Well Log Declustering Using Orientation-Based Weighting
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Solution Overview
Problem
Conventional methods for declustering well log data fail to adequately account for wellbore and stratal orientation, leading to biased reservoir property assessments in hydrocarbon exploration, particularly in non-vertical wellbores where sampling density varies significantly due to horizontal stratification.
Innovation Solution
A system and method that determine weights for well log samples based on the orientation of the wellbore from which they were acquired, using a weight determination module to adjust sampling density and account for stratal layer dip, thereby reducing biasing in subsurface volume property assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems and methods are used for declustering well log data, then processing and storage requirements are reduced, but biasing toward targeted reservoir rock properties occurs due to inadequate accounting for wellbore and stratal orientation
Solution Approach 1:
The patent applies parameter changes by transforming the sampling data through mathematical operations that adjust for wellbore orientation. Specifically, it calculates correction factors based on wellbore angle parameters and applies these to resample the log data, thereby changing the statistical parameters of the dataset to eliminate orientation bias while maintaining processing efficiency.
2Ease of operation
If samples are acquired at constant rate along wellbores, then data collection is simplified, but sampling density varies significantly in non-vertical wellbores due to horizontal stratification
Solution Approach 1:
The patent applies preliminary action by pre-calculating orientation-based correction factors before the actual data analysis phase. These correction factors are determined based on wellbore orientation parameters and are prepared in advance to be applied during the resampling process, thereby maintaining simple data collection while achieving uniform sampling density through pre-computed adjustments.
3Productivity
If wellbore orientation is not accounted for in declustering, then processing requirements are minimized, but biasing in reservoir property assessments increases
Solution Approach 1:
The patent replaces complex mechanical resampling operations with mathematical parameter transformations. Instead of physically re-sampling the data in a complex manner, it uses mathematical correction factors derived from wellbore orientation parameters to adjust the existing samples, thereby maintaining processing efficiency while eliminating bias.
Data Source
AI summary
Wellbore data samples related to a subsurface volume of interest are weighted based on wellbore orientation and/or stratal orientation. Declustering weights are determined that account for differences in sampling density caused by wellbore and/or stratal structure orientation. The declustering weights may be implemented to weight samples of parameters taken within wellbores, and/or to update or adjust other weights determined according to other schemes.