Deep Shale Geo-Stress Mapping With Structural Disturbance Indices
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Solution Overview
Problem
Current methods for estimating and modeling in-situ geo-stress fields in deep shale gas reservoirs are inaccurate due to reliance on 3D seismic data quality and geological data integration, leading to poor prediction accuracy, especially in complex tectonic zones, which affects drilling and fracturing operations.
Innovation Solution
A method integrating finite element theory with geological, geophysical, drilling, and laboratory data to create a refined 3D finite element model, using adaptive mesh refinement and Flac3D simulation for precise geo-stress prediction, incorporating stress structural indices and disturbance factors to optimize well placement and fracturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If geophysical inversion and 3D finite element numerical simulation are used to estimate and model in-situ geo-stress fields, then the prediction of crustal stress can be performed, but the model accuracy is hard to satisfy the needs of exploration and development due to limitation of 3D geological model and calculation workload
Solution Approach 1:
The patent segments the complex 3D geological model into multiple 2D cross-sectional models at different depths and orientations. Each cross-sectional model is independently analyzed using finite element methods, which reduces the overall computational complexity while maintaining prediction accuracy. The results from multiple cross-sections are then integrated to understand the three-dimensional stress field distribution.
Solution Approach 2:
The patent transitions from traditional 3D finite element modeling to a multi-dimensional approach by analyzing multiple 2D cross-sectional slices. This dimensionality change allows the use of simpler 2D computational models to represent complex 3D geological structures, reducing calculation workload while preserving essential stress field characteristics through strategic selection of cross-sectional orientations.
2Measurement precision
If the in-situ geo-stress field is predicted based on pore pressure properties of the formation, then the stress distribution can be estimated, but the prediction accuracy is poor in complex tectonic zones where the in-situ geo-stress state has large variability
Solution Approach 1:
The patent applies local quality by analyzing stress fields in different tectonic zones using orientation-specific cross-sectional models. Instead of using a uniform prediction approach, the method selects cross-sectional orientations that are locally appropriate for each tectonic setting, allowing the model to adapt to local stress field variability and improve prediction accuracy in complex zones.
Solution Approach 2:
The patent introduces dynamics by making the cross-sectional orientation adaptable rather than fixed. The method dynamically selects the optimal cross-sectional orientation based on the specific tectonic characteristics of each zone, allowing the modeling approach to respond to varying geological conditions and improve its adaptability to complex tectonic environments.
3Measurement precision
If 3D seismic data and geological data integration is used for in-situ geo-stress prediction, then the modeling can be performed, but the acquisition quality requirements and data integration complexity reduce the practical application efficiency
Solution Approach 1:
The patent extracts the essential stress field information from complex 3D seismic and geological data by focusing on specific 2D cross-sectional slices. Instead of processing and integrating all available 3D data, the method selectively extracts representative cross-sections that capture the dominant stress field characteristics, significantly reducing data processing requirements while maintaining prediction accuracy.
Data Source
AI summary
Disclosed is a method of quantitatively evaluating structural disturbance characteristics of present in-situ geo-stress in deep shale gas reservoirs, including: measuring geomechanics key parameters of key wells in different tectonic zones within a study area; performing interpretations of single-well profile rock mechanics and continuity of the in-situ geo-stress in magnitude and direction; establishing a geological model; performing anisotropic sequential Gaussian stochastic simulation to obtain three-dimensional (3D) heterogeneous rock mechanics parameter field distribution; performing prediction of distribution of geo-stress states in the study area, and calculating a stress structural index and stress disturbance factor of the target layer and a rotation degree of a maximum horizontal principal stress; and performing quantitative evaluation on an in-situ geo-stress structural disturbance and mapping.