Seismic Inversion Downscaling for Sparse Reservoir Data Coverage
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Solution Overview
Problem
Existing seismic surveys face challenges in providing adequate data coverage and resolution for accurate reservoir characterization, particularly in areas with low-quality or no seismic data, which hinders effective hydrocarbon exploration and drilling.
Innovation Solution
A data processing system performs seismic inversion downscaling and extrapolation processes to generate high-resolution seismic images by resampling, scaling, and extrapolating acoustic impedance data using stochastic modeling, guided by well data to fill gaps in seismic coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If seismic surveys are conducted to map sedimentary facies, then geological feature identification is improved, but data coverage and resolution are insufficient in areas with low-quality or no seismic data
Solution Approach 1:
The patent uses well data as an intermediary to bridge the gap in seismic data coverage. By integrating well logs and seismic data through joint inversion, the method transfers information from well locations to surrounding areas, effectively mediating the information loss in regions with poor seismic coverage.
Solution Approach 2:
The patent transforms seismic data from the time domain to the depth domain through velocity modeling and time-depth conversion. This parameter transformation enables better integration with well data and improves the resolution and accuracy of geological feature identification in areas with limited seismic coverage.
2Manufacturing precision
If traditional seismic inversion is performed at seismic scale, then computational efficiency is maintained, but vertical and lateral detail in porosity and permeability models is insufficient
Solution Approach 1:
The patent segments the inversion process into two distinct stages: seismic-scale inversion for broad structural framework and well-scale downscaling for detailed porosity and permeability modeling. This segmentation allows each stage to operate at its optimal resolution, achieving high-detail models without overwhelming computational complexity.
Solution Approach 2:
The patent introduces a new dimension of resolution by performing downscaling from seismic scale to well scale. This dimensional transformation in resolution space enables the generation of high-detail porosity and permeability models that capture fine vertical and lateral variations not visible at seismic scale.
3Reliability
If seismic data is used alone for reservoir characterization, then processing time is reduced, but accuracy in areas with no or low-quality seismic coverage deteriorates
Solution Approach 1:
The patent merges seismic data with well data through joint inversion and integration workflows. By combining these complementary data sources, the method achieves reliable reservoir characterization in areas with poor seismic coverage while maintaining reasonable processing time through efficient data fusion algorithms.
Data Source
AI summary
Methods for seismic imaging of a subterranean geological formation include receiving first acoustic impedance data, having a first resolution, associated with wells in a subsurface region. A system receives seismic data including second acoustic impedance data having a second resolution. The system performs a quality control process configured to identify a mismatch between the first acoustic impedance data and the second acoustic impedance data. The system resamples the second acoustic impedance data into a three-dimensional (3D) grid model. The system scales up the first acoustic impedance data into the 3D grid model. The system downscales the second acoustic impedance data controlled by the first acoustic impedance data in the 3D grid model. The system generates third acoustic impedance data representing fine-scale impedance data. The system extrapolates the fine-scale impedance into areas or regions having no seismic data coverage or poor seismic data coverage.