Pore-scale geometric models for clastic formation evaluation
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Solution Overview
Problem
Current methods for predicting petrophysical properties of subterranean earth formations, particularly permeability and capillary pressure, in clastic sediments are limited by the inability to accurately model the interrelation between different parameters, making it difficult to apply these predictions effectively in hydrocarbon exploration.
Innovation Solution
A pore-scale modeling approach is used, where a formation evaluation sensor measures properties like porosity, and a defined pore-scale model estimates additional properties such as permeability and capillary pressure by altering grain sizes, adding materials, and accounting for compaction and shale presence, using NMR signals to simulate and adjust the model parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pore-scale modeling is used to predict permeability and capillary pressure, then prediction accuracy improves, but model complexity increases
Solution Approach 1:
The patent applies parameter changes by systematically varying pore-scale geometric parameters (grain size distribution, pore throat dimensions, porosity) to match measured formation properties. The model adjusts these parameters iteratively to reproduce capillary pressure curves and permeability values, transforming a complex geometric modeling problem into a parameter optimization problem that can be solved using standard regression techniques.
Solution Approach 2:
The patent creates simplified geometric copies of the actual pore structure using idealized shapes (spheres, cylinders, capillary tubes) that replicate the essential features of complex clastic sediment pore networks. These geometric models serve as tractable representations that capture the dominant flow and pressure characteristics without requiring full 3D reconstruction of the intricate natural pore geometry.
2Productivity
If multiple sensors are run in a single wireline run to reduce rig time, then logging speed increases, but measurement precision may deteriorate
Solution Approach 1:
The patent employs a universal pore-scale modeling framework that can interpret data from multiple different sensor types (neutron porosity, density, NMR, resistivity) using the same geometric model. This multi-functional approach allows simultaneous processing of diverse measurement data streams, maintaining precision across all sensor types while enabling rapid integrated formation evaluation during single wireline runs.
Data Source
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AI summary
Parameters of a pore-scale geometric model of a clastic earth formation are adjusted so that the output of the model matches measurements made by a formation evaluation sensor or on a core sample. Additional properties of the earth formation are predicted using the pore-scale model. When NMR measurements are used, the grain size of a pore-scale geometric model of a clastic earth formation is adjusted so that the NMR relaxation time distribution output of the model matches a measured NMR distribution. Fluid drainage and imbibing can be simulated. Additional properties of the earth formation are predicted using the pore-scale model. The additional properties may be based on additional measurements of properties of a fluid in the formation.