Mechanical Earth Model Construction Using Integrated Logging and Calibration
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Solution Overview
Problem
Current methods for constructing mechanical earth models (MEMs) in oil and gas exploration lack comprehensive integration of well logging data, geological stress regimes, and rock mechanics laboratory tests, leading to incomplete or inaccurate estimates of in-situ stresses and rock properties.
Innovation Solution
A method that integrates density logging data to compute vertical stress, applies correlation models to estimate pore pressure and mechanical properties, calibrates these with drill stem test and laboratory data, and uses poroelastic models to estimate horizontal stresses, while also evaluating breakout regions and calibrating with minifrac tests and tectonic strain patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive integration of multiple data sources (well logging, laboratory tests, geological stress regimes) is implemented, then measurement precision of in-situ stresses and rock properties is improved, but device complexity and workflow complexity increase
Solution Approach 1:
The comprehensive MEM construction process is divided into distinct sequential modules: (1) vertical stress computation from density logging, (2) pore pressure estimation using correlation models, (3) mechanical property estimation from sonic logging, (4) calibration with laboratory tests, (5) horizontal stress estimation using poroelastic models, and (6) validation with field tests. This segmentation allows each module to be developed and validated independently while maintaining overall system accuracy.
Solution Approach 2:
The patent integrates multiple previously separate data sources and methodologies into a unified MEM construction framework. Well logging data (density, sonic, caliper), laboratory test results (core plugs, rock cuttings), field test data (drill stem tests, minifrac tests), and geological stress regime information are merged and calibrated together to produce a consistent set of in-situ stress and rock property estimates, resolving the contradiction between comprehensive integration and workflow complexity.
2Reliability
If multiple calibration steps with laboratory tests and field tests are performed, then reliability of the mechanical earth model is improved, but loss of time in the construction process increases
Solution Approach 1:
Laboratory tests on core plugs and rock cuttings are performed in advance before field operations begin. These preliminary measurements of mechanical properties (Young's modulus, Poisson's ratio, unconfined compressive strength) are used to calibrate the correlation models, enabling faster pore pressure and stress estimates during well construction without requiring time-consuming iterative field testing.
Solution Approach 2:
The patent implements a feedback calibration process where initial MEM estimates from correlation models are refined using actual field test data (drill stem tests for pore pressure, minifrac tests for horizontal stresses). The discrepancies between predicted and measured values are used to adjust correlation parameters and improve subsequent estimates, maintaining high reliability while reducing the number of iterative test cycles needed.
3Productivity
If correlation models and poroelastic models are applied to estimate pore pressure and horizontal stresses, then productivity of the MEM construction process is improved, but measurement precision may be compromised due to model assumptions
Solution Approach 1:
The patent systematically varies key parameters in the correlation models (porosity, density, sonic velocity relationships) and poroelastic models (Biot coefficient, Poisson's ratio, tectonic strain rates) to match the specific geological conditions of each formation. By calibrating these parameters against laboratory test data from actual core samples and adjusting them based on field test results, the models maintain both computational efficiency and measurement precision across different rock types and stress regimes.
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 provides a more accurate and comprehensive mechanical earth model, enhancing wellbore stability analysis, sand control, and hydraulic fracturing by improving the estimation of in-situ stresses and rock properties, thereby reducing operational risks and costs.
Implementation Method 1
integrating a density logging data set to compute vertical stress
Implementation Method 2
performing sonic logging
Implementation Method 3
applying one or more correlation models or equations to estimate a pore pressure and one or more mechanical properties
Data Source
AI summary
A method of constructing a mechanical earth model (MEM) includes integrating a density logging data set to compute vertical stress and applying correlation models or equations to estimate a pore pressure and mechanical properties. The method also includes calibrating the pore pressure with drill stem test data, calibrating the mechanical properties with laboratory tests on core plugs or on rock cuttings, estimating a minimum horizontal stress using correlation models, and calibrating the minimum horizontal stress with minifrac tests. The method further includes estimating a maximum horizontal stress using the correlation models while assuming one or more correlation parameters, calibrating the maximum horizontal stress with a global pattern of tectonic strains and a basin stress regime, evaluating one or more breakout regions using the MEM, a trajectory of a well, and a geometry of a pilot hole, and comparing the one or more breakout regions and a caliper logging data set.