Core Log Depth Matching Using Cost Function Optimization
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Solution Overview
Problem
In the oil and gas industry, accurately matching core depth with log depth is challenging due to differences in measurement methods, leading to depth mismatches that complicate the calibration of petrophysical models, which is a labor-intensive and error-prone process.
Innovation Solution
A method and system using intelligent algorithms to automatically match core depth with log depth by identifying log event pairs and applying bulk-shift and local-shift depth corrections, forming a calibrated geological model based on uncalibrated well logs and reference logs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual depth calibration between core and log data is performed, then depth matching accuracy can be improved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical depth calibration with an automated computer-based system that uses cost functions and optimization algorithms to match core and log depths automatically, eliminating labor-intensive manual operations while maintaining or improving matching accuracy
Solution Approach 2:
The system enables self-calibration by allowing the computer to automatically perform depth matching using the cost function approach, where the system independently identifies optimal depth corrections without requiring continuous human intervention or expertise
2Measurement precision
If manual depth calibration is performed, then depth matching can be achieved, but error rates increase due to human involvement
Solution Approach 1:
The patent eliminates human error by replacing manual calibration processes with automated computational methods that use mathematical cost functions to objectively determine optimal depth matches, ensuring consistent and reliable results without human intervention errors
3Productivity
If automated depth matching algorithms are implemented, then processing efficiency improves, but handling of complex formations with indistinct features becomes challenging
Solution Approach 1:
The patent transforms the complex depth matching problem into a mathematical optimization problem by defining cost functions that quantify mismatches, allowing the computer to systematically evaluate and optimize depth alignments even in complex formations where traditional visual identification of peaks and troughs is difficult
4Ease of manufacture
If traditional peak-and-trough matching is used for depth calibration, then simple formations can be calibrated, but complex formations without distinct features cannot be accurately matched
Solution Approach 1:
The patent generalizes the depth matching approach by replacing reliance on specific geological features (peaks and troughs) with a universal cost function framework that can evaluate any depth alignment quality, making the method adaptable to all formation types including those without distinct features
Solution Approach 2:
The cost function-based system serves multiple purposes: it can match simple formations with distinct features, handle complex formations without clear features, and provide a unified approach that works across diverse geological conditions, eliminating the need for different methods for different formation types
Data Source
AI summary
A method may use a core sampling system for collecting a core sample with a reference log of a first property. The method may use a wellbore logging system for recording uncalibrated well logs with a target log of the first property. The method may use a computer processor for obtaining an uncalibrated geological model, determining a bulk-shift depth correction based on a first cost function, forming a bulk-shifted log by applying the bulk-shift depth correction to the target log, identifying a plurality of log event pairs, determining, for each of the log event pairs, a local-shift depth correction based on a second cost function, forming a local-shift depth correction table from the local-shift depth correction for the log event pairs, and forming a calibrated geological model based, at least in part, on the uncalibrated geological model and the local-shift depth correction table.