Shear Strength Anisotropy Prediction in Shale Formations
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Solution Overview
Problem
Current methods for predicting shear strength anisotropy in fine-grained rock formations, such as shales, are costly and time-consuming, requiring laboratory measurements and core sampling, which can damage the rock and provide unrepresentative data, while existing predictive techniques lack generality and accuracy, especially for anisotropic rock types.
Innovation Solution
A petrophysical method using geophysical wireline logs to predict shear strength anisotropy without core sampling, compiling a database of core-based measurements, applying automated surface fitting to determine a common anisotropic failure criterion, and developing predictive algorithms to calculate equivalent anisotropic strength properties for subsurface formations, enabling optimization of mud weight design in extended reach wells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If core sampling and laboratory measurements are used to predict shear strength anisotropy, then measurement precision is improved, but loss of time and loss of substance increase
Solution Approach 1:
The patent replaces mechanical core sampling and laboratory testing with geophysical wireline log measurements and petrophysical analysis. Specifically, it uses acoustic velocity logs, density logs, and resistivity logs combined with pore pressure gradient calculations to predict shear strength anisotropy, eliminating the need for physical core extraction and laboratory mechanical testing.
Solution Approach 2:
The patent introduces pore pressure gradient as an intermediary parameter that links readily available wireline log data to shear strength anisotropy predictions. By calculating pore pressure gradients from density and resistivity logs and comparing them to overburden stress, the method indirectly determines anisotropy coefficients without direct mechanical measurement.
2Measurement precision
If core sampling is performed to measure shear strength anisotropy, then measurement precision is improved, but damage to fine-grained rock formations increases
Solution Approach 1:
The patent replaces mechanical core sampling with non-invasive geophysical wireline log measurements. Acoustic velocity logs, density logs, and resistivity logs are run through the wellbore to obtain formation properties without extracting core samples, thereby preventing mechanical damage to fragile fine-grained rock formations.
Solution Approach 2:
The patent creates a virtual model of the formation's mechanical properties by copying and processing geophysical log data. Wireline logs provide a continuous record of formation properties that can be analyzed to derive shear strength anisotropy coefficients, serving as a non-destructive copy of the formation's mechanical characteristics.
3Device complexity
If existing predictive techniques are used for shear strength anisotropy, then device complexity is reduced, but manufacturing precision and reliability worsen
Solution Approach 1:
The patent changes the parameters used for prediction from simple empirical relationships to a multi-parameter system incorporating pore pressure gradient, acoustic velocity, density, and resistivity. By introducing pore pressure gradient as a key parameter and establishing its relationship with anisotropy coefficients, the method achieves higher prediction accuracy while maintaining reasonable complexity through systematic data processing.
Solution Approach 2:
The patent combines multiple geophysical log types (acoustic velocity, density, resistivity) to create a composite predictive model. By integrating data from different measurement modalities and combining them with pore pressure gradient calculations, the method achieves robust predictions of shear strength anisotropy that are more reliable than single-parameter approaches.
Data Source
AI summary
Method and system is described for modeling one or more geophysical properties of a subsurface volume. In one example, a method for predicting strength anisotropy in subsurface formations along a wellpath comprises receiving a stress model of the subsurface formation in the area of the wellpath. Bulk strength properties of target rock are obtained and used to develop anisotropic failure criteria. The stress model may then be combined with the anisotropic failure criteria to develop an anisotropic wellbore stability model which is used to enhance hydrocarbon recovery.