A MODEL FOR HYDROCARBON SATURATION DETERMINATION FROM AN ORTHOGONAL TENSOR RELATIONSHIP IN THINLY LAMINATED ANISOTROPIC RESERVOIRS

摘要

The macroscopic effect of a laminated sand-shale sequence with different resistivities results in electrical anisotropy. This effect transforms the classic scalar, low contrast laminated shaly sand problem into an orthogonal tensor relationship with the addition of a vertical resistivity parameter to the model. The horizontal tensor component of the saturation model demonstrates that the laminar shale component is a purely additive conductivity term and the conventional bulk formation resistivity (R_t) is the inverse weighted sum of the sand and shale resistivities. The vertical tensor component represents a series resistivity relationship where vertical R_t is the weighted sum of the sand and shale resistivities. Combining both vertical and horizontal tensor components yields a system of coupled, nonlinear equations that provide a more robust solution for hydrocarbon saturation than a scalar model.rnA sensitivity analysis as a function of shale and sand conductivity ratio and shale volume suggests a more confident hydrocarbon saturation estimation as a result of using both horizontal and vertical formation resistivities. Expansion of the shale conductivity term within the saturation equation corrects for dispersed clay conductivity using Qv in this two-step tensor model approach and results in an easily implemented Patchett-Herrick model.rnThis new solution was applied to a petrophysical model derived from MWD gamma ray and propagation resistivity data from a Gulf Coast well. Additional model parameters for shale and sand were estimated from adjacent well wireline data. Anisotropy from MPR™ data was used in the direct orthogonal tensor solution. This study concludes that in laminated shaly sands, the new orthogonal tensor model provides an improved solution for hydrocarbon saturation as a function of resistivity anisotropy when compared to traditional models.