High-Resolution Rock Property Estimation via CT and Well Data Integration

The patent combines conventional well data with high-resolution CT scan data from rock samples to create a hybrid evaluation system. This merging allows the system to achieve high resolution for thinly laminated formations while maintaining the simplicity of conventional methods through automated integration algorithms that correlate well log data with CT-derived properties at matching depths.

The patent introduces rock core samples as an intermediary medium between conventional well data and the desired high-resolution formation properties. The CT scans of these samples serve as a bridge, providing detailed microstructural information that can be upscaled and integrated with well log data to derive formation properties at the well scale with enhanced resolution.

The patent replaces direct mechanical testing with a computational approach. Instead of performing physical mechanical tests on rock samples to obtain elastic properties, the system uses CT-derived rock properties (density, porosity, mineral composition) as input to petrophysical models and machine learning algorithms that predict elastic properties, thereby substituting mechanical measurement with computational prediction.

The patent transforms the problem from directly measuring elastic properties to deriving them through parameter transformation. The system measures easily obtainable parameters (density, porosity, mineralogy) via CT scanning and then applies mathematical relationships and empirical models to transform these parameters into elastic properties (Young's modulus, Poisson's ratio) needed for mechanical evaluation.