Digital Rock Wettability Calibration via Pore-Scale Segmentation
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Solution Overview
Problem
Current methods for calibrating rock wettability in reservoir models rely on single wettability parameters, which fail to accurately represent the complexity of multimineral and heterogeneous reservoirs, leading to errors in dynamic modeling and production forecasting.
Innovation Solution
A systematic method integrating digital rock analysis and accelerated physical experimentation to calibrate rock wettability on a pore-by-pore basis, using multiple wettability parameters such as contact angles to match imbibition capillary pressure data, allowing for simulation of various wettability scenarios like water-wet, oil-wet, and mixed-wet rocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If single wettability parameters are used to calibrate reservoir models, then the modeling process is simple, but the accuracy of representing complex multimineral and heterogeneous reservoirs deteriorates
Solution Approach 1:
The patent segments the reservoir rock into multiple mineral phases (e.g., quartz, calcite, clay) and assigns distinct wettability parameters to each phase. This segmentation allows the model to capture the heterogeneous nature of multimineral reservoirs, where different minerals exhibit different wettability characteristics, thereby resolving the contradiction between model simplicity and accuracy representation.
Solution Approach 2:
The patent applies local quality by assigning spatially varying wettability parameters to different regions and mineral phases within the reservoir model. Instead of using a uniform wettability parameter throughout, the model allows each local region and mineral type to have its own calibrated wettability characteristics, improving the representation of complex heterogeneous reservoirs while maintaining a systematic calibration approach.
2Measurement precision
If multiple wettability parameters are used to calibrate digital rock models, then the accuracy of representing complex reservoirs improves, but the complexity of the calibration process increases
Solution Approach 1:
The patent applies preliminary action by conducting physical experiments (such as imbibition and drainage tests) on core samples before digital model calibration. These experiments provide preliminary wettability data and constraints that guide the subsequent digital model calibration process, reducing the search space and making the complex multi-parameter calibration more manageable and systematic.
Solution Approach 2:
The patent implements feedback mechanisms where simulation results from the digital rock model are compared against experimental data, and the wettability parameters are iteratively adjusted to minimize discrepancies. This feedback loop systematically refines the multiple wettability parameters, making the complex calibration process more controlled and convergent rather than arbitrary.
3Ease of manufacture
If uniform wettability scenario is assumed for reservoir modeling, then the modeling process is simplified, but the representation of wettability variations in heterogeneous rocks deteriorates
Solution Approach 1:
The patent segments the reservoir into distinct mineral phases and spatial zones, each with its own wettability characteristics. This segmentation replaces the uniform wettability assumption with a phased, heterogeneous representation that captures the natural variability in multimineral rocks, thereby improving reliability while maintaining a structured modeling approach.
Solution Approach 2:
The patent changes the wettability parameters from a single uniform value to multiple spatially and mineralogically varying parameters. By allowing wettability parameters to change across different minerals and locations, the model accurately represents wettability variations in heterogeneous rocks while using systematic calibration methods to manage the increased parameter complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of digital rock models by reducing errors in dynamic modeling and production forecasting, enabling better representation of complex reservoirs and optimizing drilling and production operations.
Implementation Method 1
numerically simulate key controls that govern multiphase flow, such as relative permeability and capillary pressure curves
Implementation Method 2
spontaneous imbibition to restore reservoir wettability
Data Source
AI summary
A method is provided. Cells of a digital model of a formation are classified corresponding with one or more classes based on minerals and/or pore sizes. Wettability of the formation in the digital model is calibrated based on imbibition and/or drainage curves from physical experimentation for a rock sample and the one or more classes of the cells of the digital model.