Borehole Distance to Bed Boundary Uncertainty Quantification
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Solution Overview
Problem
Inversion methods used in petroleum drilling to determine formation properties from logging data often result in multiple solutions with unknown uncertainties, making it challenging to accurately determine the distance to bed boundaries and steer the drilling assembly effectively.
Innovation Solution
Introducing quantified noise into the logging data and performing a second inversion using the adjusted signal to calculate uncertainty, allowing for a comparison of first and second DTBB solutions to determine the uncertainty of the initial solutions, thereby informing the steering of the drilling assembly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inversion methods are used to determine formation properties from logging data, then formation properties and distance to bed boundaries can be calculated, but the results produce multiple solutions with unknown uncertainties making accurate determination difficult
Solution Approach 1:
The method performs a preliminary uncertainty analysis by adding quantified noise to the logging data before the main inversion process. This preliminary action creates multiple perturbed datasets that are inverted to establish a baseline uncertainty range, which then informs the interpretation of the main inversion results.
Solution Approach 2:
The method implements feedback by using the uncertainty information derived from noise-perturbed inversions to guide the interpretation and selection of the main inversion results. The uncertainty metrics feed back into the decision-making process for determining bed boundaries and formation properties, allowing operators to weigh multiple solutions based on their reliability.
2Reliability
If multiple inversion solutions are generated to account for uncertainties, then more comprehensive formation property assessment is achieved, but the complexity of interpreting and selecting the correct solution increases
Solution Approach 1:
The method changes the parameter of the logging data by adding quantified noise at different levels and configurations. This creates a series of perturbed datasets that are inverted to generate multiple solutions, allowing the system to assess uncertainty without fundamentally changing the inversion algorithm itself.
Solution Approach 2:
The inversion process is segmented into multiple independent inversions, each performed on a perturbed version of the logging data. This segmentation allows the complexity to be distributed across multiple simpler inversions rather than one complex iterative process, making the overall uncertainty analysis more manageable and interpretable.
3Reliability
If quantified noise is added to logging data to determine uncertainty, then uncertainty in inversion solutions can be quantified, but the processing time and computational effort increase
Solution Approach 1:
The method applies partial action by adding quantified noise at controlled levels rather than exhaustive perturbation. By using realistic noise levels based on actual measurement uncertainties, the method achieves sufficient uncertainty quantification without performing an excessive number of inversions that would dramatically increase processing time.
Data Source
AI summary
A system and method for determining an uncertainty of a distance to bed boundary (DTBB) inversion of a geologic formation. The system or method includes receiving logging data from a borehole tool, performing a first DTBB inversion using the logging data to calculate first DTBB solutions, adding quantified noise to the logging data to produce an adjusted signal, performing a second DTBB inversion using the adjusted signal to calculate second DTBB solutions, comparing the first DTBB solutions to the second DTBB solutions to determine an uncertainty of the first DTBB solutions based on a relationship of the quantified noise and the difference between the first DTBB solutions and the second DTBB solutions.