Seabed Elastic Waveform Inversion With Virtual Seismic Datasets
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Solution Overview
Problem
The challenge of modeling a subsurface area with insufficient seismic data, particularly in undersea environments where the number of available sensors is limited by harsh conditions, necessitates the generation of virtual datasets to supplement real datasets and achieve a desired degree of accuracy.
Innovation Solution
Generating virtual datasets based on the propagation of seismic waves to additional locations using real datasets, which include pressure and particle velocity estimates, dense seismic datasets, and P and S wavefield potentials below the seabed, to create a sufficient data set for accurate subsurface modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the number of seismic sensors is reduced due to harsh undersea conditions, then the difficulty of deployment and operation is reduced, but the quality and accuracy of subsurface modeling deteriorates due to insufficient data
Solution Approach 1:
The patent creates virtual seismic datasets that replicate the information content of physical sensor data. By generating synthetic datasets from limited real measurements using wave propagation modeling and boundary condition analysis, the system produces additional data points that mimic what additional physical sensors would have recorded, thereby maintaining modeling accuracy without deploying more physical sensors in harsh conditions
Solution Approach 2:
The patent introduces virtual datasets as an intermediary between limited real sensor data and the requirements for accurate subsurface modeling. These virtual datasets act as a bridge, translating sparse real measurements into a complete dataset suitable for full waveform inversion and elastic modeling, eliminating the need to deploy additional sensors in difficult undersea environments
2Device complexity
If the number of seismic sensors is reduced, then the cost and complexity of the seismic survey system is reduced, but the completeness of the seismic dataset deteriorates
Solution Approach 1:
The system creates complete virtual datasets that copy the information content of what a full sensor array would have recorded. By using wave equation modeling and boundary condition analysis, the system generates synthetic seismic traces that replicate the complete dataset required for accurate subsurface imaging, preventing information loss despite using fewer physical sensors
Solution Approach 2:
The patent transforms the problem from acquiring more physical data to generating data through parameter-based modeling. By changing from a physical acquisition approach to a computational generation approach using wave propagation parameters, boundary conditions, and elastic properties, the system recovers complete dataset information without increasing sensor count or system complexity
3Measurement precision
If virtual datasets are generated to supplement real datasets, then the accuracy of subsurface modeling is improved, but the computational complexity and processing time increases
Solution Approach 1:
The patent performs preliminary wave propagation modeling and boundary condition analysis to generate virtual datasets before the actual subsurface imaging process. By pre-computing the virtual data that would result from additional sensors, the system prepares complete datasets in advance, allowing the main imaging algorithm to run efficiently without needing to handle data acquisition complexity during processing
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
The combined use of real and virtual datasets enables effective subsurface modeling, improving the efficiency and accuracy of drilling operations by providing sufficient data for controlling drilling parameters.
Implementation Method 1
Generating virtual datasets based on the propagation of seismic waves to additional locations using real datasets
Data Source
AI summary
A method of modeling a subsurface area of a seabed using fewer seismic sensors than a seismic sensors that generate sufficient data to permit a desired model of the subsurface area. Seismic datasets are received from the fewer seismic sensors. The fewer seismic sensors are located at points defined in relation to the seabed. Boundary conditions of a seismic wavefield at a fluid-solid interface between the seabed and water above the seabed are identified. An estimation, from the seismic datasets and the boundary conditions, is made of one or more virtual datasets. Each of the virtual datasets includes corresponding estimated data for additional points defined in relation to the seabed. The points and the additional points, combined, are sufficient to permit the desired model of the subsurface area. A subsurface model of the subsurface area is generated by modeling the subsurface area using the seismic datasets and the virtual datasets.