Borehole Image Reconstruction via Spatial Sensitivity Deconvolution

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Solution Overview

Problem

Conventional borehole imaging techniques produce blurry images due to factors like source-detector distance and statistical noise, which compromise the interpretative value by obscuring small geological features.

Innovation Solution

The method involves processing borehole images with a two-dimensional spatial sensitivity function to reconstruct images, accounting for tool operation principles, geometry, and sensor configuration, using mathematical equations like A·X=B or f(X)=B to compute a reconstructed image that better represents formation properties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Volume of moving object

If the distance between source and detector is increased, then the formation volume contributing to measurements is increased, but image blurriness is increased

Engineering Contradiction:

Improveformation volumeVSAvoidimage quality

Core Design Contradiction:

Volume of moving objectVSManufacturing precision

Solution Approach 1:

The patent applies deconvolution processing to change the mathematical parameters of the image data, using the spatial sensitivity function as a kernel to reverse the blurring effect and recover sharper formation images while maintaining the contribution from larger formation volumes

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces physical optimization of source-detector geometry with computational processing, using mathematical deconvolution algorithms to achieve image sharpening without requiring changes to the physical tool configuration

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If rapid rotation and short measurement times are used, then productivity is improved, but measurement noise is increased

Engineering Contradiction:

Improvemeasurement speedVSAvoidmeasurement noise

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent uses vertical averaging as a feedback mechanism where measurements from multiple rotations are combined to reduce random noise, allowing rapid rotation speeds to be maintained while achieving lower noise levels through cumulative data processing

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent applies excessive averaging beyond what would be achieved by single-rotation measurements, using multiple rotations and vertical averaging to reduce noise to levels below what would be obtained from individual measurements taken at standard rotation speeds

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If vertical and azimuthal averaging routines are applied, then measurement noise is reduced, but image blurriness is increased

Engineering Contradiction:

Improvenoise reductionVSAvoidimage quality

Core Design Contradiction:

Measurement precisionVSManufacturing precision

Solution Approach 1:

The patent inverts the conventional approach by first applying averaging to reduce noise, then using deconvolution processing with the spatial sensitivity function to reverse the blurring effect, thereby achieving both noise reduction and image sharpness simultaneously

Inventive Principle:

Principle #13The other way round (Inversion)

Solution Approach 2:

The patent introduces the spatial sensitivity function as an intermediary element that characterizes the blurring process, enabling mathematical deconvolution to reverse the averaging effect and recover sharp images from averaged data

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS8600115B2Borehole image reconstruction using inversion and tool spatial sensitivity functions

Publication Date: 2013.12.03 SCHLUMBERGER TECH CORP

AI summary

A method for reconstructing a borehole image includes determining a spatial sensitivity function for a borehole imaging tool and using the imaging tool to obtain a borehole image of a subterranean formation. A reconstructed image is then computed from the borehole image and the spatial sensitivity function.