pyResToolbox MCP Server

Convert Lorenz coefficient to Dykstra-Parsons beta parameter.

HETEROGENEITY QUANTIFICATION - Converts between two common measures of reservoir heterogeneity. Essential for comparing reservoirs using different heterogeneity metrics and for literature data conversion.

Parameters:

• value (float, required): Lorenz coefficient (0-1). Must be 0 ≤ L ≤ 1. Typical: 0.2-0.7. Example: 0.5 for moderate heterogeneity.

Lorenz Coefficient (L):

• Ranges from 0 (homogeneous) to 1 (completely heterogeneous)

• Based on cumulative flow capacity vs cumulative storage capacity

• Geometric interpretation: area between Lorenz curve and 45° line

• L = 2 × area between curve and diagonal

• Directly measurable from production data (PLT, tracer tests)

Dykstra-Parsons Beta (β):

• Permeability variation coefficient (dimensionless, 0-1)

• β = (k50 - k84.1) / k50

• Based on log-normal permeability distribution

• Requires permeability data (core, logs)

• Common in literature and older studies

Conversion Relationship: Beta and Lorenz are related through log-normal distribution statistics. Higher Lorenz = higher Beta (both indicate more heterogeneity).

Typical Ranges:

• L < 0.3 (homogeneous): β < 0.5

• L = 0.3-0.6 (moderate): β = 0.5-0.7

• L > 0.6 (heterogeneous): β > 0.7

Applications:

• Waterflood Sweep Efficiency: Predict vertical sweep from heterogeneity

• Vertical Conformance Analysis: Evaluate production allocation

• Reservoir Characterization: Compare reservoirs using different metrics

• Performance Prediction: Use beta in Dykstra-Parsons calculations

• Literature Conversion: Convert published beta values to Lorenz

Returns: Dictionary with:

• beta (float): Dykstra-Parsons beta coefficient (0-1)

• lorenz_coefficient (float): Input Lorenz coefficient

• method (str): "Lorenz to Dykstra-Parsons conversion"

• interpretation (dict): Heterogeneity level guidance

• inputs (dict): Echo of input parameters

Common Mistakes:

• Lorenz coefficient outside valid range (must be 0-1)

• Confusing Lorenz with other heterogeneity measures

• Using beta from wrong distribution (must be log-normal)

• Not understanding that conversion is approximate (depends on distribution)

Example Usage:

Result: β ≈ 0.6-0.7 (moderate to high heterogeneity).

Note: Conversion assumes log-normal permeability distribution. For non-log-normal distributions, conversion may be less accurate. Always validate against actual permeability data when possible.