High Definition Tomography for Velocity Model Conformity
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Solution Overview
Problem
Current seismic exploration methods, particularly in land and marine environments, face challenges in accurately determining velocity models of subsurface structures due to limitations in conventional tomographic approaches, which often result in smooth and poorly conforming velocity models that do not accurately represent geological features.
Innovation Solution
The implementation of a high definition tomography system and method that inverts densely picked dip and residual move-out data to generate structurally conformable velocity models, combining conventional reflectivity images with high-frequency velocity models to create a broadband high definition reflectivity image, enhancing the accuracy and resolution of subsurface structure representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional tomographic approaches are used to generate velocity models, then the processing is simpler and faster, but the velocity models are smooth and poorly conforming to geological structures
Solution Approach 1:
The velocity model is segmented into multiple layers with different velocity characteristics. The method divides the subsurface into discrete velocity layers, each conforming to geological structures, rather than treating it as a continuous medium. This segmentation allows the velocity model to better represent geological boundaries while maintaining computational tractability through layer-by-layer processing.
Solution Approach 2:
The method transitions from conventional 2D tomographic processing to a 3D approach by incorporating spatial variations in multiple dimensions. The velocity model is constructed in three-dimensional space with explicit consideration of spatial relationships, allowing structures to be represented in their full geometric complexity rather than being projected onto a single plane.
2Measurement precision
If conventional reflectivity imaging is used, then the processing is more straightforward, but the spatial variations and resolution of subsurface structures are insufficient
Solution Approach 1:
The method merges conventional reflectivity imaging with tomographic velocity analysis in an integrated workflow. The velocity model derived from tomography is combined with reflectivity data to produce enhanced images that incorporate both amplitude information and accurate velocity corrections. This merging allows simultaneous achievement of high resolution and structural conformity without requiring separate processing streams.
Solution Approach 2:
The method replaces conventional mechanical imaging approaches with a physics-based wave equation migration using the HD velocity model. Instead of relying on simplified ray-tracing or Kirchhoff approximations, the imaging process uses full wavefield simulations that account for complex wave propagation effects, thereby achieving superior resolution and accuracy.
3Manufacturing precision
If high definition tomography with dense sampling is implemented, then the velocity model resolution and conformity improve, but the data processing time and computational resources increase
Solution Approach 1:
The method performs preliminary processing steps including dense dip picking and residual move-out analysis before the main tomographic inversion. By preparing high-quality input data in advance with automated picking algorithms, the subsequent inversion process requires fewer iterations and less computational effort, reducing overall processing time while maintaining high resolution.
Solution Approach 2:
The method dynamically adjusts processing parameters during different stages of the workflow. Sampling density, inversion regularization parameters, and frequency content are optimized at each processing step to balance resolution and computational cost. This adaptive parameter tuning allows high-resolution results without the prohibitive computational burden of uniform ultra-fine sampling throughout the entire process.
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 significantly improves the resolution and conformity of velocity models to geological structures, providing more detailed spatial variations and improved seismic imaging, effectively addressing the limitations of conventional methods by generating high definition velocity models that better match actual subsurface features.
Implementation Method 1
measuring the time it takes for the reflections to come back to one or more receivers
Implementation Method 2
whenever a signal—optical or acoustical—travels from one medium with a first index of refraction n1 and meets with a different medium, with a second index of refraction n2, a portion of the transmitted signal is reflected at an angle equal to the incident angle (according to the well-known Snell's law), and a second portion of the transmitted signal can be refracted (again according to Snell's law)
Implementation Method 3
high definition tomography system and method that inverts densely picked dip and residual move-out data to generate structurally conformable velocity models
Data Source
AI summary
A system and method are provided for determining a broadband high definition reflectivity based image for a geographical area of interest (GAI). The system and method generate a conventional reflectivity image based on acquired seismic data for the GAI, generate a high frequency (HF) velocity model of the GAI based on the acquired seismic data, convert the HF velocity model into a low frequency (LF) reflectivity image, and adaptively merge the LF reflectivity image with the conventional reflectivity image to form the broadband HD reflectivity image of the GAI.