The economic viability of a field is dependent on the quality and accuracy of lithology distribution prediction to better understand the heterogeneity of a potential reservoir. These components are the keys to successful hydrocarbon exploration and production.
LithoSI delivers quantified uncertainty in seismic lithology and fluid prediction. Using multiple elastic parameters from the inversion of seismic data, LithoSI performs a supervised Bayesian classification to deliver probability cubes of predicted lithology and/or fluid properties. The integrated inversion and classification workflow provides superior definition of lithology classes and allows more accurate assessment of lithology probabilities.
LithoSI is able to design complex multi-variate probability distribution functions to ensure that lithologies are properly classified and their probabilities accurately defined. The resulting litho-probability cubes enable the reservoir engineer to make a full assessment of the uncertainty in the range of net-pay scenarios and reduce production risks.
Relate derived volumes back to the well logs. Define probability distributions for each zone. Lithology prediction helps unravel details in the data not detected by more conventional inversion approaches. Well log information is the main source of information for lithology and fluid content. Therefore, a key step in lithology and fluid prediction is precise and careful analysis of the well data.
The addition of lithology probabilities directly based on well observations helps to reduce uncertainty in reservoir prospecting and qualification.
The integrated Strata inversion and LithoSI classification workflow delivers superior definition of lithology classes, and allows more accurate assessment of lithology probabilities. Additionally, rock physics modeling can enhance knowledge about the possible elastic property ranges that could be assigned to a lithology class. RockSI combines rock physics modeling and Monte Carlo simulations to simulate possible ranges of the elastic properties for each lithology class.
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