Well-to-seismic integration for deep paleokarst reservoir characterization
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Solution Overview
Problem
Current methods for evaluating the filling characteristics of deep paleokarst reservoirs face challenges due to high heterogeneity, complex lithology, and limited resolution of seismic data, leading to inaccurate identification of reservoir structure and internal filling characteristics.
Innovation Solution
A method and system for well-to-seismic integration that acquires and preprocesses geophysical logging and seismic data, uses Principal Component Analysis (PCA) to optimize characteristic parameters, and constructs an isochronous framework model to simulate high-precision characteristic values, enabling precise characterization of reservoir morphology and filling characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional logging curves are used for detection, then longitudinal resolution is high (less than 10m near wellbore), but detection range is limited and cannot cover far-away paleokarst reservoirs
Solution Approach 1:
The patent combines well logging data with 3D seismic data to create an integrated evaluation system. The well logging provides high-resolution longitudinal data near the wellbore, while the 3D seismic provides broader spatial coverage, merging the advantages of both methods to achieve both high resolution and extended detection range.
Solution Approach 2:
The patent uses well-to-seismic integration as an intermediary approach, where well logging data serves as calibration points to improve the resolution and accuracy of seismic data interpretation. This intermediary method allows seismic attributes to be enhanced using well log information, extending the effective detection range while maintaining high resolution.
2Area of stationary object
If 3D seismic data is used for detection, then detection range is extended, but resolution ratio decreases (10m generally) and signal-to-noise ratio becomes too low for deep paleokarst reservoirs
Solution Approach 1:
The patent implements a feedback mechanism where well logging data is used to calibrate and validate seismic data interpretation. The high-resolution well log measurements provide feedback to adjust and refine the seismic attributes, improving the resolution and signal-to-noise ratio of the seismic data for deep paleokarst reservoir detection.
Solution Approach 2:
The patent performs preliminary well logging measurements and data processing before seismic data interpretation. This preliminary action of acquiring and processing well log data first allows for better preparation and calibration of the seismic data, improving the overall resolution and accuracy of the final integrated evaluation.
3Loss of information
If all logging characteristic parameters are used to describe the reservoir, then comprehensive characterization is achieved, but data complexity increases
Solution Approach 1:
The patent extracts and selects only the most relevant and informative logging parameters for the specific paleokarst reservoir evaluation. By taking out the essential parameters that provide the most critical information about reservoir characteristics, the system maintains comprehensive characterization while reducing data complexity and improving processing efficiency.
Data Source
AI summary
The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for evaluating the filling characteristics of a deep paleokarst reservoir through well-to-seismic integration, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.