Seismic Data Interpolation via Wave-Field Transformation
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Solution Overview
Problem
Current seismic data interpolation methods face challenges in accurately combining different types of geophysical data and overcoming aliasing distortions, leading to incomplete imaging of subsurface structures and limitations in hydrocarbon reservoir detection.
Innovation Solution
A method that involves obtaining multiple types of geophysical data, performing wave-field transformations, and enforcing statistical constraints to enhance data representation, using techniques like Fourier, curvelet, or Radon transforms, and projection operators to interpolate missing data and align different data types, thereby improving data accuracy and completeness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If seismic data is acquired with larger receiver spacing to reduce costs, then acquisition cost is reduced, but measurement precision deteriorates due to incomplete subsurface imaging
Solution Approach 1:
The patent uses wave equation-based interpolation as an intermediary process to bridge the gap between sparsely sampled seismic data and the continuous subsurface model needed for accurate imaging. The wave equation acts as a physical mediator that propagates information from acquired traces to interpolate missing data, resolving the contradiction between sparse sampling and imaging accuracy.
Solution Approach 2:
The patent performs preliminary wave equation extrapolation and interpolation during the data processing stage to reconstruct missing seismic traces before final imaging. This preliminary action of filling in gaps using physical wave propagation models allows the use of sparser acquisition geometries while maintaining imaging quality.
2Measurement precision
If multiple types of geophysical data are combined to improve subsurface imaging, then measurement precision is improved, but device complexity increases due to multiple data acquisition systems
Solution Approach 1:
The patent implements a universal wave equation-based processing framework that can handle multiple types of geophysical data (seismic, electromagnetic, gravity, magnetic) through a single unified mathematical model. This multi-functional approach allows different data types to be integrated and processed together, improving imaging precision without proportionally increasing system complexity.
Solution Approach 2:
The patent merges multiple geophysical data types into a unified subsurface model by combining their respective wave equations or physical models. This consolidation allows synergistic use of different data sources to improve imaging accuracy while managing complexity through integrated processing rather than separate independent systems.
3Productivity
If traditional interpolation methods are used to fill missing seismic data, then productivity is improved by completing data gaps, but manufacturing precision deteriorates due to aliasing distortions
Solution Approach 1:
The patent replaces traditional mechanical or empirical interpolation methods (such as simple spatial averaging or kriging) with a physics-based wave equation system. This substitution uses the fundamental physical laws of wave propagation to guide interpolation, replacing ad hoc mathematical techniques with physically accurate models that eliminate aliasing artifacts while maintaining productivity.
Solution Approach 2:
The patent changes the fundamental parameter governing interpolation from statistical or spatial assumptions to physical wave propagation parameters (velocity, density, frequency). By using wave equation parameters that reflect actual subsurface physics, the interpolation maintains both efficiency and accuracy, avoiding the aliasing distortions that plague traditional methods.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively enhances geophysical data representation, reduces aliasing distortions, and improves the accuracy of subsurface imaging, enabling better prediction and extraction of hydrocarbons by interpolating missing data and combining diverse geophysical data types.
Implementation Method 1
using techniques like Fourier, curvelet, or Radon transforms
Implementation Method 2
using techniques like Fourier, curvelet, or Radon transforms
Implementation Method 3
using techniques like Fourier, curvelet, or Radon transforms
Implementation Method 4
enforcing statistical constraints to enhance data representation, using techniques like Fourier, curvelet, or Radon transforms, and projection operators to interpolate missing data
Data Source
AI summary
An exemplary embodiment of the present invention provides a method for interpolating seismic data. The method includes collecting seismic data of two or more types over a field (401), determining an approximation to one of the types of the seismic data (402), and performing a wave-field transformation on the approximation to form a transformed approximation (405), wherein the transformed approximation corresponds to another of the collected types of seismic data. The method may also include setting the transformed approximation to match the measured seismic data of the corresponding types at matching locations (408), performing a wave-field transformation on the transformed approximation to form an output approximation (412), and using the output approximation to obtain a data representation of a geological layer (416).