Seismic Attribute Mapping for Source Rock Characterization
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Solution Overview
Problem
Conventional techniques for mapping hydrocarbon source rock quality and maturity using seismic data are inadequate, often leading to false positives and inaccurate predictions due to the failure to account for compaction effects and the intertwined mechanical and chemical effects on rock properties, and lack applicability in assessing thermal maturity and hydrocarbon generation potential.
Innovation Solution
A method that combines seismic data with well log data and geochemical data to derive new seismic attributes such as Trend-Normalized Reflectivity and inverted Vp/Vs, which are used to map organic richness and thickness, and predicts Total Organic Carbon (TOC) and thermal maturity by accounting for depth-dependent compaction and exhumation effects, providing a globally applicable approach for source rock characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic attributes (acoustic impedance, Class IV AVO) are used to map source rock, then source rock location can be identified, but false positives occur and source rock quality prediction is inaccurate
Solution Approach 1:
The patent transforms conventional seismic attributes (acoustic impedance, AVO) into new derived attributes (trend-normalized reflectivity, inverted Vp/Vs ratio) that specifically isolate organic richness signals from compaction effects. This parameter transformation resolves the contradiction by changing the measurement basis to one that is insensitive to depth-dependent compaction, thereby improving both identification accuracy and quality prediction reliability simultaneously.
Solution Approach 2:
The patent introduces well log data and geochemical data as intermediary references to calibrate and validate the seismic attribute interpretations. These intermediaries provide ground truth measurements of organic richness and maturity that bridge the gap between seismic observations and actual source rock properties, eliminating false positives and improving prediction reliability.
2Productivity
If simple regional models are used for lateral and vertical extrapolation of source rock properties, then extrapolation beyond well control is possible, but source rock variability at basin and prospect scale is not adequately predicted
Solution Approach 1:
The patent creates a universally applicable framework that integrates multiple data types (seismic, well logs, geochemical) and multiple attributes (trend-normalized reflectivity, inverted Vp/Vs, maturity indicators) into a single source rock characterization system. This multi-functional approach enables accurate prediction of source rock variability across all scales from well-to-basin while maintaining precision, resolving the contradiction between extrapolation coverage and prediction accuracy.
3Quantity of substance
If rock physics models that treat mechanical and chemical compaction as independent are used, then local data fitting is achieved, but the intertwined effects on rock properties are not captured
Solution Approach 1:
The patent employs feedback mechanisms where well log and geochemical data continuously constrain and refine the seismic attribute interpretations. The derived attributes are validated against independent measurements of organic richness and maturity, creating a closed-loop system that captures the complex intertwined effects of mechanical and chemical compaction. This feedback-driven approach enables both local data fitting and global applicability simultaneously.
Data Source
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AI summary
A method is described for identifying source rocks in a subsurface volume of interest. The method may include generating a trend-normalized reflectivity seismic attribute and calculating the location, thickness, organic richness and thermal maturity of the potential source rocks based on seismic data. The method may be executed by a computer system.