction and simulation from prestack seismic data is developed in a Bayesian framework. The objective is to determine the LF classes along 1D profiles throughExpand
Impact of rock-physics depth trends and Markov random fields on hierarchical Bayesian lithology/fluid prediction
Early assessments of petroleum reservoirs are usually based on seismic data and observations in a small number of wells. Decision-making concerning the reservoir will be improved if these data can beExpand
Bayesian lithology and fluid prediction from seismic prestack data
A fast Bayesian inversion method for 3D lithology and fluid prediction from prestack seismic data, and a corresponding feasibility analysis were developed and tested on a real data set. The objectiveExpand
Mapping lithofacies and pore‐fluid probabilities in a North Sea reservoir: Seismic inversions and statistical rock physics
Reliably predicting lithologic and saturation heterogeneities is one of the key problems in reservoir characterization. In this study, we show how statistical rock physics techniques combined withExpand
Stochastic reservoir characterization using prestack seismic data
Reservoir characterization must be based on information from various sources. Well observations, seismic reflection times, and seismic amplitude versus offset (AVO) attributes are integrated in thisExpand
AVO classification of lithology and pore fluids constrained by rock physics depth trends
Elastic properties of rocks are strongly influenced by local geological trends and can change markedly even within a sedimentary basin. Critical geologic factors that control elastic properties areExpand
Comparison of lithology and net pay uncertainty between deterministic and geostatistical inversion workflows
Assessment of the uncertainty associated with net pay estimates can be made from inversion of seismic data, either using deterministic inversion followed by probabilistic interpretation, or directlyExpand
Detection of reservoir quality using Bayesian seismic inversion
Sorting is a useful predictor for permeability. We show how to invert seismic data for a permeable rock sorting parameter by incorporating a probabilistic rock-physics model with floating grains intoExpand
Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion
A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysicalExpand
...
1
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