Gridless Volumetric Computation for Subsurface Regions
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Solution Overview
Problem
Current methods for estimating subsurface region volumes, such as those used in oil and gas reservoirs, face challenges with accuracy due to the need for either low-resolution grids that lose precision or high-resolution grids that require extensive computation time, often compromising the understanding of subsurface properties.
Innovation Solution
A novel approach using the Mean Value Theorem and Monte Carlo simulation to estimate subsurface region volumetrics independently of a grid, allowing for precise calculations of Gross Rock Volume and other volumetric measures by sampling random points within a bounding box, thereby reducing computation time without sacrificing precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution grids are used to improve measurement precision of subsurface volumes, then accuracy is improved, but computation time increases significantly
Solution Approach 1:
The patent extracts the essential volumetric information from the complex grid structure by using Monte Carlo sampling to directly estimate volumes without processing every cell. This removes the unnecessary computational burden of high-resolution grids while retaining accuracy by sampling representative points throughout the subsurface region.
Solution Approach 2:
Instead of processing all grid cells (excessive action), the method uses a partial sample of randomly selected points to estimate volumetrics. The Monte Carlo approach achieves sufficient precision with a fraction of the computational effort by leveraging statistical convergence properties.
2Productivity
If low-resolution grids are used to reduce computation time, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces the mechanical grid-based computational system with a statistical sampling approach. Instead of systematically processing grid cells, random sampling with Monte Carlo methods is used to estimate volumes, achieving both speed and accuracy without the constraints of grid resolution.
3Manufacturing precision
If grid-based methods are used to calculate subsurface volumes, then manufacturing precision is maintained through systematic cell allocation, but device complexity increases due to grid construction and cell processing
Solution Approach 1:
The patent removes the complex grid structure entirely from the volumetric calculation process. By extracting only the essential geometric boundaries and using random sampling within those bounds, the method eliminates grid construction, cell allocation, and associated complexity while maintaining precision through statistical methods.
Solution Approach 2:
Instead of building up volume calculations from discrete grid cells (bottom-up approach), the patent inverts the approach by sampling random points within the total bounding volume and statistically inferring volumetrics (top-down approach). This inversion simplifies the computational structure while preserving accuracy.
Data Source
AI summary
In some embodiments, a method for computing, by a volume data processor, volumetrics of a subsurface region without gridlines associated with the subsurface region comprises creating, in the volume data processor, a geometry representing the subsurface region and first bounding box about the geometry, computing a first probability that a group of sampled points inside the first bounding box are inside the geometry, and computing a gross rock volume (GRV) of the geometry by multiplying the first probability by a volume of the first bounding box.