Downhole Lamination Analysis Using True Stratigraphic Thickness Index
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Solution Overview
Problem
Current methods for analyzing borehole images rely on qualitative judgments and insufficient quantitative techniques, limiting accurate lamination geometry and sequence stratigraphy analysis, as well as predictions of borehole behavior in unconventional resource environments.
Innovation Solution
A method involving downhole imaging tools and image processing systems that compute the true stratigraphic thickness index, extract lamination boundaries, and analyze lamination properties, enabling quantitative lamination analysis and sequence recognition across different scales and wells, correcting for borehole deviation and providing detailed geological insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual or semi-automatic dip picking methods are used to estimate lamination orientation and density, then the process is simple and quick, but the measurement precision and quantitative accuracy are insufficient
Solution Approach 1:
The patent replaces manual mechanical dip picking with an automated image processing system that uses computational algorithms to detect lamination boundaries, calculate dips, and generate quantitative measurements. This substitution of mechanical/manual operations with automated computational methods directly improves measurement precision while managing system complexity through software-based solutions.
Solution Approach 2:
The patent transforms qualitative visual assessment into quantitative measurements by computing specific parameters including lamination dip angles, dip azimuths, lamination thickness, and density values. This parameter transformation from qualitative to quantitative enables precise measurement while the systematic approach to parameter calculation manages the complexity of the processing system.
2Reliability
If borehole deviation is not corrected, then the analysis is simpler, but the reliability of lamination geometry analysis across different wells is compromised
Solution Approach 1:
The patent applies borehole deviation correction as a preliminary step before lamination analysis. By pre-processing the borehole trajectory data and applying correction factors to normalize dip measurements across different well paths, the system establishes reliable baseline data for well-to-well correlation. This preliminary action ensures reliability while the automated correction process manages the added complexity.
Solution Approach 2:
The patent introduces a computational correction model as an intermediary between raw borehole data and final lamination analysis. This intermediary processing layer transforms deviated well measurements into equivalent vertical well equivalents, enabling reliable cross-well comparisons. The systematic application of correction algorithms manages the complexity introduced by this intermediary step.
3Loss of information
If only single-scale lamination analysis is performed, then the processing is faster, but the loss of information about multi-scale geological features increases
Solution Approach 1:
The patent segments the lamination analysis into multiple scales by detecting and characterizing laminations at different thickness levels and spatial frequencies. This segmentation allows the system to preserve information across scales by treating each scale as a separate analytical component, preventing information loss while the modular segmented approach manages processing complexity efficiently.
Solution Approach 2:
The patent adds a scale dimension to the lamination analysis by performing measurements at multiple resolution levels and spatial scales. This dimensional expansion from single-scale to multi-scale analysis preserves comprehensive geological information while the systematic multi-dimensional approach organizes processing to maintain productivity through efficient computational algorithms.
Data Source
AI summary
Embodiments of the disclosure involve a method comprising computing a true stratigraphic thickness (“TST”) index based on one or more dynamic images, one or more measurement images, or combinations thereof. Computing the TST index comprises outputting a dynamic image value channel comprising a median value on each depth of the one or more dynamic images, a dynamic normalized image value channel comprising a normalization of the dynamic image value channel, a measurement image value channel comprising a median value on each depth of the measurement image, and the TST index. The method also involves computing a decomposition channel based on the TST, extracting lamination boundaries from the dynamic image value channel based on the decomposition channel, and computing the lamination properties based on the lamination boundaries.