Borehole Gravity Sensor Array for Geologic Boundary Estimation
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Solution Overview
Problem
Borehole gravity measurements face challenges in accurately estimating geologic boundaries due to tool position and depth errors, noise contamination, and the inversion of gravity data, which often results in apparent density values that significantly differ from true bulk density.
Innovation Solution
A method involving an array of gravity sensors along a borehole to estimate geologic boundaries by generating a model with approximate boundaries, assuming minimum density changes, and using regularization techniques to distinguish true density changes from measurement errors, allowing for accurate location and thickness estimation of geologic layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inversion methods are used to process borehole gravity data, then the processing is simple, but the resulting apparent density differs significantly from true bulk density, especially when data is contaminated with noise
Solution Approach 1:
The method segments the continuous density function into discrete layers with constant density values. By dividing the formation into N layers bounded by N-1 interfaces, the complex inversion problem becomes a system of linear equations that can be solved more accurately and efficiently, reducing the discrepancy between apparent and true density while maintaining computational simplicity.
Solution Approach 2:
The patent transforms the problem from direct density estimation to estimating the depth and density contrast at discrete interfaces. This dimensional transformation converts the ill-posed continuous inversion into a better-conditioned discrete problem, improving accuracy without proportionally increasing complexity.
2Measurement precision
If sophisticated techniques with accurate sensors and exact tool location are used, then measurement precision improves, but tool position and depth errors still occur due to tool movement
Solution Approach 1:
The method performs preliminary discretization of the formation into layers with assumed constant density before inversion. This pre-structuring of the model provides a stable framework that is less sensitive to tool position variations, allowing accurate density estimation even when exact tool location is difficult to maintain.
Solution Approach 2:
The patent changes the parameters being estimated from continuous density values at every point to discrete density contrasts at specific interface depths. This parameter transformation reduces the impact of tool movement on measurement accuracy, as the discrete interface locations are less sensitive to small position variations than continuous density profiles.
3Measurement precision
If traditional inversion methods are used, then the processing is straightforward, but noise contamination causes significant deviation from true bulk density
Solution Approach 1:
By segmenting the formation into discrete layers with constant density, the method creates a regularized inversion problem that is inherently more robust to noise. The segmentation constrains the solution space, preventing noise from creating spurious density variations and improving the reliability of bulk density estimates.
Solution Approach 2:
The patent creates a simplified copy of the continuous formation as a discrete layered model. This copied model serves as a stable representation that filters out high-frequency noise while preserving the essential density structure, allowing accurate estimation of true bulk density even when original data is contaminated.
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 enhances the accuracy of geologic boundary estimation and distinguishes true density changes from noise-induced peaks, providing superior results compared to traditional methods, as demonstrated by reduced mean square errors and improved layer boundary localization.
Implementation Method 1
receiving gravity measurements from each of a plurality of gravity sensors nsj arrayed along a length of a borehole
Data Source
AI summary
A method of estimating a geology of an earth formation includes: receiving gravity measurements from each of a plurality of gravity sensors nsj arrayed along a length of a borehole in an earth formation, each of the sensors nsj generating a gravity measurement gj associated with a location zsj, each of the plurality of sensors separated by a distance h; generating a model of the earth formation that includes approximate geological boundaries Nm having an approximate depth zmk, the geological boundaries defining a number of geologic layers therebetween; assuming that each geological boundary is represented by a minimum density change and each of the geologic layers has a thickness that encompasses two or more of the plurality of sensors nsj; and estimating a location and a density change Δρ of a geologic boundary z between locations zsj and zsj+1 based on the gravity measurements gj and the distance h.