Wellbore Survey Weighted Averaging Error Correction
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Solution Overview
Problem
Current wellbore survey methods discard early drilling survey data, leading to reduced accuracy and inefficiency in establishing a definitive wellbore survey, as they rely on post-drilling gyroscopic surveys and do not effectively utilize data collected during the drilling process.
Innovation Solution
A computer-based method and system that combine multiple surveys from different sensors (accelerometers, gyroscopes, and magnetic sensors) using weighted averaging and least squares adjustments to correct error terms, allowing for real-time accuracy improvement during drilling by iteratively refining the survey data and incorporating data from various sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple surveys from different sensors are combined using weighted averaging, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the survey data processing by separating gross error identification from the weighted averaging process. Survey measurements are first analyzed to identify and exclude those containing gross errors, then the remaining measurements are combined using weighted averaging. This segmentation simplifies the overall complexity while maintaining high measurement precision.
Solution Approach 2:
The patent applies preliminary action by performing gross error identification before the weighted averaging process. By pre-screening and removing erroneous measurements prior to combination, the system avoids the complexity of handling errors during the averaging process itself, thus improving efficiency and maintaining precision.
2Productivity
If survey data is processed in real-time during drilling, then productivity is improved, but measurement precision may deteriorate due to accumulated errors
Solution Approach 1:
The patent implements feedback by using the identified gross errors to adjust the weighting functions in subsequent weighted averaging operations. The system continuously monitors survey measurements, identifies gross errors, and uses this information to refine the weighting applied to different sensor data, thereby maintaining high measurement precision while enabling real-time processing during drilling operations.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the weighting functions based on the identified gross errors and the characteristics of each survey measurement. By changing the weight parameters in real-time according to data quality, the system maintains measurement precision while enabling continuous processing that improves productivity.
3Measurement precision
If weighted averaging with error correction is applied, then measurement precision is improved, but loss of time increases due to iterative processing
Solution Approach 1:
The patent applies preliminary action by performing gross error identification before the weighted averaging and error correction processes. By pre-filtering erroneous measurements, the system reduces the computational burden of iterative processing, thereby minimizing time loss while maintaining high measurement precision through subsequent error correction.
Solution Approach 2:
The patent extracts and removes gross errors from the survey data before applying weighted averaging and error correction. By taking out the erroneous measurements that would require extensive iterative processing to correct, the system significantly reduces processing time while preserving measurement precision through the focused application of error correction techniques on clean data.
Data Source
AI summary
A computer-based method of generating a survey of a wellbore section is provided. The method includes analyzing a plurality of surveys of the wellbore section to identify survey measurements that do not comprise gross errors, generating an initial weighted average survey, and calculating an initial set of measurement differences between the identified survey measurements and the initial weighted average survey. The method further includes calculating a plurality of error term estimates for the plurality of surveys and using the plurality of error term estimates to correct the identified survey measurements. The method further includes generating an updated weighted average survey and calculating an updated set of measurement differences between the identified survey measurements and the updated weighted average survey.