DAS Channel Location Accuracy via Global Inversion
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Solution Overview
Problem
Distributed Acoustic Sensing (DAS) technology faces positional uncertainty issues due to incorrect assumptions about light pulse propagation velocity and imprecise knowledge of fiber length, leading to inaccuracies in depth calibration of DAS channels, which are exacerbated by fiber overstuffing and lack of calibration points.
Innovation Solution
A methodology is developed to invert picked travel times of direct waves in DAS VSP data sets to simultaneously determine DAS channel locations and anisotropic velocities of a 3D layered model, constrained by measured well trajectories, using differential evolution and ray tracing techniques to reduce positional uncertainty to a few meters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional depth calibration methods (geophone data or optical attenuation points) are used, then the process is simple, but the measurement precision of DAS channel locations deteriorates due to insufficient calibration points or unavailability of geophone data
Solution Approach 1:
The patent introduces an intermediary inversion methodology that uses seismic wave travel time data as a mediator to indirectly determine DAS channel locations. Instead of directly measuring positions with calibration points, the system uses the travel time of seismic waves between known surface source locations and DAS channels as an intermediary parameter to infer accurate channel positions through iterative inversion, resolving the contradiction between simplicity and precision.
Solution Approach 2:
The patent replaces the mechanical/physical calibration system (geophones and optical attenuation points) with a computational inversion system. Instead of relying on physical calibration artifacts or additional hardware, the methodology substitutes a mathematical inversion process that uses existing seismic wave data to compute DAS channel locations, thereby improving precision without adding physical calibration components.
2Manufacturing precision
If incorrect assumptions about light pulse propagation velocity are made, then the calibration process is faster, but the manufacturing precision of depth calibration deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-determining the light pulse propagation velocity through an initial inversion process using seismic wave travel time data. This preliminary determination of velocity as a constraint parameter enables subsequent depth calibration to proceed accurately without requiring time-consuming iterative velocity adjustments, thus improving manufacturing precision while managing calibration time.
3Measurement precision
If fiber overstuffing occurs, then the fiber cable is protected during installation, but the measurement precision of DAS channel locations deteriorates due to increased positional uncertainty
Solution Approach 1:
The patent implements feedback by using the inverted DAS channel locations to identify and correct for fiber overstuffing effects. The inversion methodology compares expected channel positions (based on nominal fiber length) with actually inverted positions, and this feedback information is used to adjust the depth calibration model, thereby compensating for the positional shifts caused by fiber overstuffing and restoring measurement precision.
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 reduces positional uncertainty of DAS channels from tens of meters to a few meters, improving the accuracy of rock formation identification and reservoir monitoring by accurately locating DAS channels and estimating anisotropic velocities.
Implementation Method 1
A fiberoptic system may detect and allow the recording of the seismic waves as they traverse and/or reflect through the formation
Implementation Method 2
running an anisotropic ray tracing on the forward model
Implementation Method 3
using differential evolution and ray tracing techniques to reduce positional uncertainty to a few meters
Data Source
AI summary
A method for identifying a location of a distributed acoustic system channel in a distributed acoustic system. The method may comprise generating a two or three dimensional layer model interface with an information handling system, preparing a P-wave first arrival pick time table, estimating an initial model layer properties, estimating a location of the distributed acoustic system channels, preparing an overburden file of layer properties, running an anisotropic ray tracing, defining an upper and a lower limits for model parameters, specifying parameters for the inversion, running an inversion, selecting a solution based at least in part on stored error predictions, and calculating a mean and a standard deviation of an inverted model parameter.