pyResToolbox MCP Server

Instructions

{
    "value": 0.6
}

Implementation Reference

• src/pyrestoolbox_mcp/tools/layer_tools.py:100-169 (handler)

  The main handler function decorated with @mcp.tool() that performs the beta to Lorenz conversion using the imported layer.lorenzfromb function.

  @mcp.tool()
  def beta_to_lorenz(request: LorenzRequest) -> dict:
      """Convert Dykstra-Parsons beta to Lorenz coefficient.
  
      **HETEROGENEITY CONVERSION** - Converts beta parameter to Lorenz coefficient.
      Essential for converting literature data and comparing reservoirs using
      different heterogeneity metrics.
  
      **Parameters:**
      - **value** (float, required): Dykstra-Parsons beta coefficient (0-1).
        Must be 0 ≤ β ≤ 1. Typical: 0.3-0.8. Example: 0.6 for moderate heterogeneity.
  
      **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
  
      **Lorenz Coefficient (L):**
      - Ranges from 0 (homogeneous) to 1 (completely heterogeneous)
      - Based on cumulative flow capacity vs cumulative storage capacity
      - Directly measurable from production data
      - More intuitive for production analysis
  
      **Typical Ranges:**
      - β < 0.5: Low heterogeneity (L ~ 0.2-0.3)
      - β = 0.5-0.7: Moderate (L ~ 0.3-0.5)
      - β > 0.7: High heterogeneity (L > 0.5)
  
      **Use Cases:**
      - **Literature Conversion:** Convert published beta values to Lorenz
      - **Reservoir Comparison:** Compare reservoirs using different metrics
      - **Simulation Input:** Convert beta to Lorenz for simulation models
      - **Reservoir Analog Studies:** Use analog beta values with Lorenz-based tools
      - **Historical Data:** Convert old Dykstra-Parsons studies to modern metrics
  
      **Returns:**
      Dictionary with:
      - **lorenz_coefficient** (float): Lorenz coefficient (0-1)
      - **beta** (float): Input beta coefficient
      - **method** (str): "Dykstra-Parsons to Lorenz conversion"
      - **inputs** (dict): Echo of input parameters
  
      **Common Mistakes:**
      - Beta coefficient outside valid range (must be 0-1)
      - Confusing beta with other variation coefficients
      - Using beta from wrong distribution (must be log-normal)
      - Not understanding that conversion is approximate (depends on distribution)
  
      **Example Usage:**
      ```python
      {
          "value": 0.6
      }
      ```
      Result: L ≈ 0.4-0.5 (moderate heterogeneity).
  
      **Note:** Conversion assumes log-normal permeability distribution. For
      non-log-normal distributions, conversion may be less accurate. Always
      validate against actual production data when possible.
      """
      lorenz = layer.lorenzfromb(B=request.value)
  
      return {
          "lorenz_coefficient": float(lorenz),
          "beta": request.value,
          "method": "Dykstra-Parsons to Lorenz conversion",
          "inputs": request.model_dump(),
      }

• src/pyrestoolbox_mcp/models/layer_models.py:7-11 (schema)

  Pydantic BaseModel defining the input schema for the tool, with a single 'value' field validated between 0 and 1.

  class LorenzRequest(BaseModel):
      """Request model for Lorenz coefficient calculation."""
  
      value: float = Field(..., ge=0, le=1, description="Lorenz or beta value")

• src/pyrestoolbox_mcp/server.py:21-29 (registration)

  Imports and calls register_layer_tools(mcp) to register all layer tools including beta_to_lorenz with the FastMCP server.

  from .tools.layer_tools import register_layer_tools
  from .tools.library_tools import register_library_tools
  
  register_oil_tools(mcp)
  register_gas_tools(mcp)
  register_inflow_tools(mcp)
  register_simtools_tools(mcp)
  register_brine_tools(mcp)
  register_layer_tools(mcp)