Core-to-Log Depth Alignment Using Cross-Correlation in Pre-Salt Carbonates
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Solution Overview
Problem
Current depth matching methods for aligning core and log data in pre-salt carbonate reservoirs are manual, time-consuming, prone to bias, and lack applicability due to the absence of conventional gamma-ray markers, leading to significant uncertainties and reduced value of core data.
Innovation Solution
An automated method using a computer-implemented algorithm for core-to-log depth matching, involving data preprocessing, outlier removal, and normalized cross-correlation to determine the optimal shift between core and log data, minimizing user intervention and accounting for the heterogeneity of pre-salt carbonate formations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual depth matching methods based on gamma ray measurements are used, then the process can be completed with existing tools, but the method lacks applicability for pre-salt carbonate rocks where conventional gamma-ray markers are absent and is time-consuming
Solution Approach 1:
The patent transforms the depth matching approach by changing the measurement parameters from gamma-ray based to acoustic impedance based. Acoustic impedance values are derived from well log data and used as correlation markers instead of gamma-ray measurements, making the method applicable to pre-salt carbonate reservoirs while enabling automated processing
Solution Approach 2:
The patent replaces manual visual correlation methods with an automated computer-implemented algorithm. The system automatically calculates acoustic impedance, performs cross-correlation analysis, and determines depth shifts without human intervention, eliminating the time-consuming nature of manual methods
2Reliability
If manual depth matching methods are used, then user judgment can be applied, but the methods are prone to bias and inconsistencies
Solution Approach 1:
The system performs self-service by automatically executing the entire depth matching process without user intervention. The algorithm independently calculates acoustic impedance, performs normalized cross-correlation, identifies maximum correlation values, and applies depth shifts automatically, eliminating human bias and inconsistencies
Solution Approach 2:
The system uses feedback through normalized cross-correlation analysis to objectively determine the optimal depth shift. By calculating correlation values across different shift amounts and selecting the shift that maximizes correlation, the system provides an objective, repeatable method that eliminates subjective judgment
3Measurement precision
If core data is used as ground truth, then accurate petrophysical measurements are obtained, but measurement divergences between core depths and log depths reduce the value of core data
Solution Approach 1:
The patent applies preliminary action by performing depth matching before core data is discarded or devalued. The automated algorithm pre-processes the data, corrects depth misalignments, and prepares the core data for accurate integration with well log data, preserving the full value of the core measurements
Data Source
AI summary
A method for performing core-to-log depth matching includes receiving input data. The input data includes core data and well log data. The method also includes performing an autonomous data preprocessing procedure to standardize the core data and the well log data to determine correlations between the core data and the well log data. The method also includes performing an autonomous outlier removal procedure to address differences in acquisition methods and measurement principles of the core data and the well log data. The method also includes automatically determining normalized cross-correlations between measurements derived from the core data and measurements derived from the well log data. The method also includes automatically shifting the measurements derived from the core data to a new depth position based upon a maximum of the normalized cross-correlations.


