Print this pagePetrophysical Analysis of Laminated Sand Shale Sequence in Deepwater Setting
Estimating reservoir properties of clean, course to medium grained sand is relatively simpler job. However it gets complicated in the overbank area, where thickness of the sand and shale alternations decreases below the logging tool resolution. These thin laminations require special treatment while identifying and evaluating their properties.
Geologically thin beds are defined as the most readily recognized layers of a sedimentary body, and are considered to be the basic building blocks of these bodies. Beds are bounded by depositional surfaces termed bedding surfaces.
The mains problem in directly estimating the hydrocarbon pore volume from the well logs is that it does not measure the reservoir properties of interest, i.e., the net sand thickness, sand porosity, and sand water saturation. Instead, the logs measure petrophysical properties of the rock such as bulk density and resistivity, from which the reservoir properties must be inferred. Second, the petrophysical log measurements represent averages over some collection of beds that are too thin to be measured individually. To infer reservoir properties from these measurements, therefore, it is necessary to understand how the properties of an extended reservoir volume are related to the properties of the individual bed types within that volume. The third reason is that some petrophysical properties are anisotropic — their values depend not only on the composition of the measured volume, but on a choice of orientation within that volume.
Anisotropy
further complicates the inference of reservoir properties from measured petrophysical properties. There are various techniques available in the industries for the net pay estimation like, counting laminations using the Image logs, Lam count study on cores, Thomas Stiber Technique using conventional logs etc. But the real challenge lies in the hydrocarbon saturation estimation. Some experts like to assign the same hydrocarbon saturation and porosities to thin beds as that of the thick beds. Some prefer to classify the facies based on the resistivity micro Image logs and than carry out de-convolution does derive the properties of the beds using Inverse modeling Technique. Both has some advantages / dis-advantages, but the problem gets complicated once the drilling mud is changed over to Oil Base Mud(OBM), as the facies classification is no more a easy job.
AAPG Search and Discover Article #90100©2009 AAPG International Conference and Exhibition 15-18 November 2009, Rio de Janeiro, Brazil