Uncover Details in Your Data to Reduce Uncertainty in Reservoir Characterization

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.

Quantify Uncertainty in Seismic Lithology and Fluid Prediction

Predict reservoir distribution and its quality by determining lithology parameters.

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.

Overcome Challenges

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. 

LithoSI_fig 2.0.jpg
Image shows a crossplot of inversion outputs such as P-impedance and Vp/Vs ratio. The resulting crossplot zone can be displayed as a geobody within a seismic volume.

Benefits of LithoSI

  • Superior definition of lithology classes
  • More accurate assessment of lithology probabilities
  • Stratigraphic framework facilitates interpretation
  • Net-to-gross ratio maps from litho-classification

Features of LithoSI

  • Improves on conventional crossplotting by using Bayesian statistics to calculate lithology probabilities
  • Uses 2 or 3 Strata seismic inversion output volumes, together with lithology class logs at training wells
  • Uses a confidence matrix for cross-validation, to quality control predicted results at well locations
  • Creates volumes of predicted lithologies as well as volumes of the probabilities of each lithology class

LithoSI Figure 2

Lithology Prediction Options

  • Flexible technique using multiple elastic attributes
  • Modeling of multi-variate probability density functions of arbitrary shape
  • Integrated inversion and classification workflow

Integrated Workflow

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.

LithoSI_fig 3.jpg

Case Study

See the results for yourself. Read a case study on Seismic Lithology Prediction where the above example results are taken from. 
Read Case Study
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