Anisotropic Formation Logging via Multicomponent Signal Inversion
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Solution Overview
Problem
Existing resistivity logging systems face challenges in accurately characterizing anisotropic formations due to computational infeasibility and numerical errors associated with complex models, especially when dealing with formations that are electrically anisotropic and have varying resistivity in different directions.
Innovation Solution
The implementation of a formation logging system that uses a model accounting for anisotropic permittivity parameters, allowing for efficient inversion of single-frequency or multi-frequency multicomponent signal measurements, which includes parameters such as formation dip, anisotropic resistivity, and anisotropic permittivity, enabling accurate characterization even in the presence of anomalies like pyrite deposits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex formation models with increased parameters are used to accurately characterize anisotropic formations, then measurement precision improves, but device complexity and computational feasibility deteriorate
Solution Approach 1:
The patent extracts and isolates the critical formation parameters (horizontal resistivity Rh, vertical resistivity Rv, and dip angle θ) from the complex formation model. By focusing inversion on these specific parameters rather than attempting to characterize all formation properties, the method achieves accurate anisotropic formation characterization while avoiding the computational infeasibility of comprehensive multi-parameter models.
Solution Approach 2:
The patent transforms the formation model by parameterizing it in terms of anisotropic resistivity (Rh, Rv) and dip angle θ. This parameterization approach allows the inversion process to efficiently determine formation properties by changing and optimizing these specific parameters, thereby achieving measurement precision without requiring overly complex models with numerous parameters.
2Measurement precision
If complex formation models with increased parameters are used to accurately characterize anisotropic formations, then measurement precision improves, but computational feasibility deteriorates
Solution Approach 1:
The patent extracts and isolates the critical formation parameters (horizontal resistivity Rh, vertical resistivity Rv, and dip angle θ) from the complex formation model. By focusing inversion on these specific parameters rather than attempting to characterize all formation properties, the method achieves accurate anisotropic formation characterization while avoiding the computational infeasibility of comprehensive multi-parameter models.
Solution Approach 2:
The patent transforms the formation model by parameterizing it in terms of anisotropic resistivity (Rh, Rv) and dip angle θ. This parameterization approach allows the inversion process to efficiently determine formation properties by changing and optimizing these specific parameters, thereby achieving measurement precision without requiring overly complex models with numerous parameters.
3Measurement precision
If complex formation models with increased parameters are used to accurately characterize anisotropic formations, then measurement precision improves, but reliability deteriorates due to numerical errors
Solution Approach 1:
The patent extracts and isolates the critical formation parameters (horizontal resistivity Rh, vertical resistivity Rv, and dip angle θ) from the complex formation model. By focusing inversion on these specific parameters rather than attempting to characterize all formation properties, the method achieves accurate anisotropic formation characterization while avoiding the computational infeasibility of comprehensive multi-parameter models.
Solution Approach 2:
The patent transforms the formation model by parameterizing it in terms of anisotropic resistivity (Rh, Rv) and dip angle θ. This parameterization approach allows the inversion process to efficiently determine formation properties by changing and optimizing these specific parameters, thereby achieving measurement precision without requiring overly complex models with numerous parameters.
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 enhances inversion accuracy by simplifying the model complexity, allowing for precise determination of fluid saturations and rock types, even in complex formations, while reducing computational burdens and numerical errors.
Implementation Method 1
The transmitter antenna creates electromagnetic fields in the surrounding formation, which in turn induce a voltage in each receiver antenna.
Implementation Method 2
Many formations are electrically anisotropic, a property which is generally attributable to fine layering during the sedimentary build-up of the formation. Hence, in a formation coordinate system oriented such that the x-y plane is parallel to the formation layers and the z axis is perpendicular to the formation layers, resistivities Rx and Ry in directions x and y, respectively, are the same, but resistivity Rz in the z direction may be different from Rx and Ry.
Data Source
AI summary
Certain logging method and system embodiments obtain multi-component signal measurements from an electromagnetic logging tool conveyed along a borehole through a formation, and invert the measurements for a single frequency using an anisotropic formation model having at least dip, horizontal and vertical resistivity, and horizontal and vertical permittivity, as parameters. A resulting log is provided to represent a position dependence of at least one of said parameters or a formation property derived from at least one of said parameters. Illustrative formation properties include water saturation, rock type, and presence of pyrite or other such materials having anisotropic polarization. Inversions may be performed on measurements acquired at other frequencies to determine a representative dispersion curve for further characterization of the formation.