Nuclear Log Data Inversion for Geological Feature Resolution
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Solution Overview
Problem
Existing nuclear logging techniques suffer from poor resolution, leading to inaccurate identification or missed detection of geological features less than 0.6-m deep, especially in heavily stratified formations like coal bed methane or shale gas, and resistivity inversion algorithms are computationally complex, making real-time 'logging while drilling' and 'geosteering' operations challenging.
Innovation Solution
A method involving the acquisition of nuclear log data and additional high-resolution log data to identify zone boundaries, generating a modeled log, calculating zone response, and deconvolving log data to improve resolution, using a constrained inversion technique with a single vertical response function, enabling real-time processing and accurate feature discrimination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional nuclear logging techniques are used, then the logging operation can be performed, but the resolution is poor and geological features less than 0.6-m deep cannot be accurately identified
Solution Approach 1:
The formation is divided into discrete zones separated by identified boundaries from high-resolution log data. Each zone is treated as an independent entity with its own attribute value, allowing precise localization of geological features while maintaining computational efficiency through zone-based rather than continuous-depth processing
Solution Approach 2:
Boundaries between zones are identified in advance using high-resolution log data before performing the inversion on nuclear log data. This preliminary identification of zone boundaries constrains the inversion process, enabling accurate depth localization of geological features without requiring the nuclear logging tool to inherently achieve high resolution
2Measurement precision
If resistivity inversion algorithms are used to improve resolution, then measurement precision improves, but computational complexity increases making real-time operations challenging
Solution Approach 1:
The continuous inversion problem is segmented into discrete zone-based calculations. By dividing the formation into zones with identified boundaries, the computational problem transitions from solving a complex continuous inversion to performing simpler calculations for each discrete zone, significantly reducing overall computational complexity
Solution Approach 2:
The approach changes the fundamental parameter being inverted from continuous depth-dependent attributes to discrete zone-averaged attributes. This parameter transformation simplifies the mathematical inversion process while maintaining the ability to resolve geological features at the zone level, enabling real-time processing
3Manufacturing precision
If conventional nuclear logging is used, then the logging tool can operate, but it cannot accurately distinguish geological features extending over distances less than the tool resolution
Solution Approach 1:
High-resolution log data is acquired in advance to identify zone boundaries before processing the nuclear log data. This preliminary high-resolution mapping preserves vertical detail that would otherwise be lost, allowing the subsequent inversion process to accurately locate geological features even when they extend over distances less than the nuclear tool's inherent resolution
Solution Approach 2:
The high-resolution log data acts as an intermediary that bridges the gap between the low-resolution nuclear measurements and the desired high-resolution formation characterization. The boundaries derived from the high-resolution data constrain and guide the inversion process, enabling recovery of vertical detail without requiring the nuclear tool itself to achieve high resolution
Data Source
AI summary
Inverting nuclear log data for a geological formation surrounding a borehole involves acquiring nuclear log data for a borehole portion using a moveable nuclear logging tool and acquiring additional log data for the borehole portion using another logging device with superior resolution. Boundaries between adjacent zones are identified that exhibit an attribute of the geological formation to a detectably contrasting degree. From pre-acquired data describing one or more characteristics of the nuclear logging tool, a modeled log of the attributes is generated over the borehole portion, and a zone response is calculated from the pre-acquired data for each zone by using the boundaries to define an initial measure of the depth of each zone and ascribing a value of the attribute in dependence on the depth of each zone. The attribute of each zone is then calculated by deconvolving the nuclear log data using the zone response to minimize the difference between the nuclear log data and the convolution of the zone response and the attribute.