Convex Hull Error Bound for Microseismic SRV
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Solution Overview
Problem
Current methods for computing the stimulated reservoir volume (SRV) in subterranean regions using microseismic data are prone to errors due to measurement uncertainties and precision limitations, which can lead to inaccurate assessments of hydrocarbon productivity and treatment efficiency.
Innovation Solution
The development of algorithms to identify a boundary of geometrical objects, such as circles or spheres, representing the uncertainty domains of microseismic event data points, which computes a convex hull to provide an error bound for the SRV, accounting for precision and run-time preferences, and handles data degeneracy explicitly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microseismic data is used to compute stimulated reservoir volume, then hydrocarbon productivity assessment is enabled, but measurement uncertainties and precision limitations cause calculation errors
Solution Approach 1:
The patent applies preliminary action by computing a convex hull boundary that encompasses all microseismic event locations and their uncertainty domains before performing SRV calculations. This pre-established geometric boundary accounts for measurement uncertainties in advance, ensuring that the SRV computation is based on a robust framework that incorporates precision limitations from the start rather than attempting to correct errors afterward.
2Measurement precision
If algorithms compute convex hull of uncertainty domains, then error bound estimation is improved, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the computational task into distinct phases: first representing each microseismic event as a separate geometrical object (circle or sphere) with its uncertainty domain, then computing the convex hull of these segmented objects. This segmentation allows the complex problem of uncertainty propagation to be broken down into manageable geometric operations, making the algorithm more tractable while maintaining accuracy.
3Measurement precision
If location uncertainty is represented by geometrical objects, then measurement precision is improved, but data processing complexity increases
Solution Approach 1:
The patent applies copying by creating simplified geometrical representations (circles in 2D, spheres in 3D) that copy the essential uncertainty characteristics of each microseismic event location. Instead of working with complex uncertainty ellipsoids or probability distributions, the method uses these simplified geometric copies that capture the uncertainty domain boundaries, enabling efficient convex hull computation while preserving the critical precision information needed for accurate SRV estimation.
Data Source
AI summary
In some aspects, a closed boundary is computed based on locations and location-uncertainty domains of microseismic events associated with a stimulation treatment of a subterranean region. The closed boundary encloses the locations and respective location-uncertainty domains of multiple microseismic event data points. An error bound of a stimulated reservoir volume (SRV) for the stimulation treatment is identified based on the closed boundary.