Borehole Image Reconstruction Using Sparse Transform Inversion
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Solution Overview
Problem
Existing borehole imaging tools often produce incomplete images due to tool limitations, leading to inefficient wellbore operations and inadequate formation interpretation.
Innovation Solution
A system and method using mathematical transformations, such as discrete cosine and Fourier transforms, to generate a complete borehole image from sparse downhole data, filling in missing data and providing 100% azimuthal coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a borehole imaging tool is used with limited size or tool specification, then the tool can be deployed in the borehole, but the generated image is incomplete
Solution Approach 1:
The patent creates a complete borehole image by copying and reconstructing missing data portions through mathematical transformations. The system generates a complete image model that includes both directly measured data and reconstructed data, effectively creating a virtual copy of the full borehole environment even when physical imaging tools cannot capture the entire circumference.
Solution Approach 2:
The patent replaces mechanical imaging limitations with mathematical transformations. Instead of relying on physical tool capabilities to capture complete images, the system uses discrete cosine transforms, Fourier transforms, and other mathematical methods to reconstruct missing image portions, substituting mechanical constraints with computational solutions.
2Loss of information
If mathematical transformations are used to generate complete borehole images, then image completeness is improved, but processing complexity increases
Solution Approach 1:
The patent transforms the imaging problem by changing parameters from spatial domain to frequency domain using mathematical transforms. By applying discrete cosine transforms and Fourier transforms, the system converts incomplete spatial data into frequency domain representations, where missing information can be reconstructed more effectively, then transforms back to generate complete images.
Solution Approach 2:
The patent introduces mathematical transformation processes as intermediaries between raw incomplete imaging data and the final complete borehole image. These transformation processes act as mediators that bridge the gap between limited measurements and complete visualization, using sparse representations and iterative reconstruction algorithms.
Data Source
AI summary
A system can receive downhole acquisition data relating to a wellbore. The system can pre-process the downhole acquisition data. The system can generate an incomplete borehole image using the downhole acquisition data. The system can determine a sparse representation based on the incomplete borehole image by performing an optimization with respect to the incomplete borehole image. The system can generate a complete borehole image based on an inverse of the sparse representation.