Dip Determination Using Symmetry Axis Probability Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional dip determination methods in highly deviated wells are inaccurate due to their reliance on techniques developed for vertical wells, leading to errors in transverse component of layer dips, which can result in significant errors in layer geometry evaluation and drilling success or failure.
Innovation Solution
A dip determination system that uses downhole imaging tools to obtain images of geologic features, determining symmetry axes, splitting longitudinal components into sections, and combining them with transverse components to define sinusoid segments for accurate dip value assignment, and generating probability maps to estimate symmetry axes and fit sinusoids for precise dip calculation in each depth zone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional dip determination methods for vertical wells are used in highly deviated wells, then the method complexity is reduced, but the measurement precision of transverse component of dip deteriorates significantly
Solution Approach 1:
The method segments the dip determination process into multiple independent components: longitudinal component extraction, transverse component extraction, and their combination into final dip values. This segmentation allows each component to be optimized independently, resolving the contradiction by maintaining systematic structure while improving measurement precision through dedicated processing of each dip component.
Solution Approach 2:
The patent introduces a new dimensional approach by separating the dip vector into longitudinal and transverse components, then processing them through different algorithms before recombining. This dimensional decomposition enables the use of specialized image processing techniques for each component, improving overall measurement precision without proportionally increasing method complexity.
2Measurement precision
If image processing algorithms are applied to determine symmetry axes and fit sinusoids, then the measurement precision of dip values improves, but the device complexity and computational requirements increase
Solution Approach 1:
The system performs self-service by automatically extracting dip information from borehole images through integrated image processing algorithms. The symmetry axis determination and sinusoid fitting are executed autonomously by the dip determination system, eliminating the need for manual intervention and reducing operational complexity while maintaining high measurement precision.
Solution Approach 2:
The patent replaces manual mechanical measurement methods with automated image processing algorithms. Instead of physical measurement techniques, the system uses computational methods including symmetry axis calculation and sinusoid fitting to determine dip values, thereby improving precision while the automation handles the complexity management.
3Ease of operation
If manual dip interpretation is used, then the ease of operation is maintained, but the measurement precision and reliability deteriorate in highly deviated wells
Solution Approach 1:
The dip determination system performs self-service by automatically processing borehole images to extract dip information. The system independently executes image analysis, symmetry axis determination, and sinusoid fitting without requiring manual interpretation, thereby maintaining ease of operation while significantly improving reliability and accuracy in highly deviated well conditions.
Solution Approach 2:
The system incorporates feedback mechanisms where the processed dip information can be reviewed and adjusted if necessary. This feedback loop allows the system to maintain ease of operation through automation while improving reliability by allowing verification of the automated dip determination results.
Data Source
AI summary
Methods for dip determination from an image obtained by a down-hole imaging tool. For each pixel forming the image, a probability that a symmetry axis coincides with the pixel is determined. A probability map is then generated, depicting the determined probability of each pixel coinciding with the symmetry axis. The probability map and the image are then superposed to generate a mapped image. The symmetry axis is then estimated based on the mapped image. Image pixels coinciding with a boundary of the geologic feature are then selected in multiple depth zones, and a segment of a sinusoid is fitted to the selected image pixels within each depth zone. Dip within each of the depth zones is then determined based on the fitted sinusoid segments therein.