Coarse Layer Model Mixed Inversion for Real-Time Geosteering
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Solution Overview
Problem
Current resistivity logging technologies face challenges in achieving an optimal balance between complexity and accuracy, particularly in real-time geosteering applications, due to the computational demands of accurate inversion processes, which can lead to inefficiencies in directional well control and resource management in the oil and gas industry.
Innovation Solution
The implementation of a coarse layer model for mixed inversion purposes, which involves creating a simplified formation model by reducing the number of layers and using tilted antennas to determine formation resistivities and orientations, allowing for real-time geosteering decisions while maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an accurate inversion process is used to derive formation parameters, then measurement precision is improved, but device complexity and processing time increase
Solution Approach 1:
The patent segments the formation model into a limited number of discrete layers (e.g., 3-10 layers) with specific parameterizations. By dividing the continuous formation into discrete segments, the inversion process becomes computationally tractable while maintaining sufficient accuracy for geosteering decisions. Each layer is characterized by specific parameters (resistivity, thickness, boundaries), creating a manageable model structure.
Solution Approach 2:
The patent transforms the inversion problem by changing the parameterization approach - using a parameterized layer model with specific constraints on layer boundaries and properties. This parameterization reduces the degrees of freedom in the inversion, making the problem solvable in real-time while preserving essential formation characteristics needed for accurate geosteering.
2Productivity
If a simple formation model is used, then processing speed is improved, but measurement precision deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-defining the layer model structure, parameter relationships, and inversion algorithm before actual formation analysis. The model framework, including layer constraints and parameterizations, is prepared in advance, enabling rapid processing of formation data without sacrificing accuracy during real-time geosteering operations.
3Measurement precision
If a complex inversion model is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent implements a dynamic approach where the layer model complexity is adapted to the specific geologic situation and processing requirements. The model can be adjusted in real-time, selecting appropriate numbers of layers and parameterizations based on the formation characteristics and available processing time, optimizing the balance between accuracy and speed for each specific case.
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 enables faster and more accurate estimation of formation parameters, facilitating effective geosteering and reducing resource waste by providing a balanced complexity and accuracy in real-time monitoring and decision-making processes.
Implementation Method 1
The transmitter antenna is used to create electromagnetic fields in the surrounding formation. In turn, the electromagnetic fields in the formation induce an electrical voltage in each receiver antenna.
Data Source
AI summary
A look-ahead logging method includes obtaining an initial resistivity log. The method further includes deriving an initial formation model based on the initial resistivity log. The method further includes estimating deep resistivity measurements from the initial formation model and deriving a reduced-complexity formation model from the estimated deep resistivity measurements. The method further includes collecting actual resistivity measurements and inverting the actual resistivity measurements, using the reduced-complexity formation model, to obtain look-ahead or look-around parameter values. The method further includes displaying the look-ahead or look-around parameter values or storing the look-ahead or look-around parameter values on a non-transient information storage medium.