The Matrix-Density / U Plot

Part 12, Chapter 12: Lithology and Mineralogy

Learning objectives

  • Compute the apparent matrix grain density and matrix U cross section
  • Read a three-mineral mix as a point inside the quartz-calcite-dolomite triangle
  • Get the mineral fractions from the point's barycentric position
  • Recognize this as matrix identification solved as a mixture

The Litho-Density Triangle

The modern lithology crossplot trades the sonic for the photoelectric factor. Strip the fluid from the density and from the volumetric cross section U=Pe ρbU = P_e,\rho_b, and you get two apparent matrix quantities, the grain density and the matrix cross section:

ρmaa=ρbβˆ’Ο•β€‰Οf1βˆ’Ο•,Umaa=Peρbβˆ’Ο•β€‰Uf1βˆ’Ο•.\rho_{maa} = \frac{\rho_b - \phi\,\rho_f}{1-\phi}, \qquad U_{maa} = \frac{P_e\rho_b - \phi\,U_f}{1-\phi}.

The three common minerals sit far apart here, quartz at (4.8, 2.65), calcite at (13.8, 2.71), dolomite at (9.0, 2.87), so they frame a wide triangle.

The matrix-density / U plot4681012142.652.702.752.802.852.90apparent matrix U_maa (barns/cc)apparent matrix density rho_maa (g/cc)quartzcalcitedolomiteA three-mineral mix is a point in the triangle; its position gives 40% quartz, 30% calcite, 30% dolomite.

Position Is the Mixture

Any three-mineral mix is a point inside the triangle, a weighted average of the three vertices. Its position reads off directly as the three fractions, the barycentric coordinates: how close the point sits to each vertex is how much of that mineral the rock holds. Porosity moves it nowhere, because the strip removes the fluid exactly.

A Solved Mixture

This is matrix identification solved, for three minerals, by pure geometry. But a rock can hold more than three components, add clay, or anhydrite, or a second carbonate, and then a triangle is no longer enough. The next section generalizes the idea into a linear solver that takes any set of logs and any list of minerals and returns all the volume fractions at once, the algebra behind every one of these crossplots.

References

  • Schlumberger (2009). Log Interpretation Charts (chart CP-21). Schlumberger Educational Services.
  • Ellis, D. V. and Singer, J. M. (2007). Well Logging for Earth Scientists, 2nd ed. Springer.

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