How do you calibrate and validate your geological models with well logging data?

1 Step 1: Data preparation

Before you can use well logging data to calibrate and validate your geological models, you need to prepare the data for analysis. This involves checking the quality, accuracy, and completeness of the data, correcting any errors or anomalies, and aligning the data with the depth and coordinate system of the model. You also need to select the relevant logs that can provide useful information for the model parameters, such as porosity, permeability, lithology, and fluid saturation.

2 Step 2: Data integration

The next step is to integrate the well logging data with the geological model. This means comparing the log data with the model predictions, identifying any discrepancies or uncertainties, and adjusting the model parameters accordingly. You can use various methods to integrate the data, such as visual inspection, cross-plots, statistical analysis, or inverse modeling. The goal is to minimize the difference between the data and the model, while preserving the geological consistency and realism of the model.

3 Step 3: Data validation

After you have integrated the well logging data with the geological model, you need to validate the model performance and reliability. This means evaluating how well the model reproduces the data, as well as how well it predicts other data that were not used for calibration. You can use various criteria to validate the model, such as correlation coefficients, error metrics, confidence intervals, or sensitivity analysis. The goal is to quantify the uncertainty and variability of the model, and to assess its robustness and applicability.

4 Step 4: Data interpretation

The final step is to interpret the well logging data and the geological model in terms of their implications for reservoir characterization and management. This means extracting meaningful insights and knowledge from the data and the model, such as the distribution and heterogeneity of reservoir properties, the connectivity and compartmentalization of reservoir zones, the fluid flow and transport mechanisms, and the recovery potential and risks. You can use various tools to interpret the data and the model, such as maps, cross-sections, 3D visualizations, or simulation scenarios. The goal is to enhance your understanding and decision-making for reservoir development and optimization.

Well logging data are powerful sources of information to calibrate and validate your geological models. By following these four steps, you can improve your model quality and accuracy, reduce your model uncertainty and variability, and increase your model value and utility.

5 Here’s what else to consider

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